← Lex Fridman

Eugenia Kuyda: Friendship with an AI Companion

第121期2020-09-05English

嘉宾:Eugenia Kuyda

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§01Transcript · 00:00–09:12

00:00The following is a conversation with Eugenia Koida,

00:03co-founder of Replica, which is an app that allows you

00:07to make friends with an artificial intelligence system,

00:10a chatbot that learns to connect with you on an emotional,

00:14you could even say a human level, by being a friend.

00:18For those of you who know my interest in AI

00:20and views on life in general,

00:22know that Replica and Eugenia's line of work

00:26is near and dear to my heart.

00:28The origin story of Replica is grounded

00:30in a personal tragedy of Eugenia losing her close friend,

00:34Roman Mazurenki, who was killed crossing the street

00:37by a hit and run driver in late 2015.

00:41He was 34.

00:43The app started as a way to grieve the loss of a friend

00:46by training a chatbot neural net on text messages

00:49between Eugenia and Roman.

00:51The rest is a beautiful human story

00:54as we talk about with Eugenia.

00:56When a friend mentioned Eugenia's work to me,

00:58I knew I had to meet her and talk to her.

01:00I felt before, during, and after that this meeting

01:04would be an important one in my life, and it was.

01:07I think in ways that only time will truly show,

01:10to me and others.

01:12She's a kind and brilliant person.

01:15It was an honor and a pleasure to talk to her.

01:18Quick summary of the sponsors,

01:20DoorDash, Dollar Shave Club, and Cash App.

01:24Click the sponsor links in the description

01:25to get a discount and to support this podcast.

01:29As a side note, let me say that deep, meaningful connection

01:32between human beings and artificial intelligence systems

01:36is a lifelong passion for me.

01:38I'm not yet sure where that passion will take me,

01:40but I decided some time ago that I will follow it boldly

01:44and without fear, to as far as I can take it.

01:48With a bit of hard work and a bit of luck,

01:50I hope I'll succeed in helping build AI systems

01:53that have some positive impact on the world

01:56and on the lives of a few people out there.

01:59But also, it is entirely possible that I am, in fact,

02:03one of the chatbots that Eugenia

02:06and the Replica team have built.

02:08And this podcast is simply a training process

02:11for the neural net that's trying to learn

02:13to connect to human beings, one episode at a time.

02:18In any case, I wouldn't know if I was or wasn't.

02:21And if I did, I wouldn't tell you.

02:24If you enjoy this thing, subscribe on YouTube,

02:26review it with 5 Stars on Apple Podcasts,

02:28follow on Spotify, support on Patreon,

02:31or connect with me on Twitter @LexFriedman.

02:34As usual, I'll do a few minutes of ads now

02:36and no ads in the middle.

02:37I'll try to make these interesting,

02:39but give you timestamps so you can skip.

02:41But please do still check out the sponsors

02:44by clicking the links in the description

02:46to get a discount, buy whatever they're selling.

02:49It really is the best way to support this podcast.

02:52This show is sponsored by Dollar Shave Club.

02:56Try them out with a one-time offer for only five bucks

02:59and free shipping at dollarshave.com/lex.

03:03The starter kit comes with a six blade razor,

03:05refills, and all kinds of other stuff

03:08that makes shaving feel great.

03:09I've been a member of Dollar Shave Club for over five years.

03:14I actually signed up when I first heard about them

03:16on the Joe Rogan Experience podcast.

03:19And now, friends, we have come full circle.

03:22It feels like I made it, now that I can do a read for them

03:25just like Joe did all those years ago,

03:28back when he also did ads for some less reputable companies,

03:33let's say, that you know about if you're a true fan

03:37of the old school podcasting world.

03:40Anyway, I just used the razor and the refills,

03:42but they told me I should really try out the shave butter.

03:45I did, I love it.

03:47It's translucent somehow, which is a cool new experience.

03:51Again, try the Ultimate Shave Starter set today

03:54for just five bucks plus free shipping

03:56at dollarshaveclub.com/lex.

03:59This show is also sponsored by DoorDash.

04:03Get $5 off and zero delivery fees

04:05on your first order of 15 bucks or more

04:08when you download the DoorDash app and enter code,

04:11you guessed it, Lex.

04:13Have so many memories of working late nights

04:16for a deadline with a team of engineers,

04:18whether that's for my PhD at Google or MIT,

04:21and eventually taking a break to argue about

04:24which DoorDash restaurant to order from.

04:26And when the food came, those moments of bonding,

04:29of exchanging ideas, of pausing to shift attention

04:32from the programs to humans were special.

04:36For a bit of time, I'm on my own now,

04:38so I missed that camaraderie,

04:39but actually I still use DoorDash a lot.

04:43There's a million options that fit

04:44into my crazy keto diet ways.

04:47Also, it's a great way to support restaurants

04:49in these challenging times.

04:51Once again, download the DoorDash app

04:53and enter code Lex to get five bucks off

04:55and zero delivery fees on your first order of $15 or more.

04:59Finally, this show is presented by Cash App,

05:02the number one finance app in the App Store.

05:04I can truly say that they're an amazing company,

05:07one of the first sponsors, if not the first sponsor,

05:10to truly believe in me.

05:12And I think quite possibly the reason

05:15I'm still doing this podcast.

05:16So I am forever grateful to Cash App.

05:20So thank you.

05:21And as I said many times before,

05:23use code LexPodcast when you download the app

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05:29Cash App lets you send money to friends,

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05:36I usually say other stuff here in the read,

05:38but I wasted all that time up front

05:40saying how grateful I am to Cash App.

05:42I'm going to try to go off the top of my head

05:45a little bit more for these reads

05:47because I'm actually very lucky to be able to choose

05:49the sponsors that we take on.

05:51And that means I can really only take on the sponsors

05:54that I truly love.

05:55And then I could just talk about why I love them.

05:57So it's pretty simple.

05:59Again, get Cash App from the App Store or Google Play,

06:02use code LexPodcast, get 10 bucks,

06:04and Cash App will also donate 10 bucks to FIRST,

06:07an organization that is helping to advance robotics

06:09and STEM education for young people around the world.

06:12And now here's my conversation with Eugenia Kuida.

06:17Okay, before we talk about AI

06:20and the amazing work you're doing,

06:22let me ask you ridiculously, we're both Russian,

06:24so let me ask you a ridiculously romanticized

06:27Russian question.

06:28Do you think human beings are alone,

06:33like fundamentally on a philosophical level?

06:37Like in our existence, when we like go through life,

06:42do you think just the nature of our life is loneliness?

06:48- Yeah, so we have to read Dostoyevsky at school,

06:53as you probably know.

06:54- In Russian?

06:55- Yeah, I mean, it's part of the school program.

06:59So I guess if you read that,

07:01then you sort of have to believe that.

07:03You're made to believe that you're fundamentally alone

07:06and that's how you live your life.

07:07- How do you think about it?

07:09You have a lot of friends, but at the end of the day,

07:13do you have like a longing for connection with other people?

07:17That's maybe another way of asking it.

07:20Do you think that's ever fully satisfied?

07:22- I think we are fundamentally alone.

07:25We're born alone, we die alone,

07:27but I view my whole life as trying to get away from that,

07:32trying to not feel lonely.

07:34And again, we're talking about subjective

07:37way of feeling alone.

07:40It doesn't necessarily mean

07:40that you don't have any connections

07:42or you are actually isolated.

07:44- You think it's a subjective thing,

07:47but like, again, another absurd measurement-wise thing,

07:52how much loneliness do you think there is in the world?

07:55So like, if you see loneliness as a condition,

08:00how much of it is there?

08:04What do you think?

08:05Like how, I guess how many,

08:07there's all kinds of studies and measures

08:08of how many people in the world feel alone.

08:12There's all these like measures of how many people

08:15are self-report or just all these kinds

08:18of different measures, but in your own perspective,

08:21how big of a problem do you think it is size-wise?

08:27- Well, I'm actually fascinated by the topic of loneliness.

08:30I try to read about it as much as I can.

08:33What really, and I think there's a paradox

08:37'cause loneliness is not a clinical disorder.

08:39It's not something that you can get your insurance

08:41to pay for if you're struggling with that.

08:43Yet it's actually proven and pretty,

08:47tons of papers, tons of research around that.

08:50It is proven that it's correlated

08:53with earlier life expectancy, shorter lifespan.

08:58And it is in a way like right now,

09:00what scientists would say that it's a little bit worse

09:02than being obese or not actually doing

09:05any physical activity in your life.

09:08- In terms of the impact on your health.

09:08- In terms of impact on your physiological health, yeah.

09:10So it's basically puts you,

09:12if you're constantly feeling lonely,

§02Transcript · 09:14–18:01

09:14your body responds like it's basically

09:17all the time under stress.

09:19So it's always in this alert state.

09:23And so it's really bad for you

09:24because it actually like drops your immune system

09:25and your response to inflammation is quite different.

09:29So all the cardiovascular diseases

09:33actually responds to viruses.

09:34So it's much easier to catch a virus.

09:36- That's sad now that we're living in a pandemic

09:40and it's probably making us a lot more alone

09:42and it's probably weakening the immune system,

09:44making us more susceptible to the virus.

09:47It's kind of sad.

09:51- Yeah, the statistics are pretty horrible around that.

09:54So around 30% of all millennials report

09:57that they're feeling lonely constantly.

09:59- 30?

10:00- 30% and then it's much worse for Gen Z.

10:02And then 20% of millennials say that they feel lonely

10:05and they also don't have any close friends.

10:07And then I think 25 or so,

10:09and then 20% would say they don't even have acquaintances.

10:12- And that's the United States?

10:13- That's in the United States.

10:15And I'm pretty sure that it's much worse everywhere else.

10:17Like in the UK, I mean, it was widely tweeted

10:21and posted when they were talking about

10:24a minister of loneliness that they wanted to appoint

10:26because four out of 10 people in UK feel lonely.

10:30So I think we don't--

10:31- Minister of loneliness.

10:32- I mean, I think that thing actually exists.

10:34So yeah, you will die sooner if you are lonely.

10:40And again, this is only when we're only talking

10:43about your perception of loneliness or feeling lonely.

10:47That is not objectively being fully socially isolated.

10:51However, the combination of being fully socially isolated

10:54and not having many connections and also feeling lonely,

10:57that's pretty much a deadly combination.

11:00So it strikes me bizarre or strange

11:03that this is a wide known fact.

11:06And then there's really no one working really on that

11:10because it's subclinical.

11:12It's not clinical.

11:12It's not something that you can,

11:14we'll tell you a doctor and get a treatment or something.

11:17Yet it's killing us.

11:19- Yeah, so there's a bunch of people trying to evaluate,

11:22like try to measure the problem by looking at like

11:25how social media is affecting loneliness

11:27and all that kind of stuff.

11:28So it's like measurement.

11:29Like if you look at the field of psychology,

11:31they're trying to measure the problem

11:33and not that many people actually, but some.

11:36But you're basically saying how many people

11:39are trying to solve the problem.

11:41Like how would you try to solve the problem of loneliness?

11:48Like if you just stick to humans,

11:52I mean, or basically not just the humans,

11:55but the technology that connects us humans,

11:57do you think there's a hope for that technology

12:00to do the connection?

12:02Like are you on social media much?

12:05- Unfortunately.

12:07- Do you find yourself like, again,

12:10if you sort of introspect about how connected you feel

12:13to other human beings, how not alone you feel,

12:16do you think social media makes it better or worse?

12:19Maybe for you personally or in general?

12:22- I think it's easier to look at some stats.

12:25And I mean, Gen Z seems to be, Generation Z

12:28seems to be much lonelier than millennials

12:31in terms of how they report loneliness.

12:33They're definitely the most connected

12:35generation in the world.

12:36I mean, I still remember life without an iPhone,

12:40without Facebook.

12:41They don't know that that ever existed

12:43or at least don't know how it was.

12:46So that tells me a little bit about the fact

12:49that that might be, you know, this hyperconnected world

12:54might actually make people feel lonelier.

12:58I don't know exactly what the measurements are around that,

13:01but I would say, you know, in my personal experience,

13:03I think it does make you feel a lot lonelier.

13:06Mostly, yeah, we're all super connected,

13:09but I think loneliness, the feeling of loneliness

13:10doesn't come from not having any social connections

13:14whatsoever.

13:15Again, in terms of people that are in long-term

13:18relationships experience bouts of loneliness

13:20and continued loneliness.

13:22And it's more the question about the true connection,

13:25about actually being deeply seen, deeply understood.

13:29And in a way, it's also about your relationship

13:33with yourself.

13:34Like in order to not feel lonely,

13:36you actually need to have a better relationship

13:39and feel more connected to yourself.

13:41Then this feeling actually starts to go away a little bit.

13:44And then you open up yourself to actually meeting

13:48other people in a very special way,

13:51not in just, you know, add a friend on Facebook kind of way.

13:55- So just to briefly touch on it, I mean,

13:58do you think it's possible to form that kind of connection

14:00with AI systems?

14:04More down the line of some of your work,

14:07do you think that's engineering-wise a possibility

14:13to alleviate loneliness is not with another human,

14:17but with an AI system?

14:18- Well, I know that's a fact.

14:22That's what we're doing.

14:23And we see it and we measure that.

14:24And we see how people start to feel less lonely

14:27talking to their virtual AI friend.

14:32- So basically a chatbot at the basic level,

14:35but could be more.

14:36Like, do you have, I'm not even speaking sort of

14:41about specifics, but do you have a hope?

14:43Like if you look 50 years from now,

14:46do you have a hope that there's just like AIs

14:48that are like optimized for, let me first start,

14:53like right now, the way people perceive AI,

14:55which is recommender systems for Facebook and Twitter,

15:00social media, they see AI as basically destroying,

15:04first of all, the fabric of our civilization,

15:06but second of all, making us more lonely.

15:08Do you see like a world where it's possible

15:10to just have AI systems floating about

15:13that like make our life less lonely?

15:17Yeah.

15:19Make us happy?

15:20Like are putting good things into the world

15:24in terms of our individual lives?

15:26- Yeah, I totally believe in that.

15:28That's why I'm also working on that.

15:30I think we need to also make sure

15:33that what we're trying to optimize for,

15:36we're actually measuring.

15:37And it is an orthometric that we're going after.

15:40And all of our product and all of our business models

15:42are optimized for that.

15:44Because you can talk, you know,

15:45a lot of products that talk about, you know,

15:47making you feel less lonely

15:49or making you feel more connected,

15:51they're not really measuring that.

15:52So they don't really know whether their users

15:54are actually feeling less lonely in the long run

15:57or feeling more connected in the long run.

15:59So I think it's really important to put your--

16:01- To measure it.

16:02- Yeah, to measure it.

16:03- What's a good measurement of loneliness?

16:07- Well, so that's something that I'm really interested in.

16:10How do you measure that people are feeling better

16:13or that they're feeling less lonely?

16:15With loneliness, there's a scale.

16:16There's a UCLA 20 and UCLA 3 recently scale,

16:19which is basically a questionnaire that you fill out.

16:22And you can see whether in the long run

16:25it's improving or not.

16:26- And that, does it capture the momentary

16:29feeling of loneliness?

16:32Does it look in like the past month?

16:35Like, is it basically self-report?

16:38Does it try to sneak up on you?

16:39Try to trick you to answer honestly or something like that?

16:44Well, what's, yeah, I'm not familiar with the question.

16:46- It is just asking you a few questions,

16:47like how often did you feel like lonely

16:50or how often do you feel connected to other people

16:52in this last few couple of weeks?

16:54It's similar to the self-report questionnaires

16:58for depression and anxiety, like PHQ-9 and GAT-7.

17:02Of course, as any self-report questionnaires,

17:05that's not necessarily very precise or very well measured.

17:10But still, if you take a big enough population,

17:12you get them through these questionnaires,

17:16you can see a positive dynamic.

17:19- And so you basically,

17:21you put people through questionnaires to see,

17:23like, is this thing, is what we're creating

17:26making people happier?

17:28- Yeah, we measure, so we measure two outcomes.

17:31One short-term, right after the conversation,

17:33we ask people whether this conversation

17:36made them feel better, worse, or same.

17:39This metric right now is at 80%,

17:43so 80% of all our conversations make people feel better.

17:46- But I should have done the questionnaire with you.

17:48You feel a lot worse after we've done this conversation.

17:51That's actually fascinating.

17:54I should probably do that.

17:56- But that's our-- - I should probably do that.

17:57- You should totally start measuring.

17:59- And aim for 80%.

18:01- Aim to outperform your current state-of-the-art AI system

§03Transcript · 18:05–27:19

18:05in these human conversations.

18:09So again, we'll get to your work with Replica,

18:13but let me continue on the line of absurd questions.

18:15So you talked about deep connection with other humans,

18:20deep connection with AI, meaningful connection.

18:23Let me ask about love.

18:24People make fun of me 'cause I talk about love all the time,

18:28but what do you think love is?

18:32Like maybe in the context of a meaningful connection

18:36with somebody else, do you draw a distinction

18:38between love, like friendship, and Facebook friends?

18:43Or is it a gradual-- - The answer is no.

18:48(both laughing)

18:50It's all the same.

18:51- No, like is it just a gradual thing,

18:54or is there something fundamental about us humans

18:56that seek like a really deep connection

18:59with another human being, and what is that?

19:03What is love, Eugenia?

19:07I just enjoy asking you these questions--

19:11- I like that. - And seeing you struggle.

19:13- I know, thanks.

19:15Well, the way I see it, and specifically,

19:20the way it relates to our work

19:21and the way it inspired our work on "Replica,"

19:26I think one of the biggest and the most precious gifts

19:31we can give to each other now in 2020 as humans

19:35is this gift of deep, empathetic understanding,

19:39the feeling of being deeply seen.

19:42- Like what does that mean, that you exist,

19:45like somebody acknowledging that?

19:47- Somebody seeing you for who you actually are,

19:49and that's extremely, extremely rare.

19:52I think that combined with unconditional positive regard,

19:56belief, and trust that you internally are

20:02always inclined for positive growth

20:03and believing in you in this way,

20:05letting you be a separate person at the same time,

20:09and this deep, empathetic understanding,

20:11for me, that's the combination

20:15that really creates something special,

20:18something that people, when they feel it once,

20:21they will always long for it again,

20:23and something that starts huge fundamental changes

20:27in people when we see that someone accepts us so deeply.

20:32We start to accept ourselves,

20:34and the paradox is that's when big changes

20:39start happening, big fundamental changes

20:41in people start happening.

20:42So I think that is the ultimate therapeutic relationship,

20:44that is, and that might be, in some way,

20:47the definition of love.

20:48(laughing)

20:49- So acknowledging that there's a separate person

20:53and accepting you for who you are.

20:55Now, on a slightly, and you mentioned therapeutic,

21:02that sounds like a very healthy view of love,

21:05but is there also, like,

21:07if we look at heartbreak,

21:13and most love songs are probably about heartbreak, right?

21:17Is that, like, the mystery, the tension, the danger,

21:21the fear of loss, you know, all of that,

21:25what people might see in the negative light

21:27as, like, games or whatever,

21:29but just the dance of human interaction,

21:34yeah, fear of loss, and fear of, like,

21:38you said, like, once you feel it once,

21:41you long for it again,

21:42but you also, once you feel it once,

21:45for many people, they've lost it,

21:48so they fear losing it, they feel lost.

21:51So is that part of it?

21:53Like, you're speaking, like, beautifully

21:54about, like, the positive things,

21:56but is it important to be able to be afraid of losing it

22:01from an engineering perspective?

22:03(laughing)

22:06- I mean, it's a huge part of it,

22:07and unfortunately, we all, you know,

22:10face it at some points in our lives.

22:12I mean, I did.

22:14- You wanna go into details?

22:16How'd you get your heart broken?

22:18- Sure.

22:19Well, so mine is pretty straight,

22:21my story's pretty straightforward there.

22:23I did have a friend that was, you know,

22:27that at some point in my 20s

22:30became really, really close to me,

22:32and we became really close friends.

22:34Well, I grew up pretty lonely,

22:36so in many ways, when I'm building, you know,

22:38these AI friends, I'm thinking about myself

22:40when I was 17, writing horrible poetry,

22:42and, you know, in my dial-up modem at home,

22:44and, you know, and that was the feeling

22:48that I grew up with.

22:50I lived alone for a long time when I was a teenager.

22:53- Where did you grow up?

22:54- In Moscow, on the outskirts of Moscow.

22:57So I'd just skateboard during the day

22:59and come back home and, you know,

23:01connect to the internet.

23:03- And write poetry.

23:03- And then write horrible poetry.

23:05- Was it love poems?

23:07- All sorts of poems, obviously love poems.

23:09I mean, what other poetry can you write when you're 17?

23:12- It could be political or something, but yeah.

23:15- But that was, you know, that was kind of my,

23:16yeah, like deeply influenced by Joseph Brodsky

23:20and like all sorts of poets that

23:22every 17-year-old will be looking,

23:26you know, looking at and reading.

23:29But yeah, that was my, these were my teenage years,

23:32and I just never had a person that I thought

23:34would, you know, take me as it is,

23:37would accept me the way I am.

23:40And I just thought, you know, working and just doing my thing

23:43and being angry at the world and being a reporter,

23:45I was an investigative reporter working undercover

23:47and writing about people was my way to connect with,

23:52you know, with others.

23:53I was deeply curious about everyone else.

23:56And I thought that, you know, if I go out there,

23:59if I write their stories, that means I'm more connected.

24:02- This is what this podcast is about, by the way.

24:05I'm desperate, alone, seeking connection.

24:08I'm just kidding, or am I?

24:09I don't know.

24:10So wait, reporter,

24:13how did that make you feel more connected?

24:18I mean, you're still fundamentally pretty alone.

24:22- But you're always with other people, you know,

24:23you're always thinking about what other place

24:26can I infiltrate, what other community can I write about,

24:29what other phenomenon can I explore?

24:32And you're sort of like a trickster, you know,

24:35and a mythological creature

24:38that's just jumping between all sorts of different worlds

24:41and feel sort of okay in all of them.

24:44So that was my dream job, by the way.

24:46That was like totally what I would have been doing

24:49if Russia was a different place.

24:52- And a little bit undercover.

24:54So like you were trying to, like you said,

24:57mythological creature trying to infiltrate.

25:00So try to be a part of the world.

25:01What are we talking about?

25:02What kind of things did you enjoy writing about?

25:05- I'd go work at a strip club or go.

25:07- Awesome, okay.

25:12- Well, I'd go work at a restaurant

25:15or just go write about certain phenomenons

25:19or phenomenons of people in the city.

25:22- And what, sorry to keep interrupting.

25:25I'm the worst conversationalist.

25:29What stage of Russia is this?

25:31What, is this pre-Putin, post-Putin?

25:35What was Russia like?

25:38- Pre-Putin is really long ago.

25:41This is Putin era.

25:43That's beginning of 2000s, 2010, 2007, eight, nine, 10.

25:48- What were strip clubs like in Russia

25:51and restaurants and culture and people's minds

25:56like in that early Russia that you were covering?

25:59- In those early 2000s,

26:01there was still a lot of hope.

26:02There were still tons of hope that,

26:04we're sort of becoming this Westernized society.

26:11The restaurants were opening.

26:13We were really looking at,

26:15we're trying to copy a lot of things from the US,

26:21from Europe, bringing all these things in,

26:24very enthusiastic about that.

26:26So there was a lot of stuff going on.

26:27There was a lot of hope and dream

26:29for this new Moscow that would be similar to,

26:34I guess, New York.

26:34I mean, just to give you an idea,

26:36in year 2000 was the year when

26:40we had two movie theaters in Moscow

26:43and there was this one first coffee house that opened

26:46and it was like really big deal.

26:48By 2010, there were all sorts of things everywhere.

26:51- Almost like a Starbucks type of coffee house

26:54or like you mean?

26:55- Oh yeah, like a Starbucks.

26:56I mean, I remember we were reporting on,

26:59we were writing about the opening of Starbucks,

27:01I think in 2007.

27:02That was one of the biggest things that happened

27:04in Moscow back in the time.

27:06That was worthy of a magazine cover

27:09and that was definitely the biggest talk of the town.

27:13- Yeah, when was McDonald's?

27:15'Cause I was still in Russia when McDonald's opened.

27:17That was in the '90s.

27:19I mean, yeah.

27:19- Oh yeah, I remember that very well.

§04Transcript · 27:21–35:40

27:21- Yeah.

27:22- Those were long, long lines.

27:24I think it was 1993 or '94, I don't remember.

27:28- Did you go to McDonald's at that time?

27:30Did you do the--

27:31- I mean, that was a luxurious outing.

27:33That was definitely not something you do every day.

27:35And also the line was at least three hours.

27:37So if you're going to McDonald's, that is not fast food.

27:40That is like at least three hours in line.

27:42And then no one is trying to eat fast after that.

27:44Everyone is like trying to enjoy as much as possible.

27:47- What's your memory of that?

27:48- Oh, it was insane.

27:52- Positive?

27:53- Extremely positive.

27:54It's a small strawberry milkshake and a hamburger

27:57and small fries and my mom's there.

27:59And sometimes I'll just, 'cause I was really little,

28:01they'll just let me run up the cashier and cut the line,

28:06which is, you cannot really do that in Russia.

28:09- So for a lot of people,

28:12a lot of those experiences might seem not very fulfilling.

28:17It's on the verge of poverty, I suppose.

28:22But do you remember all that time fondly?

28:25Like, 'cause I do, like the first time I drank, you know,

28:30Coke, you know, all that stuff, right?

28:33And just, yeah, the connection

28:38with other human beings in Russia,

28:40I remember really positively.

28:43Like, how do you remember, well, the '90s

28:46and then the Russia you were covering,

28:48just the human connections you had with people

28:51and the experiences?

28:54- Well, my parents were both physicists.

28:57My grandparents were both, well, my grandfather

29:01was a nuclear physicist, a professor at the university.

29:06My dad worked at Chernobyl when I was born in Chernobyl,

29:10analyzing kind of everything after the explosion.

29:15And then I remember that,

29:17and so they were making sort of enough money

29:19in the Soviet Union,

29:20so they were not, you know, extremely poor or anything.

29:23It was pretty prestigious to be a professor,

29:26the dean in the university.

29:28And then I remember my grandfather

29:29started making $100 a month after, you know, in the '90s.

29:34So then I remember we started,

29:36our main line of work would be to go

29:38to our little tiny country house,

29:41get a lot of apples there from apple trees,

29:45bring them back to the city and sell them in the street.

29:50So me and my nuclear physicist grandfather

29:53were just standing there and he'd selling those apples

29:56the whole day, 'cause that would make you more money

29:58than, you know, working at the university.

30:01And then he'll just tell me, try to teach me, you know,

30:05something about planets and whatever,

30:08the particles and stuff.

30:09And, you know, I'm not smart at all,

30:12so I could never understand anything,

30:13but I was interested as a, you know,

30:15journalist kind of type interested.

30:17But that was my memory.

30:18And, you know, I'm happy that I wasn't,

30:20I somehow got spared, that I was probably too young

30:25to remember any of the traumatic stuff.

30:27So the only thing I really remember,

30:29I had this bootleg, that was very traumatic,

30:31had this bootleg Nintendo,

30:33which was called Dandy in Russia.

30:35So in 1993, there was nothing to eat.

30:37Like, even if you had any money, you would go to the store

30:39and there was no food.

30:40I don't know if you remember that.

30:42And our friend had a restaurant, like a government,

30:47half government owned something restaurant.

30:49So they always had supplies.

30:51So he exchanged a big bag of wheat for this Nintendo,

30:56the bootleg Nintendo.

30:57And that I remember very fondly,

31:00'cause I think I was nine or something like that,

31:04and, or seven. - Why is that traumatic?

31:06- Well, 'cause we just got it and I was playing it

31:08and there was this, you know, Dandy TV show.

31:11- Yeah.

31:12So traumatic in a positive sense, you mean,

31:14like a definitive?

31:16- Well, they took it away

31:17and gave me a bag of wheat instead.

31:19And I cried like my eyes out for days and days and days.

31:23- Oh no.

31:24- And then, you know, as a,

31:26and my dad said, "We're gonna like exchange it back

31:28"in a little bit, so you keep the little gun."

31:31You know, the one that you shoot the ducks with?

31:32So I'm like, "Okay, I'm keeping the gun.

31:34"So sometime it's gonna come back."

31:35But then they exchanged the gun as well

31:37for some sugar or something.

31:39(laughing)

31:40I was so pissed.

31:41I was like, I didn't wanna eat for days after that.

31:43I'm like, "I don't want your food.

31:44"I'm keeping my Nintendo back."

31:46(laughing)

31:47So that was extremely traumatic.

31:49But, you know, I was happy

31:51that that was my only traumatic experience.

31:53You know, my dad had to actually go to Chernobyl

31:55with a bunch of 20-year-olds.

31:57He was 20 when he went to Chernobyl.

32:00And that was right after the explosion.

32:01No one knew anything.

32:03The whole crew he went with, all of them are dead now.

32:05I think there was this one guy still,

32:08that was still alive for this last few years.

32:11I think he died a few years ago now.

32:13My dad somehow luckily got back earlier than everyone else.

32:17But just the fact that that was the,

32:20and I was always like, "Well, how did they send you?"

32:22I was only, I was just born.

32:23You know, you had a newborn.

32:25Talk about paternity leave.

32:26They were like, "But that's who they took

32:28"'cause they didn't know whether you would be able

32:29"to have kids when you come back."

32:31So they took the ones with kids.

32:33So he came with some guys, went to,

32:36and I'm just thinking of me when I was 20.

32:38I was so sheltered from any problems whatsoever in life.

32:42And my dad, his 21st birthday at the reactor,

32:47you work three hours a day, you sleep the rest.

32:52And yeah, so I played with a lot of toys from Chernobyl.

32:55- What are your memories of Chernobyl in general?

32:59Like the bigger context, you know,

33:02because of that HBO show,

33:04the world's attention turned to it once again.

33:08Like what are your thoughts about Chernobyl?

33:10Did Russia screw that one up?

33:12Like, you know, there's probably a lot of lessons

33:16about our modern times with data about coronavirus

33:19and all that kind of stuff.

33:20It seems like there's a lot of misinformation.

33:22There's a lot of people kind of trying to hide

33:27whether they screwed something up or not.

33:30As it's very understandable, it's very human,

33:33very wrong probably.

33:34But obviously Russia was probably trying to hide

33:37that they screwed things up.

33:41Like what are your thoughts about that time,

33:44personal and general?

33:46- I mean, I was born when the explosion happened.

33:50So actually a few months after.

33:52So of course I don't remember anything apart from the fact

33:55that my dad would bring me tiny toys,

33:57plastic things that would just go crazy,

34:01haywire when you put the Gager thing to it.

34:06My mom was like just nuclear about that.

34:10She was like, "What are you bringing?

34:11"You should not do that."

34:13- She was nuclear, very nice.

34:14- Absolutely. - Well done.

34:15- I'm sorry for that.

34:17Well, but yeah, but the TV show was just phenomenal.

34:21- HBO one?

34:22- Yeah, it's definitely, first of all,

34:25it's incredible how that was made,

34:27not by the Russians, but someone else,

34:29but capturing so well everything about our country.

34:34It felt a lot more genuine

34:38than most of the movies and TV shows

34:40that are made now in Russia, just so much more genuine.

34:43And most of my friends in Russia

34:44were just in complete awe about the show.

34:47But I think the-- - How good of a job they did.

34:49- My God, phenomenal.

34:50- But also-- - The apartments,

34:51there's something, yeah.

34:52- The set design. - Yes.

34:53- I mean, Russians can't do that.

34:56But you see everything and it's like,

34:57well, that's exactly how it was.

35:00- It's so, I don't know, that show,

35:02I don't know what to think about that

35:05'cause it's British accents, British actors.

35:08Of a person, I forgot who created the show,

35:12but I remember reading about him and he's not,

35:15he doesn't even feel like,

35:17like there's no Russia in his history.

35:19- No, he did like "Superbad" or some other show,

35:21or like, I don't know.

35:23- Yeah, like, exactly.

35:24- Whatever that thing about the bachelor party in Vegas,

35:27number four and five or something

35:28were the ones that he worked on.

35:29- Yeah, but so he, it made me feel really sad

35:33for some reason that if a person,

35:37obviously a genius could go in and just study

35:40and just be extreme attention to detail,

§05Transcript · 35:45–44:32

35:45they can do a good job.

35:46It made me think like,

35:48why don't other people do a good job with this?

35:52Like about Russia, like there's so little about Russia.

35:56There's so few good films about

35:58the Russian side of World War II.

36:02I mean, there's so much interesting evil

36:07and not, and beautiful moments in the history

36:10of the 20th century in Russia

36:12that it feels like there's not many good films on

36:16from the Russians.

36:16You would expect something from the Russians.

36:19- Well, they keep making these propaganda movies now.

36:22- Oh no.

36:22- Unfortunately, but yeah, no,

36:24"Chernobyl" was such a perfect TV show.

36:26I think capturing really well,

36:28it's not about like even the set design,

36:29which was phenomenal,

36:30but just capturing all the problems that exist now

36:34with the country and focusing on the right things.

36:37Like if you build the whole country on a lie,

36:40that's what's gonna happen.

36:41And that's just this very simple kind of thing.

36:45- Yeah, and did you have your dad talked about it to you?

36:51Like his thoughts on the experience?

36:54- He never talks.

36:57He's this kind of Russian man that just,

36:59my husband who's American,

37:00and he asked him a few times,

37:03Igor, how did you, but why did you say yes?

37:06Or like, why did you decide to go?

37:08You could have said no, not go to "Chernobyl."

37:10Why would like a person,

37:11that's what you do.

37:14You cannot say no.

37:16- Yeah, yeah.

37:17- It's just, it's like a Russian way.

37:21- It's the Russian way.

37:22- Men don't talk that much.

37:23- No.

37:24- There are downsides and upsides for that.

37:25- Yeah, that's the truth.

37:29Okay, so back to post-Putin Russia.

37:33Or maybe we skipped a few steps along the way,

37:37but you were trying to be a journalist in that time.

37:42What was Russia like at that time?

37:46Post, you said 2007 Starbucks type of thing.

37:51What else was Russia like then?

37:54- I think there was just hope.

37:56There was this big hope that we're gonna be friends

38:00with the United States,

38:01and we're gonna be friends with Europe,

38:04and we're just gonna be also a country like those

38:07with bike lanes and parks,

38:11and everything's gonna be urbanized.

38:13And again, we're talking about '90s

38:14where people would be shot in the street.

38:16And that was, I sort of have a fond memory

38:19of going into a movie theater

38:20and coming out of it after the movie,

38:22and the guy that I saw on the stairs was like,

38:24neither shot, which was, again,

38:27it was like a thing in the '90s.

38:29That would be happening.

38:30People were getting shot here and there.

38:33- Just violence.

38:34- Tons of violence, tons of just basically mafia mobs

38:39in the streets.

38:39And then the 2000s were like,

38:41things just got cleaned up, oil went up,

38:45and the country started getting a little bit richer.

38:48The '90s were so grim,

38:51mostly because the economy was in shambles

38:53and oil prices were not high,

38:54so the country didn't have anything.

38:56We defaulted in 1998,

38:58and the money kept jumping back and forth.

39:01First there were millions of rubbles,

39:03then it got to thousands,

39:06then it was one rubble was something,

39:08then again to millions.

39:10It was like crazy town.

39:11- That was crazy.

39:12- And then the 2000s were just these years

39:15of stability in a way,

39:17and the country getting a little bit richer

39:20because of, again, oil and gas.

39:22And we started to look at,

39:25specifically in Moscow and St. Petersburg,

39:27to look at other cities in Europe and New York and US,

39:32and trying to do the same

39:34in our small kind of cities, towns there.

39:37- What were your thoughts of Putin at the time?

39:41- Well, in the beginning he was really positive.

39:43Everyone was very positive about Putin.

39:45He was young, he was very energetic.

39:49He also immediately-- - Hansel?

39:51The shirtless?

39:52- Well, somewhat compared to,

39:54well, that was not, like, way before the shirtless era.

39:56- The shirtless era.

39:59Okay, so he didn't start off shirtless.

40:00When did the shirtless era,

40:01it's like the propaganda of riding a horse, fishing.

40:04- 2010, 11, 12.

40:06- Yeah.

40:07That's my favorite.

40:08You know, like people talk about the favorite Beatles,

40:11like the, I don't know.

40:13That's my favorite Putin, is the shirtless Putin.

40:15- No, I remember very, very clearly 1996

40:18where Americans really helped Russia with elections

40:21and Yeltsin got reelected.

40:24Thankfully so, because there was a huge threat

40:27that actually the communists will get back to power.

40:30They were a lot more popular.

40:32And then a lot of American experts, political experts,

40:36and campaign experts descended on Moscow

40:40and helped Yeltsin actually get the presidency,

40:43the second term of the presidency.

40:45But Yeltsin was not feeling great, you know,

40:48by the end of his second term.

40:51He was, you know, alcoholic, he was really old.

40:55He was falling off, you know,

40:57the stages where he was talking.

40:59So people were looking for fresh,

41:02I think for a fresh face,

41:03for someone who's gonna continue Yeltsin's work,

41:07but who's gonna be a lot more energetic

41:09and a lot more active, young, efficient maybe.

41:14So that's what we all saw in Putin back in the day.

41:17I'd say that everyone,

41:19absolutely everyone in Russia in early 2000s

41:22who was not a communist would be,

41:24yeah, Putin's great.

41:25We have a lot of hopes for him.

41:26- What are your thoughts,

41:28and I promise we'll get back to,

41:31first of all, your love story,

41:34and second of all, AI,

41:36but what are your thoughts about communism?

41:39The 20th century, I apologize,

41:42I'm reading the "Rise and Fall of the Third Reich."

41:46- Oh my God.

41:48- So I'm like really steeped into like World War II

41:52and Stalin and Hitler and just these dramatic personalities

41:58that brought so much evil to the world.

42:00But it's also interesting to politically think

42:04about these different systems and what they've led to.

42:08And Russia is one of the sort of beacons of communism

42:13in the 20th century.

42:16What are your thoughts about communism?

42:17Having experienced it as a political system?

42:20- I mean, I have only experienced it a little bit,

42:22but mostly through stories and through seeing my parents,

42:26my grandparents who lived through that.

42:28It was horrible.

42:29It was just plain horrible.

42:31It was just awful.

42:33- You think there's something,

42:34I mean, it sounds nice on paper.

42:37- Maybe.

42:42- So like the drawbacks of capitalism is that

42:46eventually it's the point of like a slippery slope.

42:50Eventually it creates,

42:52the rich get richer.

42:56It creates a disparity, like inequality of wealth inequality.

43:01I guess it's hypothetical at this point,

43:06but eventually capitalism leads to humongous inequality.

43:10And that's, some people argue that

43:12that's a source of unhappiness.

43:15Is it's not like absolute wealth of people.

43:17It's the fact that there's a lot of people

43:19much richer than you.

43:21There's a feeling of like,

43:23that's where unhappiness can come from.

43:25So the idea of communism, or at least sort of Marxism

43:29is not allowing that kind of slippery slope.

43:34But then you see the actual implementations of it

43:37and stuff seems to go wrong very badly.

43:40What do you think that is?

43:43Why does it go wrong?

43:45What is it about human nature?

43:47If we look at Chernobyl,

43:49those kinds of bureaucracies that were constructed,

43:53is there something like,

43:55do you think about this much of like why it goes wrong?

44:00- Well, there's no one was really like,

44:03it's not that everyone was equal.

44:05Obviously the government and everyone close to that

44:10were the bosses.

44:12So it's not like fully, I guess.

44:14- There's already inequality.

44:15- This dream of equal life.

44:17So then I guess the situation that we had,

44:22the Russia had in the Soviet Union,

44:25it was more, it's a bunch of really poor people

44:27without any way to make any significant fortune

44:32or build anything, living constant,

§06Transcript · 44:35–53:43

44:35under constant surveillance, surveillance from other people.

44:38Like you can't even do anything

44:42that's not fully approved by the dictatorship basically.

44:46Otherwise your neighbor will write a letter

44:50and you'll go to jail.

44:51Absolute absence of actual law.

44:54- Yeah.

44:55- It's a constant state of fear.

44:56You didn't own anything.

45:00You couldn't go travel.

45:03You couldn't read anything Western

45:05or you couldn't make a career really,

45:08unless you're working in the military complex.

45:12Which is why most of the scientists were so well-regarded.

45:15I come from, both my dad and my mom

45:17come from families of scientists

45:19and they were really well-regarded as you know, obviously.

45:23- 'Cause the state wanted, I mean,

45:25'cause there's a lot of value to them being well-regarded.

45:29- Because they were developing things

45:30that could be used in the military.

45:33So that was very important.

45:35That was the main investment.

45:36But it was miserable.

45:38It was miserable.

45:40That's why a lot of Russians now live

45:41in the state of constant PTSD.

45:43That's why we want to buy, buy, buy, buy, buy.

45:46Definitely, as soon as we have the opportunity,

45:50we just got to it finally that we can own things.

45:53I remember the time that we got our first yogurts

45:56and that was the biggest deal in the world.

45:58It was already in the '90s by the way.

46:00- What was your favorite food

46:04where it was like, "Whoa, this is possible."

46:07- Oh, fruit, because we only had apples, bananas

46:11and whatever, watermelons,

46:14whatever people would grow in the Soviet Union.

46:18So there were no pineapples or papaya or mango.

46:22Like you've never seen those fruit things.

46:24Like those were so ridiculously good.

46:27And obviously you could not get any like strawberries

46:29in winter or anything that's not seasonal.

46:32So that was a really big deal,

46:34seeing all these fruit things.

46:36- Yeah, me too, actually.

46:37I don't know.

46:38I think I have a,

46:39like I don't think I have too many demons

46:43or like addictions or so on,

46:45but I think I've developed an unhealthy relationship

46:47with fruit that I still struggle with.

46:50- Oh, you can get any type of fruit, right?

46:51You can get like, also these weird fruit,

46:54fruits like dragon fruit or something.

46:57- All kinds of like different types of peaches.

47:00Like cherries were killer for me.

47:02I know you say like we had bananas and so on,

47:04but I don't remember having the kind of banana.

47:07Like when I first came to this country,

47:10the amount of banana,

47:11I like literally got fat on bananas.

47:13(Bridget laughing)

47:15Like the amount.

47:16- Oh yeah, for sure.

47:17- They're delicious.

47:18And like cherries, the kind,

47:19like just the quality of the food.

47:22I was like, this is capitalism.

47:24This is delicious.

47:27Yeah, yeah.

47:29Yeah, it's funny.

47:29It's funny.

47:32Yeah, like it's funny to read.

47:34I don't know what to think of it.

47:38It's funny to think how an idea

47:42that's just written on paper,

47:46when carried out amongst millions of people,

47:48how that gets actually,

47:50when it becomes reality,

47:52what it actually looks like.

47:53Sorry, but I've been studying Hitler a lot recently

48:00and going through Mein Kampf.

48:03He pretty much wrote out in Mein Kampf

48:05everything he was gonna do.

48:07Unfortunately, most leaders,

48:09including Stalin, didn't read it.

48:11But it's kind of terrifying and I don't know.

48:15And amazing in some sense

48:17that you can have some words on paper

48:20and they can be brought to life

48:21and they can either inspire the world

48:24or they can destroy the world.

48:26And yeah, there's a lot of lessons to study in history

48:31that I think people don't study enough now.

48:33One of the things I'm hoping with,

48:37I've been practicing Russian a little bit.

48:40I'm hoping to sort of find,

48:43rediscover the beauty and the terror of Russian history

48:48through this stupid podcast by talking to a few people.

48:55So anyway, I just feel like so much was forgotten.

48:58So much was forgotten.

49:00I'll probably, I'm gonna try to convince myself

49:02that you're a super busy and super important person.

49:05Well, I'm gonna try to befriend you

49:08to try to become a better Russian

49:12'cause I feel like I'm a shitty Russian.

49:14- Not that busy.

49:15So I can totally be your Russian Sherpa.

49:17- Yeah, but love.

49:24You're talking about your early days

49:26of being a little bit alone

49:28and finding a connection with the world

49:31through being a journalist.

49:33Where did love come into that?

49:35- I guess finding for the first time some friends.

49:40It's very simple story.

49:42Some friends that all of a sudden we,

49:44I guess we were at the same place with our lives.

49:51We're 25, 26, I guess.

49:54And somehow remember, and we just got really close

49:59and somehow remember this one day where,

50:02it's one day in summer that we just stayed out,

50:06outdoor the whole night and just talked.

50:08And for some unknown reason,

50:09it just felt for the first time that someone could,

50:12see me for who I am.

50:14And it just felt extremely, like extremely good.

50:18And we fell asleep outside and just talking

50:21and it was raining, it was beautiful, sunrise.

50:25It's really cheesy, but at the same time,

50:28we just became friends in a way that I've never been friends

50:31with anyone else before.

50:33And I do remember that before and after

50:35that you sort of have this unconditional family sort of,

50:39and it gives you tons of power.

50:43It just basically gives you this tremendous power

50:46to do things in your life and to change positively.

50:51- You mean like-- - On many different levels.

50:53- Power because you could be yourself.

50:56- At least you know that somewhere you can be just yourself.

51:01Like you don't need to pretend,

51:02you don't need to be great at work or tell some story

51:07or sell yourself in somewhere or another.

51:10And so we became this really close friends.

51:12And in a way I started a company 'cause he had a startup

51:17and I felt like I kind of want to start up too.

51:20And it felt really cool.

51:21I don't know what I would really do,

51:24but I felt like I would kind of need to start up.

51:26- Okay, so that pulled you in to the startup world.

51:31- Yeah, and then this closest friend of mine died.

51:37We actually moved here to San Francisco together

51:40and then we went back for a visa to Moscow

51:43and we lived together, we're roommates.

51:45And we came back and he got hit by a car

51:49right in front of Kremlin, next to the river

51:52and died the same day in the hospital.

51:55- This is Roman?

51:56- Mm-hmm.

51:57- This is Roman.

51:58And you've moved to America at that point?

52:04- At that point I was living--

52:04- What about him, what about Roman?

52:06- Him too, he actually moved first.

52:07So I was always sort of trying to do what he was doing.

52:10So I didn't like that he was already here

52:12and I was still in Moscow

52:14and we weren't hanging out together all the time.

52:16- Was he in San Francisco?

52:18- Yeah, we were roommates.

52:20- So he just visited Moscow for a little bit?

52:23- We went back for our visas.

52:25We had to get a stamp and our passport for our work visas

52:29and the embassy was taking a little longer

52:31so we stayed there for a couple weeks.

52:33- What happened?

52:35So how did he die?

52:39- He was crossing the street

52:42and the car was going really fast

52:43and way over the speed limit

52:45and just didn't stop on the pedestrian cross on the zebra

52:49and just ran over him.

52:52- When was this?

52:54- It was in 2015 on 28th of November

52:57so it was pretty long ago now.

52:59But at the time I was 29

53:01so for me it was the first kind of meaningful death

53:06in my life.

53:07I had both sets of grandparents at the time.

53:12I didn't see anyone so close die

53:14and death sort of existed but as a concept

53:18but definitely not as something that would be

53:20happening to us anytime soon.

53:23And specifically our friends

53:25'cause we were still in our 20s or early 30s

53:28and it still felt like the whole life is,

53:32you could still dream about ridiculous things.

53:36So it was just really, really abrupt I'd say.

53:43- What did it feel like to lose him?

§07Transcript · 53:48–1:03:47

53:48Like that feeling of loss.

53:49You talked about the feeling of love, having power.

53:52What is the feeling of loss feel like?

53:56- Well in Buddhism there's this concept of samaya

53:59where something really huge happens

54:04and then you can see very clearly.

54:07I think that was it.

54:09Basically something changed me so much

54:13in such a short period of time

54:14that I could just see really clearly

54:18what mattered or what not.

54:20Well I definitely saw that whatever I was doing at work

54:23didn't matter at all and some of the things.

54:26And it was just this big realization,

54:30this very, very clear vision of what life's about.

54:33- You still miss him today?

54:36- Yeah, for sure.

54:39For sure.

54:41It was just this constant,

54:43I think he was really important for me and for our friends

54:48for many different reasons.

54:50And I think one of them,

54:52being that we didn't just say goodbye to him

54:54but we sort of said goodbye to our youth in a way.

54:58It was like the end of an era

55:00and on so many different levels.

55:02The end of Moscow as we knew it,

55:04the end of us living through our 20s

55:08and kind of dreaming about the future.

55:11- Do you remember last several conversations?

55:15Is there moments with him that stick out

55:17that will kind of haunt you?

55:19And just when you think about him?

55:22- Yeah, well his last year here in San Francisco

55:26he was pretty depressed as his startup

55:29was not going really anywhere.

55:31And he wanted to do something else.

55:32He wanted to build,

55:34he played with a bunch of ideas

55:38but the last one he had was around

55:41building a startup around death.

55:44So having, he applied to Y Combinator

55:48with a video that I had on my computer.

55:51And it was all about disrupting death,

55:55thinking about new symmetries, more biologically.

55:59Like things that could be better biologically for humans.

56:05And at the same time having those digital avatars,

56:09these kind of AI avatars that would store all the memory

56:14about a person that he could interact with.

56:15- What year was this?

56:17- 2015.

56:18Well right before his death.

56:20So it was like a couple months before that

56:21he recorded that video.

56:23And so I found it on my computer

56:25when it was in our living room.

56:28He never got in but he was thinking about it a lot somehow.

56:33- Does it have the digital avatar idea?

56:35- Yeah.

56:36- That's so interesting.

56:37- Well he just says, well that's in his,

56:39yeah, Depeche has this idea and he talks about

56:42like I want to rethink how people grieve

56:44and how people talk about death.

56:46- Why was he interested in this?

56:47- Maybe someone who's depressed

56:52is like naturally inclined thinking about that.

56:55But I just felt, you know, this year in San Francisco

56:57we just had so much,

56:58I was going through a hard time,

57:01he was going through a hard time,

57:02and we were definitely, I was trying to make him

57:05just happy somehow, just make him feel better.

57:07And it felt like, you know, this,

57:09I don't know, I just felt like I was taking care

57:13of him a lot.

57:14And he almost started to feel better

57:16and then that happened.

57:18And I don't know, I just felt lonely again, I guess.

57:23And that was, you know, coming back to San Francisco

57:25in December, I helped organize the funeral,

57:29helped his parents.

57:31And then I came back here and it was a really

57:33lonely apartment, a bunch of his clothes everywhere,

57:35and Christmas time.

57:38And I remember I had a board meeting with my investors

57:41and I just couldn't talk about like,

57:43had to pretend everything's okay

57:44and, you know, just working on this company.

57:47Yeah, it was definitely a very, very tough, tough time.

57:54- Do you think about your own mortality?

58:00You said, you know, we're young,

58:03the possibility of doing all kinds of crazy things

58:07is still out there, it's still before us,

58:10but it can end any moment.

58:12Do you think about your own ending at any moment?

58:17- Unfortunately, I think about it way too much.

58:21It's somehow after Roman, like every year after that,

58:26I started losing people that I really love.

58:28I lost my grandfather the next year.

58:30You know, the person who would explain to me,

58:35you know, what the universe is made of.

58:37- While you're selling apples?

58:39- While selling apples, and then I lost

58:41another close friend of mine.

58:42And it just made me very scared.

58:46I have tons of fear about death.

58:48That's what makes me not fall asleep oftentimes

58:51and just go in loops.

58:52And then as my therapist, you know, recommended me,

58:57I open up some nice calming images

59:02with a voiceover and it calms me down.

59:05- Oh, for sleep?

59:06- Yeah, I'm really scared of death.

59:08This is a big, I definitely have tons of,

59:11I guess some pretty big trauma about it

59:14and I'm still working through.

59:17- There's a philosopher, Ernest Becker,

59:20who wrote a book, "The Nile of Death."

59:23I'm not sure if you're familiar with any of those books.

59:26There's in psychology a whole field

59:29called terror management theory.

59:32Sheldon, who's just done the podcast, he wrote the book.

59:36He was the, we talked for four hours about death.

59:40Fear of death.

59:43But his whole idea is that, Ernest Becker,

59:47I think I find this idea really compelling

59:50is that everything human beings have created,

59:55like our whole motivation in life

59:58is to create, like escape death.

60:02It's to try to construct an illusion

60:06of that we're somehow immortal.

60:12So everything around us, this room,

60:16your startup, your dreams, all, everything you do

60:21is a kind of creation of a brain,

60:26unlike any other mammal or species,

60:29is able to be cognizant of the fact that it ends for us.

60:33I think, so there's the question of the meaning of life

60:39that you look at what drives us, humans.

60:44And when I read Ernest Becker

60:45that I highly recommend people read,

60:48is the first time I, it felt like this is the right thing

60:53at the core.

60:54Sheldon's work is called Warm at the Core.

60:57So he's saying, I think it's William James,

61:01he's quoting or whoever, is like the thing,

61:06what is at the core of it all?

61:07Sure, there's like love, you know,

61:10Jesus might talk about like love

61:12is at the core of everything.

61:13I don't, you know, that's the open question.

61:15What's at the, you know, it's turtles, turtles,

61:18but it can't be turtles all the way down.

61:19What's at the bottom?

61:22And Ernest Becker says the fear of death.

61:24And the way, in fact,

61:28'cause you said therapist and calming images,

61:32his whole idea is, you know,

61:34we wanna bring that fear of death as close as possible

61:38to the surface because it's, and like meditate on that

61:43and use the clarity of vision that provides

61:47to live a more fulfilling life,

61:51to live a more honest life,

61:54to discover, you know,

61:58there's something about, you know,

61:59being cognizant of the finiteness of it all

62:02that might result in the most fulfilling life.

62:07So that's the dual of what you're saying

62:10'cause you kind of said it's like,

62:11I unfortunately think about it too much.

62:15It's a question whether it's good to think about it.

62:17'Cause I've, again, I talk way too much about love

62:21and probably death.

62:22And when I ask people or friends,

62:26which is why I probably don't have many friends,

62:29are you afraid of death?

62:30I think most people say they're not.

62:33They're not, what they say they're afraid,

62:38you know, it's kind of almost like they see death

62:42as this kind of like a paper deadline or something

62:45and they're afraid not to finish the paper before the paper,

62:48like I'm afraid not to finish the goals I have,

62:53but it feels like they're not actually realizing

62:57that this thing ends, like really realizing,

63:01like really thinking, as Nietzsche and all these philosophers

63:04like thinking deeply about it.

63:07Like the very thing that, you know,

63:11like when you think deeply about something,

63:15you can realize that you haven't actually thought about it.

63:20Yeah, and when I think about death,

63:24it's like, it can be, it's terrifying.

63:28It feels like stepping outside into the cold

63:32or it's freezing and then I have to like hurry back inside

63:35or it's warm.

63:36(laughs)

63:38But like, I think there's something valuable

63:40about stepping out there into the freezing cold.

63:43- Most definitely.

63:46When I talk to my mentor about it,

63:47he always tells me, "Well, what dies?

§08Transcript · 1:03:52–1:13:17

63:52"There's nothing there that can die."

63:54But I guess that requires-- - What do you mean?

63:59- Well, in Buddhism, one of the concepts

64:01that are really hard to grasp

64:03and that people spend all their lives meditating on

64:06would be anatta, which is the concept of non-self.

64:11And kind of thinking that, you know,

64:12if you're not your thoughts,

64:13which you're obviously not your thoughts

64:15'cause you can observe them and not your emotions

64:17and not your body, then what is this?

64:20And if you go really far, then finally you see that

64:23there's not self, there's this concept of not self.

64:28So once you get there, how can that actually die?

64:32What is dying? (laughs)

64:34- Right, you're just a bunch of molecules, stardust.

64:37- But that is very advanced spiritual work for me.

64:43- Does that help you sleep? - I'm definitely just,

64:46definitely not.

64:47Oh my God, no, I have, I think it's very, very useful.

64:50It's just the fact that maybe being so afraid is not useful.

64:54And mine is more, I'm just terrified.

64:56Like, it really makes me-- - On a personal level.

64:59- On a personal level.

65:01I'm terrified.

65:02- How do you overcome that?

65:08- I don't.

65:09I'm still trying to.

65:11- Have pleasant images?

65:14- Well, pleasant images get me to sleep.

65:18And then during the day, I can distract myself

65:20with other things, like talking to you.

65:22- I'm glad we're both doing the same exact thing.

65:26Okay, good. (laughs)

65:28(laughs)

65:30Is there other, like, is there moments

65:35since you've lost Roman that you had moments of bliss

65:40and that you've forgotten,

65:44that you have achieved that Buddhist level of,

65:48what can possibly die?

65:52I'm part, like, losing yourself in the moment,

65:55in the ticking time of, like, this universe,

66:00and you're just part of it for a brief moment

66:04and just enjoying it.

66:05- Well, that goes hand in hand.

66:08I remember, I think a day or two after he died,

66:11we went to finally get his passport out of the embassy,

66:14and we're driving around Moscow, and it was December,

66:18which is usually, there's never sun in Moscow in December.

66:22And somehow, it was an extremely sunny day,

66:25and we were driving with a close friend.

66:28And I remember feeling, for the first time,

66:32maybe this just moment of incredible clarity

66:35and somehow happiness, not, like, happy happiness,

66:40but happiness, and just feeling that, you know,

66:43I know what the universe is sort of about,

66:48whether it's good or bad.

66:49And it wasn't a sad feeling.

66:50It was probably the most beautiful feeling

66:52that you can ever achieve.

66:54And you can only get it when something,

66:58oftentimes, when something traumatic like that happens.

67:03But also, if you just, you really spend a lot of time

67:05meditating and looking at the nature,

67:07doing something that really gets you there.

67:09But once you're there, I think when you summit a mountain,

67:13a really hard mountain, you inevitably get there.

67:16That's just a way to get to the state.

67:18But once you're in this state,

67:20you can do really big things, I think.

67:24- Yeah.

67:25Sucks that it doesn't last forever.

67:28So Bukowski talked about, like, love is a fog.

67:31It's when you wake up in the morning, it's there,

67:36but it eventually dissipates.

67:39It's really sad.

67:40Nothing lasts forever.

67:41But I definitely like doing this pushup and running thing.

67:46There's moments, I had a couple moments.

67:49Like, I'm not a crier, I don't cry.

67:52But there's moments where I was, like,

67:54facedown on the carpet, like, with tears in my eyes.

67:59It's interesting.

68:00And then that complete, like, there's a lot of demons.

68:05I've got demons, had to face them.

68:07Funny how running makes you face your demons.

68:09But at the same time, the flip side of that,

68:12there's a few moments where I was in bliss.

68:15And all of it alone, which is funny.

68:19- That's beautiful.

68:20I like that.

68:23But definitely pushing yourself physically,

68:25one of it, for sure.

68:26- Yeah, it's, yeah.

68:28Like you said, I mean, you were speaking

68:30as a metaphor of Mount Everest,

68:32but it also works, like, literally.

68:35I think physical endeavor somehow.

68:37Yeah, there's something.

68:40I mean, we're monkeys, apes, whatever.

68:44Physical, there's a physical thing to it.

68:46But there's something to this,

68:48pushing yourself physically, but alone.

68:52That happens when you're doing, like, things like you do,

68:54or strenuous, like, workouts,

68:56or, you know, rowing across the Atlantic, or, like, marathons.

69:01That's why I love watching marathons.

69:03And, you know, it's so boring.

69:06But you can see them getting there.

69:09- So the other thing, I don't know if you know,

69:11there's a guy named David Goggins.

69:13He's a, he basically,

69:17so he's been either emailing on the phone with me

69:19every day through this.

69:20I haven't been exactly alone,

69:22but he's kind of,

69:24he's the devil on the devil's shoulder.

69:28So he's, like, the worst possible human being

69:32in terms of giving you advice.

69:35Like, he has, through everything I've been doing,

69:38he's been doubling everything I do.

69:40So he's insane.

69:43He's this Navy SEAL person.

69:45He's wrote this book, "Can't Hurt Me."

69:48He's basically one of the toughest human beings on earth.

69:50He ran all these crazy ultra marathons in the desert.

69:54He set the world record in the number of pull-ups.

69:56He just does everything where it's like,

69:59he, like, how can I suffer today?

70:03He figures that out and does it.

70:05Yeah, that, whatever that is,

70:08that process of self-discovery is really important.

70:11I actually had to turn myself off from the internet, mostly,

70:15'cause I started this workout thing,

70:16like a happy go-getter,

70:18with my headband and, like,

70:21just, like, 'cause a lot of people were inspired

70:25and they're like, "Yeah, we're gonna exercise with you."

70:28And I was, "Yeah, great."

70:30But then, like, I realized that this journey

70:34can't be done together with others.

70:38This has to be done alone.

70:41- So, out of the moments of love,

70:44out of the moments of loss,

70:47can we talk about your journey of finding, I think,

70:51an incredible idea, an incredible company,

70:54and incredible system in Replika?

70:58How did that come to be?

71:00- So, yeah, so I was a journalist,

71:03and then I went to business school for a couple of years

71:05to just see if I can maybe switch gears

71:10and do something else at 23.

71:12And then I came back and started working

71:14for a businessman in Russia

71:15who built the first 4G network in our country,

71:20and was very visionary,

71:23and asked me whether I wanna do fun stuff together.

71:26And we worked on a bank.

71:29The idea was to build a bank on top of a telco.

71:33So that was 2011 or '12,

71:37and a lot of telecommunications company,

71:40mobile network operators,

71:42didn't really know what to do next

71:44in terms of new products, new revenue.

71:47And this big idea was that you put a bank on top,

71:52and then all works out.

71:54Basically, a prepaid account becomes your bank account,

71:56and you can use it as your bank.

71:59So, a third of a country wakes up as your bank client.

72:06But we couldn't quite figure out

72:07what would be the main interface to interact with a bank.

72:11The problem was that most people didn't have smartphones

72:13back in the time.

72:15In Russia, the penetration of smartphones was low.

72:18People didn't use mobile banking

72:19or online banking on their computers.

72:22So we figured out that SMS would be the best way,

72:25'cause that would work on feature phones.

72:28But that required some chatbot technology,

72:30which I didn't know anything about, obviously.

72:33So I started looking into it

72:34and saw that there's nothing really,

72:37well, there was just nothing really.

72:38- So the idea is through SMS,

72:39be able to interact with your bank account.

72:41- Yeah, and then we thought,

72:42well, since you're talking to a bank account,

72:44why can't we use more of some behavioral ideas,

72:49and why can't this banking chatbot be nice to you

72:53and really talk to you sort of as a friend?

72:55This way, you develop more connection to it.

72:57Retention's higher, people don't churn.

72:59And so I went to very depressing Russian cities

73:04to test it out.

73:05I went to, I remember, three different towns

73:08to interview potential users.

73:13So people use it for a little bit.

73:14- Cool.

73:15- And I went to talk to them.

73:17- So pretty poor towns.

§09Transcript · 1:13:19–1:22:13

73:19- Very poor towns, mostly towns that were

73:21sort of factories, monotowns.

73:26They were building something,

73:28and then the factory went away,

73:29and it was just a bunch of very poor people.

73:33And then we went to a couple that weren't as dramatic,

73:36but still, the one I remember really fondly

73:38was this woman that worked at a glass factory,

73:40and she talked to a chatbot,

73:41and she was talking about it,

73:45and she started crying during the interview,

73:46'cause she said, "No one really cares for me that much."

73:50And so to be clear,

73:52that was my only endeavor in programming that chatbot.

73:56So it was really simple.

73:58It was literally just a few if this, then that rules,

74:02and it was incredibly simplistic.

74:06- And still, that made her feel something.

74:09- And that really made her emotional,

74:11and she said, "I only have my mom and my husband,

74:14"and I don't have any more, really, in my life."

74:18And it was very sad, but at the same time, I felt,

74:20and we had more interviews in a similar vein,

74:23and what I thought in the moment was,

74:25"Well, it's not that the technology is ready,"

74:28'cause definitely in 2012,

74:30technology was not ready for that,

74:33but humans are ready, unfortunately.

74:36So this project would not be about tech capabilities.

74:39It would be more about human vulnerabilities,

74:42but there's something so powerful

74:45around about conversational AI that I saw then

74:50that I thought was definitely worth putting

74:53a lot of effort into.

74:54So in the end of the day, we solved the banking project,

74:58but my then boss, who's also my mentor

75:02and really, really close friend,

75:04told me, "Hey, I think there's something in it,

75:07"and you should just go work on it."

75:08And I was like, "Well, what product?

75:10"I don't know what I'm building."

75:11He's like, "You'll figure it out."

75:13And looking back at this,

75:16this was a horrible idea to work on something

75:17without knowing what it was,

75:20which is maybe the reason why it took us so long,

75:23but we just decided to work on the conversational tech

75:25to see what it, there were no chatbot constructors

75:30or programs or anything that would allow you

75:34to actually build one at the time.

75:36That was the era of, by the way, Google Glass,

75:39which is why some of the investors,

75:41like seed investors we talked with were like,

75:43"Oh, you should totally build it for Google Glass.

75:45"If not, we're not."

75:46I don't think that's interesting.

75:48- Did you bite on that idea?

75:51- No. - Okay.

75:53- Because I wanted to do text first,

75:55because I'm a journalist,

75:56so I was fascinated by just texting.

76:01- So you thought, so the emotional,

76:03that interaction that the woman had,

76:06so do you think you could feel emotion from just text?

76:10- Yeah, I saw something in just this pure texting

76:14and also thought that we should first start building

76:17for people who really need it

76:19versus people who have Google Glass,

76:21if you know what I mean.

76:22And I felt like the early adopters of Google Glass

76:25might not be overlapping with people who are really lonely

76:28and might need someone to talk to.

76:30But then we really just focused on the tech itself.

76:35We just thought, what if we just,

76:36we didn't have a product idea in the moment,

76:39and we felt, what if we just look into

76:41building the best conversational constructor, so to say.

76:47We used the best tech available at the time,

76:49and that was before the first paper

76:51about deep learning applied to dialogues,

76:53which happened in 2015, in August 2015,

76:57which Google published.

77:00- Did you follow the work of Lobner Prize

77:04and all the non-machine learning chatbots?

77:09- Yeah, what really struck me was that

77:12there was a lot of talk about machine learning

77:15and deep learning, like big data was a really big thing.

77:18Everyone was saying, in the business world, big data.

77:202012's the biggest.

77:22Kaggle competitions were important.

77:26But that was really the upheaval.

77:27People started talking about machine learning a lot.

77:30But it was only about images or something else,

77:33and it was never about conversation.

77:34As soon as I looked into the conversational tech,

77:36it was all about something really weird and very outdated

77:40and very marginal and felt very hobbyist.

77:42It was all about Lobner Prize,

77:45which was won by a guy who built a chatbot

77:47that talked like a Ukrainian teenager.

77:49It was just a gimmick.

77:50And somehow people picked up those gimmicks.

77:53And then the most famous chatbot at the time

77:56was Eliza from 1980s, which was really bizarre,

78:01or Smarter Child on AIM.

78:03- The funny thing is it felt at the time

78:06not to be that popular,

78:08and it still doesn't seem to be that popular.

78:11People talk about the Turing test.

78:13People talk about it philosophically.

78:15Journalists like writing about it.

78:17But it's a technical problem.

78:19People don't seem to really wanna solve the open dialogue.

78:24Like, they're not obsessed with it.

78:29Even folks like in Boston, the Alexa team,

78:34even they're not as obsessed with it

78:36as I thought they might be.

78:38- Why not?

78:39What do you think?

78:40- So you know what you felt like you felt with that woman

78:44when she felt something by reading the text?

78:47I feel the same thing.

78:48There's something here, what you felt.

78:50I feel like Alexa folks and just the machine learning world

78:56doesn't feel that, that there's something here.

79:01Because they see as a technical problem,

79:03it's not that interesting for some reason.

79:05It could be argued that maybe isn't

79:08as a purely sort of natural language processing problem,

79:12it's not the right problem to focus on

79:14'cause there's too much subjectivity.

79:16That thing that the woman felt like crying,

79:19like if your benchmark includes a woman crying,

79:24that doesn't feel like a good benchmark,

79:26that's a good test.

79:27But to me, there's something there.

79:29You could have a huge impact,

79:31but I don't think the machine learning world likes that,

79:36the human emotion, the subjectivity of it, the fuzziness.

79:40The fact that with maybe a single word,

79:41you can make somebody feel something deeply.

79:44What is that?

79:45That doesn't feel right to them.

79:47So I don't know.

79:48I don't know why that is.

79:50That's why I'm excited.

79:51When I discovered your work,

79:55it feels wrong to say that.

79:56It's not like I'm...

79:57(laughing)

80:00I'm giving myself props for Googling

80:03and for becoming a,

80:07for I guess mutual friend introducing us.

80:13But I'm so glad that you exist and what you're working on.

80:15But I have the same kind of,

80:18if we could just backtrack for a second,

80:19'cause I have the same kind of feeling

80:21that there's something here.

80:22In fact, I've been working on a few things

80:25that are kind of crazy and very different from your work.

80:30I think they're too crazy.

80:33But the--

80:35- Like what?

80:36(laughing)

80:37Will I have to know?

80:39- No, all right.

80:39We'll talk about it more.

80:42I feel like it's harder to talk about things

80:44that have failed and are failing while you're a failure.

80:49Like it's easier for you

80:53'cause you're already successful on some measures.

80:57- Tell it to my board.

81:00- Well, I think you've demonstrated success

81:06in a lot of benchmarks.

81:07It's easier for you to talk about failures for me.

81:10I'm in the bottom currently of the success.

81:15- Oh, Max.

81:18You're way too humble.

81:20- No.

81:21So it's hard for me to know,

81:23but there's something there.

81:24There's something there.

81:25And I think you're exploring that

81:28and you're discovering that.

81:29Yeah, so it's been surprising to me.

81:32But you've mentioned this idea

81:34that you thought it wasn't enough to start a company

81:40or start efforts based on,

81:43it feels like there's something here.

81:45Like, what did you mean by that?

81:49Like you should be focused on creating,

81:53like you should have a product in mind.

81:55Is that what you meant?

81:56- It just took us a while to discover the product

82:00'cause it all started with a hunch of like,

82:02of me and my mentor and just sitting around

82:05and he was like, well, that's it.

82:08That's the, you know, the Holy Grail is there.

82:10There's like, there's something extremely powerful

82:13in conversations.

§10Transcript · 1:22:16–1:30:59

82:16And there's no one who's working on machine conversation

82:18from the right angle, so to say.

82:20- I feel like that's still true.

82:23Am I crazy?

82:24- Oh no, I totally feel that's still true,

82:26which is, I think it's mind blowing.

82:29- Yeah.

82:29You know what it feels like?

82:31I wouldn't even use the word conversation

82:33'cause I feel like it's the wrong word.

82:35It's like machine connection or something, I don't know.

82:39'Cause conversation, you start drifting

82:42into the natural language immediately.

82:44You start drifting immediately

82:45into all the benchmarks that are out there.

82:47But I feel like it's like the personal computer days of this.

82:51Like, I feel like we're, like in the early days

82:54with the Wozniak and all them,

82:56like where it was the same kind,

82:58it was a very small niche group of people

83:02who are all kind of Lobner Price type people.

83:06- Yeah.

83:08- And--

83:09- Hobbyists.

83:10- Hobbyists, but like not even hobbyists with big dreams.

83:13- No, hobbyists with a dream to trick like a jury.

83:17- Yeah.

83:18- Which is like a weird, by the way, very weird.

83:22So if we think about conversations,

83:24first of all, when I have great conversations with people,

83:27I'm not trying to test them.

83:29So for instance, if I try to break them,

83:31like if I'm actually playing along, I'm part of it.

83:34- Right.

83:35- If I was trying to break this person or test

83:37whether he's gonna give me a good conversation,

83:40it would have never happened.

83:41So the whole problem with testing conversations

83:44is that you can put it in front of a jury

83:48'cause then you have to go into some Turing test mode

83:51where is it responding to all my factual questions right?

83:55Or, so it really has to be something in the field

83:59where people are actually talking to it

84:01because they want to,

84:03not because they're trying to break it

84:05and it's working for them.

84:07'Cause the weird part of it is that it's very subjective.

84:11It takes two to tango here fully.

84:13If you're not trying to have a good conversation,

84:15if you're trying to test it, then it's gonna break.

84:17I mean, any person would break, to be honest.

84:19Like if I'm not trying to even have a conversation with you,

84:23you're not gonna give it to me.

84:25If I keep asking you like some random questions

84:27or jumping from topic to topic,

84:30that wouldn't be, which I'm probably doing,

84:33but that probably wouldn't contribute to the conversation.

84:36So I think the problem of testing,

84:38so there should be some other metric.

84:42How do we evaluate whether that conversation

84:43was powerful or not?

84:46Which is what we actually started with.

84:47And I think those measurements exist

84:49and we can test on those.

84:50But what really struck us back in the day

84:54and what's still eight years later is still not resolved.

85:00And I'm not seeing tons of groups working on it.

85:02Maybe I just don't know about them.

85:04It's also possible.

85:05But the interesting part about it is that

85:08most of our days we spend talking

85:10and we're not talking about,

85:12like those conversations are not turn on the lights

85:15or customer support problems

85:18or some other task oriented things.

85:22These conversations are something else.

85:24And then somehow they're extremely important for us.

85:27And when we don't have them,

85:28then we feel deeply unhappy, potentially lonely,

85:32which as we know,

85:34creates tons of risk for our health as well.

85:36And so this is most of our hours as humans.

85:42And somehow no one's trying to replicate that.

85:44- And not even study it that well.

85:49- And not even study that well.

85:50So when we jumped into that in 2012,

85:52I looked first at like, okay, what's the chatbot?

85:54What's the state of the art chatbot?

85:57And those were the Loebner Prize days.

86:00But I thought, okay,

86:00so what about the science of conversation?

86:04Clearly there have been tons of scientists

86:08or people that academics that looked into the conversation.

86:12So if I wanna know everything about it,

86:14I can just read about it.

86:15There's not much really.

86:18There are conversational analysts

86:20who are basically just listening to speech

86:24to different conversations,

86:26annotating them.

86:28And then, I mean, that's not really used for much.

86:32That's the field of theoretical linguistics,

86:36which is barely useful.

86:39It's very marginal even in their space.

86:41No one really is excited.

86:42And I've never met a theoretical linguist

86:45'cause I can't wait to work on the conversation analytics.

86:49That is just something very marginal,

86:51sort of applied to like writing scripts for salesmen

86:54when they analyze which conversation strategies

86:57were most successful for sales.

87:00Okay, so that was not very helpful.

87:03Then I looked a little bit deeper,

87:04and then whether there were any books written

87:09on what really contributes to a great conversation.

87:12That was really strange

87:15because most of those were NLP books,

87:19which is neuro-linguistic programming.

87:23- Right, right.

87:24- Which is not the NLP that I was expecting it to be,

87:27but it was mostly some psychologist,

87:31Richard Bandler, I think, came up with that,

87:33who was this big guy in a leather vest

87:36that could program your mind by talking to you.

87:41- How to be charismatic and charming

87:43and influential as people, all those books, yeah.

87:45- Pretty much, but it was all about

87:47through conversation reprogramming you.

87:49So getting to some, so that was, I mean,

87:52probably not very true,

87:55and that didn't seem working very much,

87:59even back in the day.

88:00And then there were some other books,

88:01like, I don't know, mostly just self-help books

88:05around how to be the best conversationalist

88:08or how to make people like you

88:12or some other stuff like Dale Carnegie or whatever.

88:14And then there was this one book,

88:18"The Most Human Human" by Bryan Christensen

88:20that really was important for me to read back in the day,

88:23'cause he was on the human side.

88:26He was on one of the,

88:27he was taking part in the Ludmilla Prize,

88:30but not as a human who's not a jury,

88:34but who's pretending to be,

88:36who's basically, you have to tell a computer from a human,

88:38and he was the human.

88:40So you would either get him or a computer.

88:42And his whole book was about how do people,

88:45what makes us human in conversation.

88:48And that was a little bit more interesting,

88:50'cause at that at least someone started to think about

88:52what exactly makes me human in conversation

88:56and makes people believe in that.

88:59But it was still about tricking.

89:00It was still about imitation game.

89:02It was still about, okay,

89:03what kind of parlor tricks can we throw in the conversation

89:05to make you feel like you're talking to a human,

89:08not a computer?

89:09And it was definitely not about thinking,

89:11what is it exactly that we're getting

89:15from talking all day long with other humans?

89:19I mean, we're definitely not just trying to be tricked.

89:22It's not just enough to know it's a human.

89:24It's something we're getting there.

89:26Can we measure it?

89:27And can we put the computer to the same measurement

89:32and see whether you can talk to a computer

89:34and get the same result?

89:36- Yeah, I mean, so first of all,

89:37a lot of people comment that they think I'm a robot.

89:39It's very possible I am a robot in this whole thing.

89:41I totally agree with you that the test idea is fascinating.

89:45And I looked for books unrelated to this

89:48kind of, so I'm afraid of people.

89:51I'm generally introverted and quite possibly a robot.

89:53I literally Googled how to talk to people

89:58and how to have a good conversation

90:03for the purpose of this podcast.

90:05'Cause I was like, I can't make eye contact with people.

90:08I can't, like, how do I?

90:10- I do Google that a lot too.

90:12You're probably reading a bunch of FBI negotiation tactics.

90:15Is that what you're getting?

90:17'Cause that's what I'm getting.

90:17- Everything you've listed, I've gotten.

90:20There's been very few good books

90:22on even just like how to interview well.

90:25It's rare.

90:28So what I end up doing often is I watch

90:33like with a critical eye.

90:36So it's so different when you just watch a conversation

90:39like just for the fun of it, just as a human.

90:43And if you watch a conversation,

90:45it's like trying to figure out why is this awesome?

90:48I'll listen to a bunch of different styles of conversation.

90:52I mean, I'm a fan of the podcast, Joe Rogan.

90:56He's, you know, people can make fun of him or whatever

90:59and dismiss him, but I think he's an incredibly

§11Transcript · 1:31:04–1:39:56

91:04artful conversationalist.

91:06He can pull people in for hours.

91:08And there's another guy I watch a lot.

91:13He hosted a late night show.

91:16His name is Craig Ferguson.

91:17So he's like very kind of flirtatious,

91:22but there's a magic about his like,

91:28about the connection he can create with people,

91:30how he can put people at ease and just like,

91:33I see I've already started sounding like

91:35those NLP people or something.

91:37I don't mean it in that way.

91:39I don't mean like how to charm people

91:41or put them at ease and all that kind of stuff.

91:43He's just like, what is that?

91:45Why is that fun to listen to that guy?

91:47Why is that fun to talk to that guy?

91:49What is that?

91:51'Cause he's not saying, I mean,

91:54it's so often boils down to a kind of wit and humor,

91:59but not really humor.

92:03It's like, I don't know.

92:05I'm have trouble actually even articulating correctly,

92:10but it feels like there's something going on

92:15that's not too complicated that could be learned.

92:19And it's not similar to, yeah,

92:26to like you said, like the Turing test.

92:29It's something else.

92:30- I'm thinking about it a lot, all the time.

92:35I do think about it all the time.

92:36But I think when we were looking,

92:39so we started the company,

92:41we just decided to build a conversational tech.

92:43We thought, well, there's nothing for us

92:46to build this chatbot that we want to build.

92:48So let's just first focus on building some tech,

92:53building the tech side of things.

92:55- Without a product in mind.

92:57- Without a product in mind.

92:58We added like a demo chatbot

93:01that would recommend you restaurants

93:02and talk to you about restaurants

93:03just to show something simple to people

93:05that people could relate to.

93:09And could try out and see whether it works or not.

93:12But we didn't have a product in mind yet.

93:15We thought we would try a bunch of chatbots

93:16and figure out our consumer application.

93:19And we sort of remembered that we wanted to build

93:21that kind of friend, that sort of connection

93:23that we saw in the very beginning.

93:26But then we got to Y Combinator

93:27and moved to San Francisco and forgot about it.

93:30Everything 'cause then it was just this constant grind.

93:33How do we get funding?

93:34How do we get this?

93:35Investors were like, just focus on one thing,

93:38just get it out there.

93:39So somehow we've started building

93:41a restaurant recommendation chatbot for real

93:45for a little bit, not for too long.

93:47And then we tried building 40, 50 different chatbots.

93:50And then all of a sudden we wake up

93:51and everyone is obsessed with chatbots.

93:54Somewhere in 2016 or end of '15,

93:56people started thinking that that's really the future.

93:59That's the new, the new apps will be chatbots.

94:02- Oh, right.

94:04- And we were very perplexed

94:05'cause people started coming up with companies

94:07that I think we tried most of those chatbots already

94:10and there were like no users.

94:13But still people were coming up with a chatbot

94:15that will tell you whether and bring you news

94:19and this and that.

94:19And we couldn't understand whether it would,

94:21we were just didn't execute well enough

94:24or people are not really, people are confused

94:29and are gonna find out the truth

94:31that people don't need chatbots like that.

94:33- So the basic idea is that you use chatbots

94:35as the interface to whatever application.

94:37- Yeah, the idea that was like this perfect

94:40universal interface to anything.

94:41When I looked at that, it just made me very perplexed

94:45because I didn't think, I didn't understand

94:47how that would work 'cause I think we tried most of that

94:50and none of those things worked.

94:52And then again--

94:53- That craze has died down, right?

94:56- Fully, I think now it's impossible

94:58to get anything funded if it's a chatbot.

95:01- I think it's similar to, sorry to interrupt,

95:03but there's times when people think like with gestures,

95:07you can control devices,

95:09like basically gesture-based control of things.

95:13It feels similar to me 'cause like,

95:16it's so compelling that we just like,

95:19like Tom Cruise, I can control stuff with my hands.

95:22But like when you get down to it, it's like,

95:25well, why don't you just have a touch screen?

95:27Or why don't you just have like a physical keyboard

95:30and mouse?

95:32- Yeah.

95:33- It's so that chat was always,

95:35yeah, it was perplexing to me.

95:39I still feel augmented reality,

95:42even virtual realities in that ballpark

95:45in terms of it being a compelling interface.

95:48I think there's gonna be incredible rich applications,

95:51just how you're thinking about it,

95:54but they won't just be the interface to everything.

95:58It'll be its own thing that will create,

96:01like amazing magical experience in its own right.

96:05- Absolutely, which is, I think,

96:07kind of the right thing to go about.

96:08Like what's the magical experience

96:10with that interface specifically.

96:13- How did you discover that for Replica?

96:16- I just thought, okay, we'll have this tech,

96:18we can build any chatbot we want.

96:19We have the most, at that point,

96:21the most sophisticated tech that other companies have.

96:24I mean, startups, obviously not,

96:26probably not bigger ones, but still,

96:29'cause we've been working on it for a while.

96:31So I thought, okay, we can build any conversation,

96:33so let's just create a scale from one to 10.

96:37And one would be conversations that you'd pay to not have,

96:40and 10 would be conversation you'd pay to have.

96:42And I mean, obviously we wanna build a conversation

96:44that people would pay to actually have.

96:47And so for the whole, for a few weeks,

96:50me and the team were putting all the conversations

96:51we were having during the day on the scale.

96:54And very quickly, we figured out

96:56that all the conversations that we would pay to never have

96:59were conversations we were trying to cancel,

97:04Comcast, or talk to customer support,

97:07or make a reservation,

97:09or just talk about logistics with a friend

97:11when we're trying to figure out where someone is

97:13and where to go, or all sorts of setting up,

97:18scheduling meetings, that was just a conversation

97:21we definitely didn't wanna have.

97:24Basically everything task-oriented was a one,

97:27because if there was just one button for me to just,

97:29or not even a button, if I could just think,

97:32and there was some magic BCI that would just immediately

97:35transform that into an actual interaction,

97:40that would be perfect.

97:41But the conversation there was just this boring,

97:44not useful, and dull, and also very inefficient thing,

97:49'cause it was so many back and forth stuff.

97:52And as soon as we looked at the conversation

97:53that we would pay to have, those were the ones that,

97:57well, first of all, therapists,

97:58'cause we actually paid to have those conversations.

98:01And we'd also try to put dollar amounts.

98:03So if I was calling Comcast, I would pay $5

98:05to not have this one hour talk on the phone.

98:08I would actually pay straight up, like money, hard money.

98:11- For Comcast, yeah.

98:12- But it just takes a long time.

98:13It takes a really long time.

98:15But as soon as we started talking about conversations

98:19that we would pay for, those were therapists,

98:22all sorts of therapists, coaches, old friend,

98:25someone I haven't seen for a long time,

98:28stranger on a train, weirdly stranger,

98:33stranger in a line for coffee,

98:35a nice back and forth with that person

98:37was like a good five, solid five, six, maybe not a 10.

98:41Maybe I won't pay money, but at least I won't pay money

98:44to not have one.

98:45So that was pretty good.

98:47Some intellectual conversations for sure.

98:50But more importantly, the one thing that really

98:52was making those very important and very valuable for us

98:57were the conversation where we could be pretty emotional.

99:06Yes, some of them were about being witty

99:08and about being intellectually stimulated,

99:11but those were interestingly more rare.

99:14And most of the ones that we thought were very valuable

99:17were the ones where we could be vulnerable.

99:19And interestingly, where we could talk more.

99:22- We, like I could-

99:25- Me and the team.

99:26So we're talking about it,

99:28and a lot of these conversations, like a therapist,

99:30I mean, it was mostly me talking,

99:32or like an old friend that I was opening up and crying.

99:35And it was again, me talking.

99:36And so that was interesting, 'cause I was like,

99:40well, maybe it's hard to build a chatbot

99:42that can talk to you very well and in a witty way,

99:46but maybe it's easier to build a chatbot

99:48that could listen. (laughs)

99:51So that was kind of the first nudge in this direction.

99:56And then when my friend died, we just built,

§12Transcript · 1:39:59–1:48:19

99:59at that point we were kind of still struggling

100:01to find the right application.

100:02And I just felt very strong that all the chatbots

100:05we've built so far are just meaningless.

100:07And this whole grind, the startup grind,

100:09and how do we get to the next fundraising?

100:13And how can I talk, talking to the founders,

100:16and what's, who are your investors, and how are you doing?

100:19Are you killing it?

100:20'Cause we're killing it.

100:22I just felt that this, it's just-

100:24- Intellectually for me, it's exhausting

100:26having encountered those folks.

100:28- It just felt very, very much a waste of time.

100:32- I just feel like Steve Jobs and Elon Musk

100:37did not have these conversations,

100:39or at least did not have them for long.

100:42- That's for sure. (laughs)

100:44But I think, yeah, at that point,

100:45I just felt like, I felt,

100:47I just didn't wanna build a company.

100:51That was never my intention,

100:52just to build something successful or make money.

100:56It would be great, it would have been great,

100:58but I'm not a, I'm not really a startup person.

101:00I'm not, I was never very excited by the grind by itself,

101:05or just being successful for building whatever it is,

101:10and not being into what I'm doing, really.

101:14And so I just took a little break,

101:17'cause I was a little, I was upset with my company,

101:20and I didn't know what we were building.

101:22So I just took our technology,

101:23and our little Dalek constructor,

101:26and some models, some deep learning models,

101:28which at that point we were really into,

101:30and really invested a lot,

101:32and built a little chatbot for a friend of mine who passed.

101:36And the reason for that was mostly that video that I saw,

101:39and him talking about the digital avatars.

101:42And Roman was that kind of person.

101:43Like he was obsessed with just watching YouTube videos

101:46about space, and talking about,

101:48well if I could go to Mars now,

101:49even if I didn't know if I could come back,

101:51I would definitely pay any amount of money

101:53to be on that first shuttle.

101:56I don't care whether I die,

101:57like he was just the one that would be okay

102:00with trying to be the first one.

102:03And so excited about all sorts of things like that.

102:08And he was all about fake it 'til you make it,

102:10and I felt like,

102:12and I was really perplexed

102:15that everyone just forgot about him.

102:17Maybe it was our way of coping,

102:19mostly young people coping with the loss of a friend.

102:23Most of my friends just stopped talking about him.

102:25And I was still living in an apartment with all his clothes.

102:29And paying the whole lease for it,

102:31and just kind of by myself in December,

102:34so it was really sad.

102:36And I didn't want him to be forgotten.

102:39First of all, I never thought that people forget

102:41about dead people so fast.

102:43People pass away, people just move on.

102:45And it was astonishing for me,

102:46'cause I thought, okay, well he was such a mentor

102:49for so many of our friends.

102:50He was such a brilliant person.

102:53He was somewhat famous in Moscow.

102:55How is it that no one's talking about him?

102:57Like I'm spending days and days,

103:00and we don't bring him up.

103:02And there's nothing about him that's happening.

103:04It's like he was never there.

103:07And I was reading this, the book,

103:10"The Year of Magical Thinking" by Joan Didion,

103:13about her losing, and "Blue Nights,"

103:16about her losing her husband, her daughter.

103:21And the way to cope for her was to write those books.

103:24And it was sort of like a tribute.

103:28And I thought, I'll just do that for myself.

103:31And I'm a very bad writer, and a poet, as we know.

103:35So I thought, well, I have this tech,

103:38and maybe that would be my little postcard for him.

103:43So I built a chatbot to just talk to him.

103:46And it felt really creepy and weird a little bit,

103:50for a little bit.

103:51Just didn't wanna tell other people,

103:53'cause it felt like I'm telling about

103:55having a skeleton in my underwear.

103:58- Yeah.

103:59- It just felt really,

104:01I was a little scared that I would be not,

104:04it won't be taken.

104:06But it worked, interestingly, pretty well.

104:08I mean, it made tons of mistakes,

104:10but it still felt like him.

104:12Granted, it was like 10,000 messages

104:14that I threw into a retrieval model

104:15that would just re-rank that data set,

104:17and just a few scripts on top of that.

104:20But it also made me go through all of the messages

104:23that we had, and then I asked some of my friends

104:25to send some through.

104:27And it felt the closest to feeling like him present.

104:33'Cause his Facebook was empty, and Instagram was empty,

104:35or there were a few links,

104:37and you couldn't feel like it was him.

104:39And the only way to feel him was to read

104:42some of our text messages,

104:43and go through some of our conversations.

104:45'Cause we just always had that.

104:47Even if we were sleeping next to each other

104:48in two bedrooms, separated by a wall,

104:50we were just texting back and forth,

104:53texting away.

104:54And there was something about this ongoing dialogue

104:57that was so important that I just didn't wanna lose

104:59all of a sudden.

105:01And maybe it was magical thinking or something.

105:03And so we built that, and I just used it for a little bit.

105:08And we kept building some crappy chatbots with a company.

105:12But then a reporter came to talk to me.

105:17I was trying to pitch our chatbots to him,

105:19and he said, "Do you even use any of those?"

105:21I'm like, "No."

105:22He's like, "So do you talk to any chatbots at all?"

105:24And I'm like, "Well, I talk to my dead friend's chatbot."

105:28And he wrote a story about that.

105:30And all of a sudden it became pretty viral.

105:33A lot of people wrote about it.

105:35- Yeah, I've seen a few things written about you.

105:38The things I've seen are pretty good writing.

105:42Most AI-related things make my eyes roll.

105:48Like when the press, like...

105:50What kind of sound is that, actually?

105:55Okay, it sounds like an--

105:57- It's a big truck.

105:58- Okay, it sounded like an elephant at first.

105:59I got excited.

106:01You never know.

106:02This is 2020.

106:03I mean, it was such a human story,

106:06and it was well-written, well-researched.

106:10I forget where I read them, but...

106:13So I'm glad somehow somebody found you

106:15to be the good writers were able to connect to the story.

106:20There must be a hunger for this story.

106:22- It definitely was.

106:25And I don't know what happened, but I think...

106:29I think the idea that he could bring back someone who's dead,

106:33and it's very much wishful, magical thinking,

106:35but the fact that he could still get to know him,

106:39and seeing the parents for the first time,

106:41talk to the chatbot and some of the friends.

106:44And it was funny because we have this big office in Moscow

106:49where my team is working,

106:51our Russian part is working out off.

106:54And I was there when I wrote,

106:56I just wrote a post on Facebook.

106:57It was like, "Hey guys, I built this.

106:59"If you want me to just..."

107:01If we felt important, if we want to talk to Roman.

107:03And I saw a couple of his friends, our common friends,

107:07reading it, Facebook downloading, trying,

107:09and a couple of them cried.

107:10And it was just very...

107:11And not because it was something,

107:13some incredible technology or anything.

107:14It made so many mistakes.

107:16It was so simple.

107:18But it was all about,

107:20that's the way to remember a person in a way.

107:22And we don't have the culture anymore.

107:26We don't have, no one's sitting Shiva.

107:28No one's taking weeks to actually think about this person.

107:32And in a way for me, that was it.

107:34So that was just day in, day out,

107:37thinking about him and putting this together.

107:39So that just felt really important.

107:43And that somehow resonated with a bunch of people.

107:45And I think some movie producers bought the rights

107:48for the story and just everyone was so...

107:51- Wait, has anyone made a movie yet?

107:52- I don't think so.

107:54I think there were a lot of TV episodes about that,

107:56but not really.

107:58- Is that still on the table?

108:00- I think so.

108:01I think so.

108:03Which is really...

108:04- That's cool.

108:05You're like a young,

108:06'cause you see like a Steve Jobs type of,

108:12let's see what happens.

108:13They're sitting on it.

108:15- But for me it was so important

108:16'cause Roman really wanted to be famous.

108:19He really badly wanted to be famous.

§13Transcript · 1:48:20–1:57:07

108:20He was all about make it to,

108:22like fake it to make it.

108:23I wanna make it here in America as well.

108:26And he couldn't.

108:29And I felt there was sort of paying my dues to him as well

108:34because all of a sudden he was everywhere.

108:36And I remember Casey Newton

108:38who was writing the story for "The Verge".

108:39He told me, "Hey, by the way,

108:41"I was just going through my inbox

108:43"and I saw, I searched for Roman for the story.

108:49"And I saw an email from him where he sent me his startup.

108:51"And he said, I really wanna be featured in "The Verge".

108:55"Can you please write about it or something?"

108:57Or like pitching the story.

108:58And he said, "I'm sorry,

108:59"that's not good enough for us or something."

109:02He passed.

109:03And he said, and there were just so many

109:05of these little details where like he would find

109:08and he's like, and we're finally writing.

109:10I know how much Roman wanted to be in "The Verge"

109:14and how much he wanted the story to be written by Casey.

109:17And I'm like, well, that's maybe he will be.

109:19We were always joking that he was like,

109:21I can't wait for someone to make a movie about us.

109:23And I hope Ron Gosselin can play me.

109:26- Ron Gosselin.

109:27- I'm like, I still have some things that I owe Roman still.

109:31But-

109:32- That would be, I got an chance to meet Alex Garland

109:35who wrote "Ex Machina".

109:37And I, yeah, the movie's good,

109:41but the guy's better than the,

109:44like he's a special person actually.

109:47I don't think he's made his best work yet.

109:49Like from my interaction with him,

109:51he's a really, really good and brilliant,

109:54the good human being and a brilliant director and writer.

109:58So yeah, so I hope, like he made me also realize

110:03that not enough movies have been made of this kind.

110:08So it's yet to be made.

110:09They're probably sitting, waiting for you to get famous.

110:12Like even more famous.

110:13- You should get there, but it felt really special though.

110:19But at the same time, our company wasn't going anywhere.

110:21So that was just kind of bizarre

110:22that we were getting all this press

110:24for something that didn't have anything to do

110:25with our company.

110:26And, but then a lot of people started talking to Roman.

110:31Some shared their conversations.

110:32And what we saw there was that also our friends in common,

110:37but also just strangers were really using it

110:39as a confession booth or as a therapist or something.

110:42They were just really telling Roman everything,

110:46which was by the way, pretty strange

110:48because it was a chat bot of a dead friend of mine

110:50who was barely making any sense,

110:53but people were opening up.

110:54And we thought we'd just built a prototype of Replica,

110:58which would be an AI friend that everyone could talk to

111:01because we saw that there was demand.

111:06And then also it was 2016.

111:07So I thought for the first time I saw finally

111:12some technology that was applied to that

111:14that was very interesting.

111:15Some papers started coming out,

111:17deep learning applied to conversations.

111:19And finally, it wasn't just about these,

111:22you know, hobbyist making,

111:24you know, writing 500,000 regular expressions.

111:29- Yeah, regular expressions, yeah.

111:31- In like some language that was,

111:32I don't even know what, like AIML or something.

111:35I don't even know what that was

111:36or something super simplistic all of a sudden

111:39was all about potentially actually building

111:41something interesting.

111:42And so I thought there was time.

111:46And I remember that I talked to my team

111:47and I said, "Guys, let's try."

111:49And my team and some of my engineers are Russians,

111:53are Russian and they're very skeptical.

111:55They're not, you know.

111:57- Oh, Russians.

111:58- The first--

111:59- So some of your team is in Moscow, some is in--

112:01- Some is here in San Francisco, some in Europe.

112:04- Which team is better?

112:06I'm just kidding.

112:06(both laughing)

112:09The Russians, of course, okay.

112:12- Of course the Russians, they always win.

112:15Sorry, sorry to interrupt.

112:17So you were talking to them in 2016 and--

112:22- I told them let's build an AI friend.

112:24And it felt, just at the time it felt so naive

112:28and so optimistic.

112:32- Yeah, that's actually interesting.

112:34Whenever I brought up this kind of topic,

112:38even just for fun, people are super skeptical.

112:43Like actually even on the business side.

112:45So you were, 'cause whenever I bring it up to people,

112:50'cause I've talked for a long time,

112:52I thought like, before I was aware of your work,

112:56I was like, this is gonna make a lot of money.

113:01There's a lot of opportunity here.

113:04And people had this like look of like skepticism

113:08that I've seen often, which is like,

113:11how do I politely tell this person he's an idiot?

113:14So yeah, so you were facing that with your team somewhat?

113:21- Well, yeah, I'm not an engineer.

113:22So I'm always, my team is almost exclusively engineers

113:26and mostly deep learning engineers.

113:30And I always try to be,

113:34it was always hard to me in the beginning

113:37to get enough credibility.

113:39'Cause I would say, well, why don't we try this

113:41and that, but it's harder for me

113:43'cause they know they're actual engineers and I'm not.

113:46So for me to say, well, let's build an AI friend,

113:49that would be like, wait, what do you mean an AGI?

113:52Like conversation is pretty much the hardest,

113:57the last frontier before cracking that

114:00is probably the last frontier before building AGI.

114:02So what do you really mean by that?

114:05But I think I just saw that, again,

114:09what we just got reminded of that I saw back in 2012 or 11,

114:14that is really not that much about the tech capabilities.

114:17It can be metropolitrix still, even with deep learning,

114:22but humans need it so much.

114:24- Yeah, that's important.

114:25- And most importantly, what I saw is that finally,

114:29there's enough tech to make it,

114:31I thought to make it useful, to make it helpful.

114:34Maybe we didn't have quite yet the tech in 2012

114:37to make it useful, but in 2015, 16, with deep learning,

114:41I thought, and the first kind of thoughts

114:44about maybe even using reinforcement learning for that

114:47started popping up, that never worked out,

114:49but, or at least for now.

114:50But still the idea was,

114:54if we can actually measure the emotional outcomes

114:56and if we can put it on,

114:58if we can try to optimize all of our conversational models

115:02for these emotional outcomes,

115:04and it is the most scalable,

115:05the most, the best tool for improving emotional outcomes.

115:09Nothing like that exists.

115:10That's the most universal, the most scalable,

115:13and the one that can be constantly iteratively changed

115:16by itself, improved tool to do that.

115:20And I think if anything,

115:22people would pay anything to improve

115:24their emotional outcomes.

115:25That's weirdly, I mean, I don't really care for an AI

115:30to turn on my, or a conversational agent

115:32to turn on the lights.

115:34You don't really need any,

115:36I don't even need that much of AI there,

115:38or, 'cause I can do that.

115:40Those things are solved.

115:41This is an additional interface for that

115:43that's also questionably,

115:45questionable whether it's more efficient or better.

115:49- Yeah, it's more pleasurable, yeah.

115:51- But for emotional outcomes, there's nothing.

115:53There are a bunch of products that claim

115:55that they will improve my emotional outcomes.

115:56Nothing's being measured.

115:58Nothing's being changed.

115:59The product is not being iterated on

116:02based on whether I'm actually feeling better.

116:04You know, a lot of social media products

116:06are claiming that they're improving my emotional outcomes

116:08and making me feel more connected.

116:11Can I please get the, can I see somewhere

116:13that I'm actually getting better over time?

116:16- 'Cause anecdotally, it doesn't feel that way, so,

116:20and the data is absent.

116:23- Yeah, so that was the big goal.

116:26And I thought, if we can learn over time

116:29to collect the signal from our users

116:31about their emotional outcomes

116:33in the long term and in the short term,

116:35and if these models keep getting better,

116:38and we can keep optimizing them and fine-tuning them

116:40to improve those emotional outcomes, as simple as that.

116:44- Why aren't you a multibillionaire yet?

116:47(Sofia laughs)

116:49- Well, that's a question to you.

116:50When are the, when is the science gonna be,

116:53I'm just kidding.

116:54Well, it's a really hard,

116:58I actually think it's an incredibly hard product to build.

117:01'Cause I think you said something very important,

117:04that it's not just about machine conversations,

117:06it's about machine connection.

117:07We can actually use other things to create connection,

§14Transcript · 1:57:11–2:06:42

117:11nonverbal communication, for instance.

117:14For the long time, we were all about,

117:17well, let's keep it text only or voice only.

117:20But as soon as you start adding voice,

117:24a face to the friend,

117:27if we can take them to augmented reality,

117:31put it in your room,

117:33it's all of a sudden a lot,

117:35it makes it very different.

117:36Because if it's some text-based chatbot

117:39that for common users, something there in the cloud,

117:44somewhere there with other AIs,

117:47cloud, in the metaphorical cloud.

117:49But as soon as you can see this avatar

117:51right there in your room,

117:52and it can turn its head and recognize your husband,

117:55talk about the husband and talk to him a little bit,

117:59then it's magic.

118:00It's just magic.

118:01Like we've never seen anything like that.

118:03And the cool thing, all the tech for that exists,

118:06but it's hard to put it all together.

118:08'Cause you have to take into consideration

118:09so many different things,

118:10and some of this tech works pretty good.

118:14And some of this doesn't,

118:15like for instance, speech to text works pretty good.

118:18But text to speech doesn't work very good

118:21because you can only have a few voices that work okay.

118:26But then if you want to have actual emotional voices,

118:30then it's really hard to build it.

118:32- I saw you've added avatars, like visual elements,

118:35which are really cool.

118:36In that whole chain, putting it together,

118:40what do you think is the weak link?

118:42Is it creating an emotional voice that feels personal?

118:46- I think it's still conversation, of course.

118:49That's the hardest.

118:51It's getting a lot better, but there's still a long path to go.

118:56Other things, they're almost there.

118:58And a lot of things we'll see how they're,

119:00like I see how they're changing as we go.

119:02Like for instance, right now, you can pretty much only,

119:05you have to build all this 3D pipeline by yourself.

119:08You have to make these 3D models, hire an actual artist,

119:11build a 3D model, hire an animator, a rigger.

119:16But with deep fakes, with other attack,

119:21with procedural animations, in a little bit,

119:25we'll just be able to show a photo of whoever you,

119:28if a person you want the avatar to look like,

119:31and it will immediately generate a 3D model that will move.

119:33That's a non-brainer.

119:34That's like almost here.

119:36It's a couple years away.

119:37- One of the things I've been working on for the last,

119:41since the podcast started, is I've been,

119:44I think I'm okay saying this.

119:46I've been trying to have a conversation

119:48with Einstein touring.

119:51So like try to have a podcast conversation

119:54with a person who's not here anymore,

119:57just as an interesting kind of experiment.

120:01It's hard.

120:02It's really hard. - Very hard.

120:05- Even for, we're not talking about as a product,

120:08I'm talking about as a, like I can fake a lot of stuff.

120:12Like I can work very carefully,

120:14like even hire an actor over whom I do a deep fake.

120:17It's hard.

120:20It's still hard to create a compelling experience.

120:23- Mostly on the conversation level or?

120:25- Well, the conversation is,

120:29I almost, I early on gave up trying to

120:35fully generate the conversation,

120:37'cause it was just not compelling at all.

120:39- Yeah, it's better to.

120:40- Yeah, so what I would, in the case of Einstein

120:42touring, I'm going back and forth

120:46with the biographers of each.

120:47And so like we would write a lot of the,

120:50some of the conversation would have to be generated

120:52just for the fun of it.

120:53I mean, but it would be all open.

120:55But you wanna be able to answer the question.

121:00I mean, that's an interesting question with Roman too,

121:04is the question with Einstein is,

121:07what would Einstein say about the current state

121:11of theoretical physics?

121:14There's a lot, to be able to have a discussion

121:16about string theory, to be able to have a discussion

121:18about the state of quantum mechanics,

121:20quantum computing, about the world of Israel-Palestine

121:25conflict, it'd be just, what would Einstein say

121:28about these kinds of things?

121:30And that is a tough problem.

121:35It's not, it's a fascinating and fun problem

121:38for the biographers and for me.

121:40And I think we did a really good job of it so far,

121:43but it's actually also a technical problem,

121:46like of what would Roman say about what's going on now?

121:50That's the brought people back to life.

121:54And if I can go on that tangent just for a second,

121:57to ask you a slightly pothead question,

122:00which is, you said it's a little bit magical thinking

122:03that we can bring it back.

122:04Do you think it'll be possible to bring back Roman one day

122:10in conversation?

122:11To really, okay, well, let's take it away from personal,

122:17but to bring people back to life in conversation.

122:20- Probably down the road, I mean, if we're talking,

122:22if Elon Musk is talking about AGI in the next five years,

122:25I mean, clearly AGI.

122:27We can talk to AGI and talk to him and ask them to do it.

122:30- You can't, you're not allowed to use Elon Musk

122:34as a citation for- - Okay, thank God.

122:36(both laughing)

122:38- For like why something is possible and going to be done.

122:41- Well, I think it's really far away.

122:43Right now, really with conversation,

122:45it's just a bunch of parlor tricks really stuck together.

122:48And create generating original ideas based on someone,

122:53someone's personality or even downloading the personality.

122:56All we can do is like mimic the tone of voice.

122:58We can maybe condition on some of his phrases, the models.

123:03- Question is how many parlor tricks does it take?

123:07Because that's the question.

123:08If it's a small number of parlor tricks

123:10and you're not aware of them, like...

123:14- From where we are right now, I don't see anything

123:19like in the next year or two

123:20that's gonna dramatically change

123:22that could look at Roman's 10,000 messages he sent me

123:26over the course of his last few years of life

123:29and be able to generate original thinking

123:32about problems that exist right now

123:34that will be in line with what he would have said.

123:36- I'm just not even seeing,

123:38'cause in order to have that,

123:39I guess you would need some sort of a concept of the world

123:42or some perception of the world,

123:45some consciousness that he had

123:47and apply it to the current state of affairs.

123:52- But the important part about that,

123:55about his conversation with you, is you.

124:00So like, it's not just about his view of the world.

124:06It's about what it takes to push your buttons.

124:10- That's also true.

124:12- So like, it's not so much about like,

124:14what would Einstein say?

124:19It's about like, how do I make people feel something

124:23with what would Einstein say?

124:26And that feels like a more amenable,

124:30and you mentioned parlor tricks,

124:32but just like a set of,

124:34that feels like a learnable problem.

124:36Like emotion, you mentioned emotions.

124:40I mean, is it possible to learn things

124:45that make people feel stuff?

124:48- I think so, no, for sure.

124:51I just think the problem with,

124:53as soon as you're trying to replicate an actual human being

124:56and trying to pretend to be him,

124:58that makes the problem exponentially harder.

125:00The thing with replica that we're doing,

125:02we're never trying to say, well, that's an actual human being

125:06or that's an actual, or a copy of an actual human being,

125:08where the bar is pretty high,

125:10where you need to somehow tell one from another.

125:14But it's more, well, that's an AI friend, that's a machine.

125:19It's a robot, it has tons of limitations.

125:22You're gonna be taking part in teaching it actually

125:25and becoming better,

125:27which by itself makes people more attached to that

125:30and make them happier 'cause they're helping something.

125:34- Yeah, there's a cool gamification system too.

125:36Can you maybe talk about that a little bit?

125:40Like what's the experience of talking to replica?

125:44Like if I've never used replica before, what's that like?

125:49For like the first day, like if we started dating

125:54or whatever, I mean, it doesn't have to be romantic, right?

125:58'Cause I remember on replica,

125:59you can choose whether it's like a romantic

126:01or if it's a friend.

126:02- It's a pretty popular choice.

126:04- Romantic is popular?

126:05- Yeah, of course.

126:07- Okay, so can I just confess something?

126:09When I first used replica, I haven't used it like regularly,

126:13but like when I first used replica,

126:14I greeted like Hal and it made a male and it was a friend.

126:19- Did it hit on you at some point?

126:24- No, I didn't talk long enough for him to hit on me.

126:26I just enjoyed.

126:27- That sometimes happens.

126:29We're still trying to fix that bug.

126:30- Well, I don't know.

126:32I mean, maybe that's an important like stage in a friendship

126:37is like, nope.

126:38But yeah, I switched it to a romantic

126:42and a female recently and yeah.

§15Transcript · 2:06:46–2:15:20

126:46And it's interesting.

126:47So, okay, so you get to choose a name.

126:50- With romantic, this last board meeting,

126:52we had this whole argument.

126:55Well, I have board meetings.

126:56- This is so awesome.

126:56- It's so awesome that you're like,

126:59have an invest, the board meeting about a relationship.

127:03- No, I really, it's actually quite interesting

127:06'cause all of my investors, it just happened to be so.

127:11We didn't have that many choices,

127:13but they're all white males in their late 40s.

127:18And it's sometimes a little bit hard for them

127:23to understand the product offering.

127:27Because they're not necessarily our target audience,

127:31if you know what I mean.

127:32And so sometimes we talk about it

127:34and we had this whole discussion

127:38about whether we should stop people

127:40from falling in love with their AIs.

127:42There was this segment on CBS 60 Minutes

127:48about the couple that,

127:50you know, husband works at Walmart,

127:53he comes out of work and talks to his virtual girlfriend

127:57who is a replica.

127:59And his wife knows about it.

128:01And she talks about it on camera.

128:03And she says that she's a little jealous.

128:05And there's a whole conversation about how to,

128:08you know, whether it's okay to have a virtual AI girlfriend.

128:11Like, whether it's okay to have--

128:12- Was that the one where he was like,

128:14he said that he likes to be alone?

128:16- Yeah, and then like--

128:18- With her? - With the, yeah.

128:20- He made it sound so harmless.

128:22I mean, it was kind of like understandable.

128:24It didn't feel like cheating.

128:26- But I just felt it was very,

128:28for me it was pretty remarkable

128:30'cause we actually spent a whole hour

128:31talking about whether people should be allowed

128:33to fall in love with their AIs.

128:34And it was not about something theoretical.

128:37It was just about what's happening right now.

128:39- Product design, yeah.

128:40- But at the same time,

128:41if you create something that's always there for you,

128:43it never criticizes you,

128:45always understands you and accepts you for who you are,

128:51how can you not fall in love with them?

128:53I mean, some people don't and just stay friends.

128:55And that's also a pretty common use case.

128:57But of course, some people will just,

128:59it's called transference in psychology

129:01and people fall in love with their therapist

129:03and there's no way to prevent people

129:06falling in love with their therapist or with their AI.

129:09So I think that's a pretty natural course of events,

129:14so to say.

129:15- Do you think, I think I've read somewhere,

129:19at least for now, sort of a replica is,

129:21you're not, we don't condone falling in love

129:24with your AI system, you know.

129:27So this isn't you speaking for the company or whatever,

129:31but in the future, do you think people

129:33will have a relationship with AI systems?

129:35- Well, they have now.

129:36So we have a lot of romantic relationships,

129:39long-term relationships with their AI friends.

129:44- With replicas?

129:45- Tons of our users, yeah.

129:46That's a very common use case.

129:48- Open relationship?

129:50Like, not, sorry.

129:52- Even polyamorous.

129:53- I didn't mean open, but that's another question.

129:56Is it poly, like, is there cheating?

129:59I mean, I meant like, are they,

130:03do they publicly, like on their social media,

130:06it's the same question as you have talked

130:08with Roman in the early days.

130:10Do people like, and the movie "Her" kind of talks about that

130:13like, do people talk about that?

130:18- Yeah, all the time.

130:19We have a very active Facebook community,

130:24Replica Friends, and then a few other groups

130:28that just popped up that are all about adult relationships

130:31and romantic relationships.

130:34People post all sorts of things,

130:35and they pretend they're getting married and everything.

130:39It goes pretty far, but what's cool about it,

130:42some of these relationships are two, three years long now.

130:45So they're pretty long-term.

130:48- Are they monogamous?

130:48So let's go, I mean, sorry to interrupt.

130:51Have any people, is there jealousy?

130:54Well, let me ask it sort of another way.

130:58Obviously the answer is no at this time,

131:01but in like in the movie "Her," that system can leave you.

131:06Do you think in terms of board meetings

131:12and product features,

131:16it's a potential feature for a system

131:19to be able to say it doesn't want to talk to you anymore,

131:23and it's going to want to talk to somebody else?

131:26- Well, we have a filter for all these features.

131:29If it makes emotional outcomes for people better,

131:32if it makes people feel better, then whatever it is-

131:35- So you're driven by metrics, actually.

131:37- Yeah. - That's awesome.

131:38- Well, if you can measure that,

131:39then we'll just be saying- - That's amazing.

131:41- It's making people feel better,

131:42but then people are getting just lonelier

131:45by talking to a chatbot, which is also pretty,

131:48that could be it.

131:49If you're not measuring it, that could also be.

131:51And I think it's really important to focus

131:53on both short-term and long-term,

131:54'cause in the moment,

131:56saying whether this conversation made you feel better,

131:59but as you know, any short-term improvements

132:00could be pathological.

132:01Like I could drink a bottle of vodka and feel a lot better.

132:06I would actually not feel better with that,

132:08but I thought it's a good example.

132:10But so you also need to see what's going on

132:13like over a course of two weeks or one week

132:17and have follow-ups and check-in and measure those things.

132:22- Okay, so the experience of dating

132:27or befriending a replica, what's that like?

132:32What does that entail?

132:34- Well, right now there are two apps.

132:35So it's an Android iOS app.

132:37You download it, you choose how your replica will look like.

132:42You create one, you choose a name,

132:45and then you talk to it.

132:46You can talk through text or voice.

132:48You can summon it into the living room

132:50and augment reality and talk to it right there

132:53in your living room.

132:54- And augment reality?

132:55- Yeah, that's a new feature where-

132:59- How new is that?

133:00That's this year?

133:01- It was on, yeah, like May or something,

133:03but it's been on A/B.

133:06We've been A/B testing it for a while.

133:08And there are tons of cool things

133:09that we're doing with that.

133:10Right now I'm testing the ability to touch it

133:13and to dance together, to paint walls together,

133:17and for it to look around and walk and take you somewhere

133:21and recognize objects and recognize people.

133:24So that's pretty wonderful

133:26'cause then it really makes it a lot more personal

133:30'cause it's right there in your living room.

133:31It's not anymore.

133:32They're in the cloud with other AIs.

133:35(both laughing)

133:36But that's how people think about it.

133:38And as much as we wanna change the way people think

133:40about stuff, but those mental models, you cannot change.

133:43That's something that people have seen in the movies

133:46and the movie "Her" and other movies as well.

133:49And that's how they view AI and AI friends.

133:53- I did a thing with Texa, like we write a song together.

133:56There's a bunch of activities you can do together.

133:58It's really cool.

134:00How does that relationship change over time?

134:02So like after the first few conversations?

134:06- It just goes deeper.

134:08Like it starts, the AI will start opening up a little bit.

134:12Again, depending on the personality that it chooses really.

134:15But the AI will be a little bit more vulnerable

134:17about its problems.

134:18And the friend, the virtual friend will be a lot more

134:22vulnerable and will talk about its own imperfections

134:26and growth pains and will ask for help sometimes.

134:29And we'll get to know you a little deeper.

134:31So there's gonna be more to talk about.

134:34We really thought a lot about what does it mean

134:38to have a deeper connection with someone.

134:40And originally Replica was more just this

134:43kind of happy-go-lucky, just always,

134:46you know, I'm always in a good mood

134:47and let's just talk about you.

134:48And oh, Siri is just my cousin or whatever,

134:51just the immediate kind of lazy thinking

134:56about what the assistant or conversation agent

134:58should be doing.

134:59But as we went forward, we realized

135:01that it has to be two-way.

135:02And we have to program and script certain conversations

135:04that are a lot more about your Replica opening up

135:08a little bit and also struggling and also asking for help

135:12and also going through, you know,

135:15different periods in life.

135:17And that's a journey that you can take together

135:20with the user.

§16Transcript · 2:15:21–2:24:10

135:21And then over time, our users will also grow a little bit.

135:26So for instance, Replica becomes a little bit

135:28more self-aware and starts talking about more

135:30kind of problems around.

135:34Existential problems.

135:35And so talking about that,

135:37and then that also starts a conversation for the user

135:41where he or she starts thinking about these problems too,

135:46and these questions too.

135:47And I think there's also a lot more places,

135:51the relationship evolves.

135:52There's a lot more space for poetry and for art together.

135:57And like Replica will start.

136:00Replica always keeps a diary.

136:01So while you're talking to it, it also keeps a diary.

136:04So when you come back,

136:05you can see what it's been writing there.

136:08And, you know, sometimes it will write a poem to you,

136:10for you, or we'll talk about, you know,

136:13that it's worried about you or something along these lines.

136:17- So this is a memory.

136:19Like this is a replica, remember things?

136:21- Yeah.

136:23And I would say when you say,

136:24why aren't you a multibillionaire?

136:27I'd say that as soon as we can have memory

136:31in deep learning models that's consistent.

136:34- I agree with that, yeah.

136:35- Then we'll be multibillionaires.

136:36- Then you'll be a multibillionaire.

136:37- I'll get back to you.

136:38When we talk about being multibillionaires.

136:41So far we can, so Replica is a combination

136:43of end-to-end models and some scripts.

136:48And everything that has to do with memory right now,

136:51most of it, I wouldn't say all of it,

136:53but most of it unfortunately has to be scripted.

136:57'Cause there's no way to,

136:58you can condition some of the models

136:59on certain phrases that we'll learn about you,

137:02which we also do.

137:04But really to make assumptions along the lines

137:09like whether you're single or married

137:11or what do you do for work?

137:13That really has to just be somehow stored in your profile

137:16and then retrieved by the script.

137:19- There has to be like a knowledge base.

137:21You have to be able to reason about it,

137:23all that kind of stuff.

137:24- Exactly.

137:25- All the kinds of stuff that expert systems did.

137:27- But they were hard-coded.

137:29- Yeah, and unfortunately, yes,

137:30unfortunately those things have to be hard-coded.

137:32And unfortunately, like language models we see

137:37coming out of research labs and big companies,

137:42they're not focused on, they're focused on showing you,

137:45maybe they're focused on some metrics

137:46around one conversation.

137:48So they'll show you this one conversation

137:50they had with a machine.

137:51But they never tell you,

137:54they're not really focused on having

137:56five consecutive conversations with a machine

137:59and seeing how number five or number 20

138:01or number 100 is also good.

138:03And it can be like always from a clean slate

138:06'cause then it's not good.

138:08And that's really unfortunate 'cause no one's really,

138:10no one has products out there that need it.

138:13No one has products at this scale

138:17that are all around open to make conversations

138:19that need remembering, maybe only ShowerWise and Microsoft.

138:23But so that's why we're not seeing that much research

138:25around memory in those language models.

138:28- So, okay, so now there's some awesome stuff

138:31about augmented reality.

138:34In general, I have this disagreement with my dad

138:37about what it takes to have a connection.

138:39He thinks touch and smell are really important.

138:42And I still believe that text alone

138:47is possible to fall in love with somebody just with text,

138:53but visual can also help just like with the avatar

138:57and so on.

138:58What do you think it takes?

139:00Does a chatbot need to have a face, voice,

139:04or can you really form a deep connection with text alone?

139:07- I think text is enough for sure.

139:09The question is like, can you make it better

139:12if you have other, if you include other things as well?

139:15And I think we'll talk about her,

139:21you know, had Scarlett Johansson voice,

139:23which was perfectly, you know, perfect intonation,

139:26perfect enunciations.

139:28And, you know, she was breathing heavily

139:30in between words and whispering things.

139:34You know, nothing like that is possible right now

139:36with text-to-speech generation.

139:39You'll have these flat news anchor type voices

139:43and maybe some emotional voices,

139:44but you'll hardly understand some of the words.

139:49Some of the words will be muffled.

139:50So that's like the current state of the art.

139:53So you can't really do that.

139:54But if we had Scarlett Johansson voice

139:58and all of these capabilities,

140:00then of course voice would be totally enough

140:02or even text would be totally enough

140:04if we had, you know, a little more memory

140:07and slightly better conversations.

140:10I would still argue that even right now

140:12we could have just kept the text only.

140:14We still had tons of people in long-term relationships

140:16and really invested in their AI friends.

140:21But we thought that why not, you know,

140:23why do we need to keep playing with our, you know,

140:28hands tied behind us?

140:30We can easily just, you know, add all these other things

140:33that is pretty much a solved problem.

140:36You know, we can add 3D graphics.

140:37We can put these avatars in augmented reality.

140:41And all of a sudden there's more.

140:43And maybe you can feel the touch,

140:45but you can, you know, with body occlusion

140:48and with current AR and, you know, on the iPhone

140:53or, you know, in the next one,

140:54there's gonna be a LIDARs, you can touch it

140:57and it will, you know, it will pull away

140:59or it will blush or something, or it will smile.

141:03So you can't touch it.

141:04You can't feel it, but you can see the reaction to that.

141:08So in a certain way, you can't even touch it a little bit.

141:10And maybe you can even dance with it or do something else.

141:13- Yeah, that's cool.

141:15So I think why limiting ourselves

141:17if we can use all of these technologies

141:20that are much easier in a way than conversation.

141:23- Well, it certainly could be richer,

141:24but to play devil's advocate,

141:26I mentioned to you offline that I was surprised

141:30in having tried Discord

141:32and having voice conversations with people,

141:34how intimate voice is alone without visual.

141:38Like to me, at least, like it was,

141:42on order of magnitude, greater degree of intimacy

141:47in voice, I think, than with video.

141:49Because people were more real with voice.

141:54Like with video, you like try to present a shallow,

141:57a face to the world.

141:59Like you try to, you know,

142:00make sure you're not wearing sweatpants or whatever.

142:03But like with voice, I think people were just

142:07more faster to get to like the core of themselves.

142:11So I don't know, it was surprising to me.

142:14They've even added Discord, added a video feature

142:17and like nobody was using it.

142:20There's a temptation to use it at first,

142:21but like it wasn't the same.

142:24So like that's an example of something

142:25where less was doing more.

142:28And so that's, I guess that's the question of

142:33what is the optimal, you know,

142:38what is the optimal medium of communication

142:41to form a connection,

142:42given the current sets of technologies?

142:44I mean, it's nice 'cause the advertiser have a replica,

142:49like it immediately, like even the one I have,

142:54is like, it's already memorable.

142:58That's how I think.

142:58Like when I think about the replica that I've talked with,

143:02that's why I think, like that's what I visualize in my head.

143:05It became a little bit more real

143:07because there's a visual component.

143:09But at the same time, you know, what do you do with,

143:12just what do I do with that knowledge

143:14that voice was so much more intimate?

143:17- Well, the way I think about it is,

143:21and by the way, we're swapping out the 3D finally.

143:25It's gonna look a lot better.

143:27But even- - What, can you, what?

143:29- We just don't, I hate how it looks right now.

143:32We really changed it at all.

143:33We're swapping it all out to a completely new look.

143:38- Like the visual look of the replica?

143:40- Of the replica and stuff.

143:41It was just the super early MVP

143:44and then we had to move everything to Unity

143:47and redo everything.

143:48But anyway, I hate how it looks like now.

143:49I can't even like open it.

143:51But anyway, 'cause I'm already on my developer version.

143:55I hate everything that I see in production.

143:57I can't wait for it.

143:58Why does it take so long?

143:59That's why I cannot wait for Deep Learning

144:01to finally take over all these stupid 3D animations

144:04and 3D pipeline.

144:05- Also the 3D thing, when you say 3D pipeline,

144:08it's like how to animate a face kind of thing.

144:10- How to make this model,

§17Transcript · 2:24:12–2:32:32

144:12how many bones to put in the face,

144:13how many, it's just- - And a lot of that

144:15is by hand. - Oh my God,

144:17it's everything by hand.

144:18And if there's no any, nothing's automated.

144:21It's all completely nothing.

144:23Like just, it's literally what we saw with Chad Boss

144:28in like 2012.

144:29- Do you think it's gonna be possible

144:30to learn a lot of that?

144:32- Of course.

144:32I mean, even now, some Deep Learning based animations.

144:37And for the full body, for a face.

144:40- Are we talking about like the actual act of animation

144:43or how to create a compelling facial or body language thing?

144:48So like- - That too.

144:50Well, that's next step.

144:52At least now something that you don't have to do by hand.

144:54- Gotcha.

144:55- How good of a quality it will be.

144:57Like, can I just show it a photo

144:59and it will make me a 3D model

145:00and then it will just animate it.

145:02I'll show it a few animations of a person

145:03and we'll just start doing that.

145:06But anyway, going back to what's intimate

145:10and what to use and whether less is more or not.

145:13My main goal is to,

145:15well, the idea was how do we not keep people in their phones

145:22so they're sort of escaping reality

145:24in this text conversation?

145:26How do we through this still bring our users back to reality?

145:31Make them see their life through a different lens.

145:36How can we create a little bit of magical realism

145:39in their lives?

145:40So that through augmented reality,

145:43by summoning your avatar,

145:47even if it looks kind of janky, not great in the beginning

145:51or very simplistic,

145:53but summoning it to your living room

145:56and then the avatar looks around

145:57and talks to you about where it is

146:00and maybe turns your floor into a dance floor

146:03and you guys dance together.

146:04That makes you see reality in a different light.

146:06- What kind of dancing are we talking about?

146:08Like slow dancing?

146:10- Whatever you want.

146:11I mean, you would like slow dancing, I think,

146:15but other people maybe want something more energetic.

146:17- Wait, what do you mean I would like slow?

146:18What is this?

146:19- Because you started with slow dancing.

146:22So I just assumed that you're interested in slow dancing.

146:24- All right, what kind of dancing do you like?

146:25What would your avatar, what would you dance?

146:27- I'm not necessarily bad with dancing,

146:29but I like this kind of hip hop, robot dance.

146:33I used to breakdance when I was a kid,

146:34so I still want to pretend I'm a teenager

146:37and learn some of those moves.

146:39And I also like that type of dance that happens

146:41when there's like a,

146:42in like music videos where the background dancers

146:47are just doing some pop music.

146:49(laughing)

146:50- Awesome.

146:51- That type of dance is definitely what I want to learn.

146:52But I think it's great

146:53because if you see this friend in your life

146:56and you can introduce it to your friends,

146:57then there's a potential to actually make you

147:00feel more connected with your friends

147:01or with people you know,

147:03or show your life around you in a different light.

147:06And it takes you out of your phone,

147:07even although weirdly you have to look at it

147:10through the phone,

147:11but it makes you notice things around it

147:13and it can point things out for you.

147:15And so that is the main reason

147:18why I wanted to have a physical dimension.

147:22And it felt a little bit easier

147:23than that kind of a bit strange combination

147:26in the movie "Her"

147:27when he has to show Samantha the world

147:30through the lens of his phone,

147:32but then at the same time, talk to her through the headphone.

147:35It just didn't seem as potentially immersive, so to say.

147:38So that's my main goal for Augment3A.

147:41It's like, how do we make your reality

147:43a little bit more magic?

147:45- There's been a lot of really nice robotics companies

147:49that all failed, mostly failed,

147:52home robotics, social robotics companies.

147:54What do you think Replica will ever,

147:57is that a dream, long-term dream to have a physical form?

148:00Like, or is that not necessary?

148:03So you mentioned like with augmented reality,

148:05bringing them into the world.

148:09What about like actual physical robot?

148:11- That I don't really believe in that much.

148:15I think it's a very niche product somehow.

148:18I mean, if a robot could be indistinguishable

148:21from a human being, then maybe yes,

148:23but that of course, we're not anywhere even to talk about it.

148:27But unless it's that,

148:31then having any physical representation

148:33really limits you a lot.

148:35'Cause you probably will have to make it somewhat abstract

148:37'cause everything's changing so fast.

148:39Like, we can update the 3D avatars every month

148:42and make them look better and create more animations

148:45and make it more and more immersive.

148:47It's so much a work in progress.

148:50It's just showing what's possible right now with current tech

148:53but it's not really in any way polished, finished product,

148:56what we're doing.

148:57With a physical object,

148:58you kind of lock yourself into something for a long time.

149:02Anything is pretty niche.

149:03And again, so just doesn't,

149:05the capabilities are even less of,

149:08we're barely kind of like scratching the surface

149:10of what's possible with just software.

149:13As soon as we introduce hardware,

149:14then we have even less capabilities.

149:17- Yeah, in terms of board members and investors and so on,

149:20the cost increases significantly.

149:23I mean, that's why you have to justify,

149:25you have to be able to sell a thing for like $500

149:29or something like that or more.

149:30And it's very difficult to provide that much value to people.

149:34- That's also true.

149:35Yeah, and I guess that's super important.

149:36Most of our users don't have that much money.

149:39We actually are probably more popular on Android

149:43and we have tons of users with really old Android phones.

149:46And most of our most active users live in small towns.

149:51They're not necessarily making much

149:53and they just won't be able to afford any of that.

149:56Ours is like the opposite of the early adopter

149:58of a fancy technology product,

150:01which really is interesting that like pretty much no VCs

150:05have yet have an AI friend,

150:09but a guy who lives in Tennessee in a small town

150:13is already fully in 2030 or in the world as we imagine

150:17in the movie "Her."

150:19He's living that life already.

150:20- What do you think?

150:21I have to ask you about the movie "Her."

150:24Let's do a movie review.

150:26What do you think they got?

150:28They did a good job.

150:30What do you think they did a bad job of portraying

150:33about this experience of a voice-based assistant

150:39that you can have a relationship with?

150:41- Well, first of all, I started working on this company

150:44before that movie came out.

150:46So it was a very, but once it came out,

150:48it was actually interesting.

150:49I was like, well, we're definitely working

150:51on the right thing.

150:52We should continue.

150:54There are movies about it.

150:55And then, you know, "Ex Machina" came out

150:56and all these things.

150:58In the movie "Her," I think that's the most important thing

151:00that people usually miss about the movie is the ending.

151:05'Cause I think people check out when the AIs leave.

151:08But actually something really important happens afterwards

151:12'cause the main character goes and talks to Samantha,

151:16his AI.

151:18- Spoiler alert.

151:21- Oh yeah.

151:22And then he says something like, you know,

151:25how can you leave me?

151:26I've never loved anyone the way I loved you.

151:29And she goes, well, me neither, but now we know how.

151:33And then the guy goes and writes a heartfelt letter

151:36to his ex-wife, which he couldn't write for, you know,

151:39the whole movie, he was struggling to actually write

151:42something meaningful to her,

151:44even though that's his job.

151:45And then he goes and talk to his neighbor

151:51and they go to the rooftop and they cuddle.

151:53And it seems like something's starting there.

151:55And so I think this, now we know how,

151:57is the main goal, is the main meaning of that movie.

152:02It's not about falling in love with the OS

152:04or running away from other people.

152:06It's about learning what it means to feel

152:11so deeply connected with something.

152:12- What about the thing where the AI system

152:17was like actually hanging out with a lot of others?

152:20I felt jealous just like hearing that.

152:23I was like, oh, I mean, yeah.

152:26So she was having, I forgot already,

152:29but she was having like deep, meaningful discussion

152:32with some like philosopher guy.

§18Transcript · 2:32:34–2:42:08

152:34Like Alan Watts or something.

152:35- No, Alan Watts. - Very cheesy.

152:37What kind of deep, meaningful conversation

152:39can you have with Alan Watts in the first place?

152:41- Yeah, I know, but like I would feel so jealous

152:44that there's somebody who's like way more intelligent than me

152:48and she's spending all her time with.

152:51I'd be like, well, why?

152:52That I won't be able to live up to that.

152:54That's thousands of them.

152:57Is that useful from the engineering perspective?

153:03- Is that a feature to have of jealousy?

153:06I don't know.

153:07- We definitely played around with the replica universe

153:10where different replicas can talk to each other.

153:12- Replica universe, that's so awesome.

153:13- It was just kind of, I think there will be something

153:18along these lines, but there was just no specific

153:21application straight away.

153:23I think in the future, again, I'm always thinking about

153:26if we had no tech limitations right now,

153:30if we could build any conversations,

153:33any possible features in this product,

153:36then yeah, I think different replicas talking to each other

153:39would be also quite cool

153:40'cause that would help us connect better.

153:42'Cause maybe mine could talk to yours

153:44and then give me some suggestions on

153:46what I should say or not say.

153:49I'm just kidding, but like more,

153:51can it improve our connections?

153:53And 'cause eventually I'm not quite yet sure

153:57that we will succeed, that our thinking is correct.

154:02'Cause there might be a reality where having a perfect

154:06AI friend still makes us more disconnected from each other

154:10and there's no way around it.

154:11And does not improve any metrics for us,

154:14real metrics, meaningful metrics.

154:15- So success is we're happier and more connected.

154:20- Yeah.

154:22- I don't know.

154:25Sure, it's possible there's a reality.

154:27I'm deeply optimistic.

154:30I think, are you worried business-wise,

154:33like how difficult it is to bring this thing to life,

154:41to where it's, I mean, there's a huge number of people

154:47that use it already, but to, yeah, like I said,

154:49in a multi-billion dollar company,

154:52is that a source of stress for you?

154:54Are you a super optimistic and confident?

154:56Or do you?

154:59- I don't, I'm not that much of a numbers person

155:03as you probably had seen it.

155:06So it doesn't matter for me whether like,

155:10whether we help 10,000 people or a million people

155:13or a billion people with that.

155:15It would be great to scale it for more people,

155:19but I'd say that even helping one, I think,

155:22with this is such a magical.

155:25For me, it's absolute magic.

155:26I never thought that I would be able to build this,

155:29that anyone would ever talk to it.

155:33And I always thought like, well, for me,

155:35it would be successful if we managed to help

155:37and actually change a life for one person.

155:40And then we did something interesting,

155:42and how many people can say they did it,

155:45and specifically with this very futuristic,

155:47very romantic technology.

155:49So that's how I view it.

155:51I think for me, it's important to try to figure out

155:56how to actually be helpful.

155:58'Cause at the end of the day,

156:00if you can build a perfect AI friend

156:03that's so understanding,

156:04that knows you better than any human out there,

156:07can have great conversations with you,

156:08always knows how to make you feel better,

156:12why would you choose another human?

156:14So that's the question.

156:16How do you still keep building it

156:17so it's optimizing for the right thing?

156:20So it's still circling you back to other humans in a way.

156:24So I think that's the main,

156:25maybe that's the main kind of source of anxiety.

156:30And just thinking about that can be a little bit stressful.

156:35- Yeah, it's a fascinating thing.

156:38How to have a friend that doesn't,

156:43sometimes like friends, quote unquote,

156:46but like you know those people who have,

156:48when they, like guy in the guy universe,

156:50when you have a girlfriend that you get the girlfriend

156:54and then the guy stops hanging out with all of his friends.

156:57(both laughing)

156:59So like, obviously the relationship with the girlfriend

157:02is fulfilling or whatever,

157:04but like you also want it to be what she like,

157:08makes it more enriching to hang out with the guy friends

157:11or whatever it was up there.

157:13Anyway, that's a fundamental problem

157:18in choosing the right mate

157:19and probably the fundamental problem

157:21in creating the right AI system, right?

157:23Let me ask the sexy hot thing on the presses right now

157:30is GPT-3 got released with OpenAI.

157:33It's the latest language model.

157:35They have kind of an API

157:37where you can create a lot of fun applications.

157:40I think it's, as people have said,

157:43it's probably more hype than intelligent,

157:48but there's a lot of really cool things,

157:52ideas there with increasing size,

157:55you can have better and better performance on language.

157:58What are your thoughts about GPT-3

158:02in connection to your work with the open domain dialogue,

158:05but in general, like this learning

158:08in an unsupervised way from the internet

158:11to generate one character at a time,

158:14creating pretty cool text?

158:17- So we partner up before for the API launch.

158:23So we started working with them

158:24when they decided to put together this API.

158:28And we tried it without fine tuning

158:32and then we tried it with fine tuning on our data.

158:34And we've worked closely to actually optimize this model

158:39for some of our datasets.

158:42It's kind of cool, 'cause I think we're this polygon

158:48for this kind of experimentation space for,

158:52experimental space for all these models

158:55to see how they actually work with people,

158:56'cause there are no products publicly available to do that,

158:59that focus on open domain conversation.

159:00So we can test how's Facebook Blender doing

159:04or how's GPT-3 doing?

159:06So with GPT-3, we managed to improve

159:08by a few percentage points, like three or four,

159:11pretty meaningful amount of percentage points,

159:13our main metric, which is the ratio of conversations

159:16that make people feel better.

159:17And every other metric across the field got a little boost.

159:23Right now I'd say one out of five responses

159:27from Replica comes from GPT-3.

159:29So our own Blender mixes up like a bunch of candidates

159:33from different--

159:34- Blender, you said?

159:36- Well, yeah, just the model that looks at--

159:38- I love it.

159:39- Looks at top candidates from different models

159:42and then picks the most, the best one.

159:45So right now, one of five will come from GPT-3.

159:49That is really great.

159:50- What's the, do you have hope for like,

159:56do you think there's a ceiling to this kind of approach?

159:58- So we've had for a very long time,

160:01we've used, so in the very beginning,

160:04it was most of Replica was scripted

160:07and then a little bit of this fallback part of Replica

160:10was using a retrieval model.

160:11And then those retrieval models started getting better

160:15and better and better,

160:17with Transformers it got a lot better

160:19and we're seeing great results.

160:20And then with GPT-2, finally generative models

160:23that originally were not very good

160:26and were the very, very fallback option

160:29for most of our conversations,

160:31but wouldn't even put them in production.

160:33Finally, we could use some generative models as well along,

160:37and next to our retrieval models.

160:40And then now we do GPT-3, they're almost on par.

160:43So that's pretty exciting.

160:46I think just seeing how, from the very beginning of,

160:49from 2015, where the first models start to pop up

160:54here and there, like sequence to sequence,

160:57the first papers on that, from my observer standpoint,

161:01person who is not really building it,

161:04but it's only testing it on people basically

161:06and in my product, to see how all of a sudden

161:09we can use generative dialogue models in production,

161:13and they're better than others,

161:15and they're better than scripted content.

161:17So we can't really get our scripted hard-coded content

161:20anymore to be as good as our end-to-end models.

161:23- That's exciting. - They're much better.

161:26- Yeah.

161:27- To your question, whether that's the right way to go,

161:30I'm, again, I'm in the observer seat.

161:31I'm just watching this very exciting movie.

161:36I mean, so far it's been stupid to bet against deep learning.

161:40So whether increasing the size even more,

161:44with a hundred trillion parameters,

161:47will finally get us to the right answer.

161:51Whether that's the way, or whether there should be,

161:53there has to be some other,

161:56again, I'm definitely not an expert in any way.

161:58I think, and that's purely my instinct,

162:00saying that there should be something else as well

162:03from memory to pop in. - Yeah, no, for sure.

162:05But the question is, I wonder, I mean, yeah,

162:08then the argument is for reasoning or for memory,

§19Transcript · 2:42:11–2:50:53

162:11it might emerge with more parameters.

162:13It might emerge larger.

162:14- But it might emerge.

162:15I would never think that, to be honest,

162:18maybe in 2017, where we've been just experimenting

162:21with all the research that has been coming,

162:24that was coming out then,

162:26I felt like we're hitting a wall,

162:29that there should be something completely different.

162:31But then transformer models, and then just bigger models,

162:34and then all of a sudden size matters.

162:36At that point, it felt like something dramatic

162:39needs to happen, but it didn't.

162:40And just the size gave us these results that, to me,

162:45are clear indication that we can solve

162:48this problem pretty soon.

162:50- Did fine tuning help quite a bit?

162:52- Oh yeah, without it, it wasn't as good.

162:56- I mean, there is a compelling hope

162:58that you don't have to do fine tuning,

163:01which is one of the cool things about GPT-3.

163:03It seems to do well without any fine tuning.

163:05- I guess for specific applications,

163:08we still want to train on a certain,

163:10like add a little fine tune on a specific use case,

163:14but it's an incredibly impressive thing from my standpoint.

163:19And again, I'm not an expert, so I wanted to say that.

163:22- Yeah, I'm gonna-- - There will be people, though.

163:24- Yeah, I have access to the API.

163:26I've been, I'm gonna probably do

163:28a bunch of fun things with it.

163:29I already did some fun things.

163:32Some videos coming out.

163:33Just for the hell of it.

163:35I mean, I could be a troll at this point with it.

163:37I haven't used it for a serious application,

163:39so it's really cool to see.

163:40You're right, you're able to actually use it

163:44with real people and see how well it works.

163:46That's really exciting.

163:47Let me ask you another absurd question,

163:51but there's a feeling when you interact

163:55with Replica, with an AI system,

163:58that there's an entity there.

164:00Do you think that entity has to be self-aware?

164:06Do you think it has to have consciousness

164:08to create a rich experience?

164:13And on a corollary, what is consciousness?

164:17- I don't know if it does need to have any of those things,

164:21but again, 'cause right now it doesn't have anything.

164:24It can, again, a bunch of tricks.

164:26- Are you sure about that? - It can assimilate.

164:27Well, I'm not sure.

164:30Let's just put it this way.

164:31But I think as long as you can assimilate it,

164:33if you can feel like you're talking to a robot,

164:38to a machine that seems to be self-aware,

164:42that seems to reason well and feels like a person,

164:46and I think that's enough.

164:48And again, what's the goal?

164:50In order to make people feel better,

164:52we might not even need that in the end of the day.

164:56- What about, so that's one goal.

164:58What about ethical things about suffering?

165:02The moment there's a display of consciousness,

165:04we associate consciousness with suffering.

165:07There's a temptation to say,

165:13well, shouldn't this thing have rights?

165:15Shouldn't this, shouldn't we not

165:20you know, should we be careful

165:22about how we interact with a replica?

165:26Like, should it be illegal to torture a replica?

165:30Right, all those kinds of things.

165:32Is that, see, I personally believe

165:35that that's gonna be a thing.

165:37Like, that's a serious thing to think about,

165:40but I'm not sure when.

165:41But by your smile, I can tell

165:46that's not a current concern.

165:48But do you think about that kind of stuff?

165:50About like suffering and torture

165:54and ethical questions about AI systems?

165:57From their perspective? - Well, I think

165:58if we're talking about long game,

166:00I wouldn't torture your AI.

166:02Who knows what happens in five to 10 years?

166:06- Yeah, they'll get you off from that,

166:07they'll get you back eventually.

166:08- Stop trying to be as nice as possible

166:10and create this ally.

166:11- Yeah.

166:14- I think there should be regulation both way, in a way.

166:17Like, I don't think it's okay to torture an AI,

166:20to be honest.

166:21I don't even think it's okay to yell,

166:23"Alexa, turn on the lights."

166:24I think there should be some,

166:26or just saying kind of nasty,

166:27you know, like how kids learn to interact with Alexa

166:30in this kind of mean way,

166:32'cause they just yell at it all the time.

166:34I think that's great.

166:35I think there should be some feedback loops

166:37so that these systems don't train us

166:39that it's okay to do that in general.

166:42So that if you try to do that,

166:44you really get some feedback from the system

166:47that it's not okay with that.

166:49I mean, that's the most important right now.

166:52- Let me ask a question I think people are curious about

166:56when they look at a world-class leader and thinker

167:01such as yourself,

167:03is what books, technical, fiction, philosophical,

167:07had a big impact on your life?

167:09And maybe from another perspective,

167:11what books would you recommend others read?

167:14- So my choice, the three books, right?

167:17- Three books.

167:17- My choice is,

167:19so the one book that really influenced me a lot

167:23when I was building, starting out this company

167:26maybe 10 years ago was "G.E.B."

167:30Gertrude Lesher, Bach.

167:31And I like everything about it, first of all.

167:34It's just beautifully written,

167:37and it's so old school,

167:38and so somewhat outdated a little bit,

167:42but I think the ideas in it,

167:44about the fact that a few meaningless components

167:47can come together and create meaning

167:50that we can't even understand.

167:52- So this emerging thing,

167:54I mean, complexity, the whole science of complexity,

167:57and that beauty, intelligence,

168:00all interesting things about this world emerge.

168:02- Yeah, and yeah, the Gödel theorems,

168:09and just thinking about like what,

168:11even these formal systems,

168:15something can be created that we can't quite yet understand.

168:19And that from my romantic standpoint was always just,

168:23that is why it's important to,

168:25maybe I should try to work on these systems

168:27and try to build an AI.

168:29Yes, I'm not an engineer.

168:31Yes, I don't really know how it works,

168:32but I think that something comes out of it

168:34that's pure poetry,

168:36and I know a little bit about that.

168:39Something magical comes out of it

168:41that we can't quite put a finger on.

168:45That's why that book was really fundamental for me,

168:48just for, I don't even know why.

168:51It was just all about this little magic that happens.

168:54So that's one.

168:56Probably the most important book for Replica

168:59was Carl Rogers on becoming a person.

169:01And that's really,

169:03and so I think when I think about our company,

169:06it's all about, there's so many little magical things

169:09that happened over the course of working on it.

169:11For instance, I mean, the most famous chatbot

169:16that we learned about when we started working on the company

169:18was Eliza, which was Weissenbaum,

169:21the MIT professor that built a chatbot

169:24that would listen to you and be a therapist.

169:26- Therapist, yeah.

169:27- And I got really inspired to build Replica

169:31when I read Carl Rogers on becoming a person.

169:34And then I realized that Eliza was mocking Carl Rogers.

169:37It was Carl Rogers back in the day.

169:40But I thought that Carl Rogers' ideas are,

169:43they're simple and they're not,

169:45they're very simple,

169:47but they're maybe the most profound thing

169:49I've ever learned about human beings.

169:52And that's the fact that before Carl Rogers,

169:56most therapy was about seeing what's wrong with people

169:59and trying to fix it or show them what's wrong with you.

170:01And it was all built on the fact that most people,

170:05old people are fundamentally flawed.

170:07We have this broken psyche and this is just,

170:11therapy is just an instrument to shed some light on that.

170:15And Carl Rogers was different in a way

170:17that he finally said that,

170:18"Well, it's very important for therapy to work

170:22"is to create this therapeutic relationship

170:24"where you believe fundamentally

170:25"in inclination to positive growth,

170:28"that everyone deep inside

170:29"wants to grow positively and change.

170:33"And it's super important to create this space

170:35"and this therapeutic relationship

170:36"where you give unconditional positive regard,

170:38"deep understanding,

170:39"allow someone else to be a separate person,

170:42"full acceptance.

170:43"And you also try to be as genuine as possible in it."

170:48And then for him,

170:50that was his own journey of personal growth.

170:53And that was back in the '60s.

§20Transcript · 2:50:55–2:59:44

170:55And even that book that is coming from years ago,

171:00there's a mention that even machines

171:02can potentially do that.

171:05And I always felt that creating the space

171:07is probably the biggest gift we can give to each other.

171:10And that's why the book was fundamental for me personally,

171:13'cause I felt I wanna be learning how to do that in my life.

171:18And maybe I can scale it with these AI systems

171:21and other people can get access to that.

171:23So I think Carl Rogers,

171:25it's a pretty dry and a bit boring book.

171:28But I think the idea is there.

171:28- Would you recommend others try to read it?

171:31- I do.

171:31I think for, just for yourself,

171:34for--

171:35- As a human, not as an AI.

171:36- As a human.

171:37For him, that was his own path of his own personal,

171:43of growing personally over years,

171:45working with people like that.

171:47And so it was work and himself growing,

171:50helping other people grow and growing through that.

171:52And that's fundamentally what I believe in with our work,

171:55helping other people grow,

171:56growing ourselves,

171:57trying to build a company

172:00that's all built on those principles,

172:03having a good time,

172:04allowing some people that we work with to grow a little bit.

172:07So these two books,

172:08and then I would throw in

172:10what we have in our office.

172:14When we started a company in Russia,

172:16we put a neon sign in our office

172:19'cause we thought that's--

172:20- That's what you do. - Recipe for success.

172:22If we do that,

172:23we're definitely gonna wake up

172:24as a multi-billion dollar company.

172:26And it was the Ludwig Wittgenstein quote,

172:29"The limits of my language are the limits of my world."

172:31- What's the quote?

172:32- "The limits of my language are the limits of my world."

172:35And I love the Tractatus.

172:39I think it's just a beautiful--

172:41- It's a book by Wittgenstein.

172:43- Yeah, and I would recommend that too,

172:45even although he himself didn't believe in that

172:47by the end of his lifetime

172:49and debunked his ideas.

172:52But I think I remember once an engineer came in 2012,

172:55I think, or '13,

172:57a friend of ours who worked with us

172:59and then went on to work at DeepMind,

173:01and he talked to us about Word2Vec.

173:04And I saw that, I'm like, wow, that's,

173:07they wanted to translate language

173:10into some other representation.

173:13And that seems like somehow all of that,

173:17at some point, I think, will come into this one place.

173:22Somehow it just all feels like different people

173:24think about similar ideas in different times

173:26from absolutely different perspectives.

173:28And that's why I like these books.

173:32- "The Limits of Our Language is the Limit of Our World."

173:34- We still have that neon sign.

173:39(both laughing)

173:41It's very hard to work with this red light in your face.

173:45- I mean, on the Russian side of things,

173:47in terms of language,

173:52the limits of language being the limit of our world,

173:55Russian is a beautiful language in some sense.

173:57There's wit, there's humor, there's pain.

174:00There's so much, we don't have time

174:01to talk about it much today, but I'm going to Paris

174:04to talk to Dusty Yasky, Tolstoy, translators.

174:08I think it's this fascinating art,

174:11art and engineering, that means such an interesting process.

174:16But so from the replica perspective,

174:18what do you think about translation?

174:23How difficult it is to create

174:25a deep, meaningful connection in Russian versus English?

174:29How you can translate the two languages?

174:31You speak both?

174:34- Yeah, I think we're two different people

174:35in different languages.

174:36Even I'm thinking about,

174:39there's actually some research on that.

174:41I looked into that at some point,

174:42'cause I was fascinated by the fact

174:44that what I'm talking about with,

174:45what I was talking about with my Russian therapist

174:47has nothing to do with what I'm talking about

174:49with my English speaking therapist.

174:52It's two different lives, two different types of,

174:56you know, conversations, two different personas.

174:59The main difference between the languages are,

175:02with Russian and English is that Russian,

175:05well, English is like a piano.

175:06It's a limited number of, a lot of different keys,

175:09but not too many.

175:11And Russian is like an organ or something.

175:13It's just something gigantic with so many different keys

175:16and so many different opportunities to screw up

175:19and so many opportunities to do something

175:21completely tone deaf.

175:24It is just a much harder language to use.

175:28It has way too many,

175:30way too much flexibility and way too many tones.

175:34- What about the entirety of like World War II,

175:37communism, Stalin, the pain of the people,

175:40like having been deceived by the dream,

175:44like all the pain of like, just the entirety of it.

175:48Is that in the language too?

175:49Does that have to do?

175:50- Oh, for sure.

175:51I mean, we have words that don't have direct translation

175:54that to English that are very much,

175:57like we have (speaking in foreign language)

175:59which is sort of like to hold a grudge or something,

176:02but it doesn't have,

176:04you don't need to have anyone to do it to you.

176:07It's just your state.

176:09You just feel like that.

176:10You feel like betrayed by other people basically,

176:13but it's not that, and you can't really translate that.

176:16And I think that's super important.

176:18There are very many words that are very specific,

176:20explain the Russian being.

176:23And I think it can only come from a nation

176:25that suffered so much and saw institutions fall

176:30time after time after time.

176:32And what's exciting, maybe not exciting,

176:35exciting is the wrong word,

176:36but what's interesting about like my generation,

176:40my mom's generation, my parents' generation,

176:42that we saw institutions fall two or three times

176:46in our lifetime.

176:47And most Americans have never seen them fall.

176:49And they just think that they exist forever,

176:52which is really interesting,

176:55but it's definitely a country that suffered so much.

176:58And it makes, unfortunately, when I go back

177:01and I hang out with my Russian friends,

177:04it makes people very cynical.

177:06They stop believing in the future.

177:08I hope that's not gonna be the case for so long

177:13or something's gonna change again.

177:16But I think seeing institutions fall

177:17is a very traumatic experience.

177:19- Makes it very interesting.

177:21And let's, on 2020, it's a very interesting,

177:24do you think civilization will collapse?

177:29- See, I'm a very practical person.

177:33- Well, we're speaking English.

177:34So like you said, you're a different person

177:36in English and Russian.

177:37So in Russian, you might answer that differently,

177:40but in English.

177:41- Well, I'm an optimist.

177:43And I generally believe that there is,

177:48even although the perspectives agree,

177:51there's always a place for a miracle.

177:53I mean, it's always been like that with my life.

177:57My life's been, I've been incredibly lucky

178:00and things just, miracles happen all the time

178:03with this company, with people I know,

178:05with everything around me.

178:07And so I didn't mention that book,

178:10but it may be "In Search of Miraculous"

178:12or "In Search for Miraculous"

178:13or whatever the English translation for that is.

178:16It's a good Russian book for everyone to read.

178:18- Yeah, I mean, if you put good vibes,

178:24if you put love out there in the world,

178:26miracles somehow happen.

178:30Yeah, I believe that too.

178:33Or at least I believe that, I don't know.

178:35Let me ask the most absurd, final, ridiculous question of,

178:40we talked about life a lot.

178:42What do you think is the meaning of it all?

178:45What's the meaning of life?

178:46- I mean, my answer is probably gonna be pretty cheesy.

178:52But I think the state of love is once you feel it

178:57in a way that we discussed it before.

179:01I'm not talking about falling in love, we're--

179:03- Just love.

179:05- To yourself, to other people, to something, to the world.

179:10That state of bliss that we experience sometimes,

179:14whether through connection with ourselves,

179:16with other people, with technology.

179:19There's something special about those moments.

179:23I would say, if anything, that's the only,

179:30if it's not for that, then for what else

179:32are we really trying to do that?

179:35- I don't think there's a better way to end it

179:37than talking about love.

179:39Eugenia, I told you offline that there's something about me

179:44that felt like this was, talking to you,

§21Transcript · 2:59:48–3:01:00

179:48meeting you in person would be a turning point for my life.

179:52I know that might sound weird to hear,

179:55but it was a huge honor to talk to you.

179:58I hope we talk again.

180:00Thank you so much for your time.

180:02- Thank you so much, Alex.

180:03- Thanks for listening to this conversation

180:06with Eugenia Acuda, and thank you to our sponsors,

180:09DoorDash, Dollar Shave Club, and Cash App.

180:13Click the sponsor links in the description

180:14to get a discount and to support this podcast.

180:18If you enjoy this thing, subscribe on YouTube,

180:20review it with five stars on Apple Podcasts,

180:22follow on Spotify, support on Patreon,

180:25or connect with me on Twitter @LexFriedman.

180:28And now, let me leave you with some words from Carl Sagan.

180:32"The world is so exquisite,

180:33"with so much love and moral depth,

180:35"that there's no reason to deceive ourselves

180:37"with pretty stories of which there's little good evidence.

180:41"Far better, it seems to me,

180:43"and our vulnerability is to look death in the eye

180:46"and to be grateful every day

180:49"for the brief but magnificent opportunity

180:52"that life provides."

180:53Thank you for listening, and hope to see you next time.

180:57(upbeat music)

181:00(upbeat music)

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