Dan Kokotov: Speech Recognition with AI and Humans
Guests: Dan Kokotov
Full transcript · Read the full conversation in order, with its original context.
Contents11 chapters
§01Transcript · 00:00–08:39§02Transcript · 08:40–16:34§03Transcript · 16:38–24:44§04Transcript · 24:45–33:16§05Transcript · 33:20–42:29§06Transcript · 42:33–51:09§07Transcript · 51:11–59:31§08Transcript · 59:32–1:08:18§09Transcript · 1:08:19–1:17:01§10Transcript · 1:17:03–1:25:50§11Transcript · 1:25:52–1:28:40§01Transcript · 00:00–08:39
The following is a conversation with Dan Kokorov,
VP of Engineering at Rev.ai, which is by many metrics,
the best speech to text AI engine in the world.
Rev in general is a company that does captioning
and transcription of audio by humans and by AI.
I've been using their services for a couple of years now
and planning to use Rev to add both captions and transcripts
to some of the previous and future episodes of this podcast
to make it easier for people to read through
the conversation or reference various parts of the episode,
since that's something that quite a few people requested.
I'll probably do a separate video on that
with links on the podcast website
so people can provide suggestions and improvements there.
Quick mention of our sponsors,
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So the choice is health, wisdom or money.
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And if you wish, click the sponsor links below
to get a discount and to support this podcast.
As a side note, let me say that I reached out to Dan
and the Rev team for a conversation
because I've been using and genuinely loving their service
and really curious about how it works.
I previously talked to the head of Adobe Research
for the same reason.
For me, there's a bunch of products,
usually it's software that comes along
and just makes my life way easier.
Examples are Adobe Premiere for video editing,
iZotope RX for cleaning up audio,
AutoHotKey on Windows for automating keyboard
and mouse tasks,
Emacs as an ID for everything,
including the universe itself.
I can keep on going, but you get the idea.
I just like talking to people who create things
I'm a big fan of.
That said, after doing this conversation,
the folks at Rev.ai offered to sponsor this podcast
in the coming months.
This conversation is not sponsored by the guest.
It probably goes without saying,
but I should say it anyway,
that you cannot buy your way onto this podcast.
I don't know why you would want to.
I wanted to bring this up to make a specific point
that no sponsor will ever influence
what I do on this podcast,
or to the best of my ability,
influence what I think.
I wasn't really thinking about this,
for example, when I interviewed Jack Dorsey,
who is the CEO of Square
that happens to be sponsoring this podcast,
but I should really make it explicit.
I will never take money for bringing a guest on.
Every guest on this podcast is someone
I genuinely am curious to talk to,
or just genuinely love something they've created.
As I sometimes get criticized for,
I'm just a fan of people,
and that's who I talk to.
As I also talk about way too much,
money is really never a consideration.
In general, no amount of money can buy my integrity.
That's true for this podcast,
and that's true for anything else I do.
If you enjoy this thing, subscribe on YouTube,
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or connect with me on Twitter @LexFriedman.
And now, here's my conversation with Dan Kokorov.
You mentioned science fiction on the phone,
so let's go with the ridiculous first.
What's the greatest sci-fi novel of all time,
in your view?
And maybe, what ideas do you find
philosophically fascinating about it?
- The greatest sci-fi novel of all time is Dune,
and the second greatest is the Children of Dune,
and the third greatest is the God Emperor of Dune, so.
I'm a huge fan of the whole series.
I mean, it's just an incredible world that he created.
And I don't know if you've read the book or not.
- No, I have not.
It's one of my biggest regrets,
especially 'cause the new movie is coming out.
Everyone's super excited about it.
It's ridiculous to say,
and sorry to interrupt,
is that I used to play the video game.
It used to be Dune.
I guess you would call that real-time strategy.
- Right, right, I think I remember that game.
- Yeah, it was kind of awesome, '90s or something.
I think I played it, actually, when I was in Russia.
- I definitely remember it.
I was not in Russia anymore.
I think at the time that I used to live in Russia,
I think video games were about the suspicion of Pong.
I think Pong was pretty much the greatest game
I ever got to play in Russia,
which was still a privilege in that age.
- So you didn't get color?
You didn't get like a--
- Well, so I left Russia in 1991, right?
- '91, okay.
- So I always wanted to feel like a kid
'cause my mom was a programmer,
so I would go to her work.
I would take the Metro.
I'd go to her work and play on, I guess,
the equivalent of a 286 PC, you know?
- Nice, with floppy disks.
- Yes, yes.
- So okay, but back to Dune, what do you get?
- Back to Dune.
And by the way, the new movie I'm pretty interested in,
but the original--
- You're skeptical?
- I'm a little skeptical.
I'm a little skeptical.
I saw the trailer.
I don't know, so there's a David Lynch movie, Dune,
as you may know.
I'm a huge David Lynch fan, by the way.
So the movie is somewhat controversial,
but it's a little confusing,
but it captures kind of the mood of the book
better than I would say most any adaptation.
And like, Dune is so much about kind of mood
and the world, right?
But back to the philosophical point.
So in the fourth book, "God, Emperor of Dune,"
there's a sort of setting where Leto,
one of the characters,
he's become this weird sort of god-emperor.
He's turned into a gigantic worm,
and you kind of have to read the book
to understand what that means.
- So the worms are involved.
- Worms are involved.
You probably saw the worms in the trailer, right?
- And in the video game.
- So he kind of like merges with this worm
and becomes this tyrant of the world,
and he like oppresses the people for a long time, right?
But he has a purpose,
and the purpose is to kind of break through
kind of a stagnation period in civilization, right?
But people have gotten too comfortable, right?
And so he kind of oppresses them so that they explode
and go on to colonize new worlds
and kind of renew the forward momentum of humanity, right?
And so to me, that's kind of fascinating, right?
You need a little bit of pressure and suffering, right,
to kind of make progress, not get too comfortable.
(laughing)
Maybe that's a bit of a cruel philosophy to take away, but.
- That seems to be the case, unfortunately.
Obviously, I'm a huge fan of suffering.
So one of the reasons we're talking today
is that a bunch of people requested
that I do transcripts for this podcast and do captioning.
I used to make all kinds of YouTube videos,
and I would go on Upwork, I think,
and I would hire folks to do transcription,
and it was always a pain in the ass, if I'm being honest.
And then I don't know how I discovered Rev,
but when I did, it was this feeling of like,
holy shit, somebody figured out
how to do it just really easily.
I'm such a fan of just,
when people take a problem and they just make it easy.
- Right.
- Like just,
there's so many, it's like there's so many things in life
that you might not even be aware of that are painful,
and then Rev, you just like give the audio, give the video,
you can actually give a YouTube link,
and then it comes back like a day later,
or two days later, whatever the hell it is,
with the captions, all in a standardized format.
I don't know, it was truly a joy.
So I thought I had, just for the hell of it, talk to you.
One other product, it just made my soul feel good.
One other product I've used like that
is for people who might be familiar,
is called iZotope RX, it's for audio editing.
And that's another one where it was like,
you just drop it, I dropped into the audio,
and it just cleans everything up really nicely.
All the stupid, like the mouth sounds,
and sometimes there's background like sounds
due to the malfunction of the equipment,
it can clean that stuff up.
§02Transcript · 08:40–16:34
It has like general voice denoising,
it has like automation capabilities
where you can do batch processing,
and you can put a bunch of effects.
I mean, it just, I don't know, everything else sucked
for like voice-based cleanup that I've ever used.
I've used Audition, Adobe Audition,
I've used all kinds of other things with plugins,
and you have to kind of figure it all out,
you have to do it manually, here it just worked.
So that's another one in this whole pipeline
that just brought joy to my heart.
Anyway, all that to say is,
Rev put a smile to my face.
So can you maybe take a step back and say,
what is Rev, and how does it work?
And Rev or Rev.com?
- Rev, Rev.com.
(laughing)
Same thing, I guess.
Though we do have Rev.ai now as well,
which we can talk about later.
- Like, do you have the actual domain, or is it just--
- The actual domain, but we also use it
kind of as a sub-brand.
So we use Rev.ai to denote our ASR services, right?
And Rev.com is kind of our more human
and to the end user services.
- So it's like wordpress.com and wordpress.org,
they actually have separate brands that like,
I don't know if you're familiar with what those are.
- Yeah, yeah, yeah.
They provide almost like a separate branch of--
- A little bit, I think with that, it's like,
wordpress.org is kind of their open source, right?
And wordpress.com is sort of their
hosted commercial offering.
- Yes.
- And with us, the differentiation is a little bit different,
but maybe a similar idea.
- Yeah.
Okay, so what is Rev?
- Before I launch into what is Rev,
I was gonna say, you know, like you were talking about,
like Rev was music to your ears.
Your spiel was music to my ears,
and to us, the founders of Rev,
because Rev was kind of founded
to improve on the model of Upwork.
That was kind of the original,
or part of their original impetus.
Like our CEO, Jason, was a early employee of Upwork,
so he's very familiar with their--
- Upwork the company.
- Upwork the company.
And so he was very familiar with that model,
and he wanted to make the whole experience better,
because he knew like, when you go,
at that time, Upwork was primarily programmers.
So the main thing they offered is,
if you wanna hire someone to help you code a little site,
you could go on Upwork,
and you could like browse through a list of freelancers,
pick a programmer, have a contract with them,
and have them do some work.
But it was kind of a difficult experience,
because for you, you would kind of have to browse
through all these people, right?
And you have to decide, okay, like,
well, is this guy good, or is somebody else better?
And naturally, you're going to Upwork
because you're not an expert, right?
If you're an expert, you probably wouldn't be
like getting a programmer from Upwork.
So how can you really tell?
So there's kind of like a lot of potential regret, right?
What if I choose a bad person?
They're like gonna be late on the work.
It's gonna be a painful experience.
And for the freelancer, it was also painful,
because half the time, they spent not
on actually doing the work,
but kind of figuring out how can I make my profile
most attractive to the buyer, right?
And they're not an expert on that either.
So like, Rob's idea was, let's remove the barrier, right?
Like, let's make it simple.
We'll pick a few verticals that are fairly standardizable.
Now, we actually started with translation,
and then we added audio transcription a bit later.
And we'll just make it a website.
You go, give us your files.
We'll give you back the results as soon as possible.
Originally, maybe it was 48 hours,
then we made it shorter and shorter and shorter.
- Yeah, there's a rush processing too.
- There's a rush processing now.
And we'll hide all the details from you, right?
- Yeah.
- And like, that's kind of exactly
what you're experiencing, right?
You don't need to worry about the details
of how the sausage is made.
- That's really cool.
So you picked like a vertical.
By vertical, you mean basically a--
- A service, a service category.
- Why translation?
Is Rev thinking of potentially going
into other verticals in the future?
Or is this like the focus now is translation,
transcription, like language?
- The focus now is language or speech services generally,
speech to text, language services.
You can kind of group them however you want.
So, but we originally,
the categorization was work from home.
And so we wanted work that was done by people on a computer.
You know, we weren't trying to get into, you know,
task rabbit type of things.
And something that could be relatively standard,
not a lot of options.
So we could kind of present the simplified interface, right?
So programming wasn't like a good fit
because each programming project is kind of unique, right?
We're looking for something that transcription is,
you know, you have five hours of audio,
it's five hours of audio, right?
Translation is somewhat similar in that, you know,
you can have a five page document, you know,
and then you just can price it by that.
And then you pick the language you want,
and that's mostly all that is to it.
So those were a few criteria.
We started with translation because we saw the need
and we picked up kind of a specialty of translation
where we would translate things like birth certificates,
immigration documents, things like that.
And so they were fairly, even more well-defined
and easy to kind of tell if we did a good job.
- So you can literally charge per type of document?
Was that the, so what is it now?
Is it per word or something like that?
Like how do you measure the effort involved
in a particular thing?
- So now it looks like for audio transcription, right?
It's per audio unit.
- Well, that, yes.
- For our translation,
we don't really actually focus on that anymore.
But, you know, back when it was still a main business
of Revit was per page, right?
Or per word, depending on the kind of--
- 'Cause you can also do translation now
on the audio, right?
- Mm-hmm, like subtitles.
So it would be both transcription and translation.
- That's right.
- I wanted to test the system to see how good it is,
to see like how, well, is Russian supported?
- I think so, yeah.
- It'd be interesting to try it out.
I mean, one of the--
- But now it's only in like the one direction, right?
So you start with English
and then you can have subtitles in Russian.
- In Russian.
- Not really the other way.
- Got it, because I'm deeply curious about this.
When COVID opens up a little bit,
when the economy, when the world opens up a little bit.
- You wanna build your brand in Russia?
- No, I don't.
First of all, I'm allergic to the word brand.
(laughing)
I'm definitely not building any brands in Russia.
But I'm going to Paris to talk to the translators
of Dostoevsky and Tolstoy.
There's this famous couple that does translation.
And I'm more and more thinking of how is it possible
to have a conversation with a Russian speaker?
'Cause I have just some number of famous Russian speakers
that I'm interested in talking to.
And my Russian is not strong enough to be witty and funny.
I'm already an idiot in English.
I'm an extra level of like awkward idiot in Russian,
but I can understand it, right?
And I also like wonder how can I create
a compelling English-Russian experience
for an English speaker?
Like if I, there's a guy named Grigori Perlman,
who's a mathematician,
who obviously doesn't speak any English.
So I would probably incorporate
like a Russian translator into the picture.
And then it would be like a, not to use a weird term,
but like a three person thing,
where it's like a dance of, like I understand it one way,
they don't understand the other way,
but I'll be asking questions in English.
§03Transcript · 16:38–24:44
I don't know.
I don't know the right way.
- It's complicated.
- It's complicated,
but I feel like it's worth the effort
for certain kinds of people.
One of whom I'm confident is Vladimir Putin,
I'm for sure talking to.
I really want to make it happen
'cause I think I could do a good job with it.
But the right, you know,
understanding the fundamentals of translation
is something I'm really interested in.
So that's why I'm starting with the actual translators
of like Russian literature,
because they understand the nuance
and the beauty of the language
and how it goes back and forth.
But I also want to see like in speech,
how can we do it in real time?
So that's like a little bit of a baby project
that I hope to push forward.
But anyway.
- It's a challenging thing.
So just to share,
my dad actually does translation.
Not professionally, he writes poetry.
That was kind of always his,
not a hobby, but he had a job, like a day job,
but his passion was always writing poetry.
And then we got to America
and like he started also translating.
First he was translating English poetry to Russian.
Now he also like goes the other way.
You kind of gain some small fame in that world anyways,
because recently this poet, like Louise Clark,
I don't know if you know of,
some American poet,
she was awarded the Nobel Prize for literature.
And so my dad had translated
one of her books of poetry into Russian.
He was like one of the few.
So he kind of like, they asked him
and gave an interview to Radio Svoboda,
if you know what that is.
And he kind of talked about some of the intricacies
of translating poetry.
So that's like an extra level of difficulty, right?
Because translating poetry is even more challenging
than translating just, you know, interviews.
- Do you remember any experiences and challenges
to having to do the translation that stuck out to you?
Like something he's talked about?
- I mean, a lot of it I think is word choice, right?
It's the way Russian is structured
is first of all quite different
than the way English is structured, right?
Just there's inflections in Russian and genders
and they don't exist in English.
One of the reasons actually why machine translation
is quite difficult for English to Russian
and Russian to English,
because they're such different languages.
But then English has like a huge number of words,
many more than Russian actually, I think.
So it's often difficult to find the right word
to convey the same emotional meaning.
- Yeah, Russian language, they play with words much more.
So you were mentioning that Rev was kind of born
out of trying to take a vertical on Upwork
and then standardize it.
So--
- We're just trying to make
the freelancer marketplace idea better, right?
Better for both customers
and better for the freelancers themselves.
- Is there something else to the story of Rev,
finding Rev?
Like what did it take to bring it to actually to life?
Was there any pain points?
- Plenty of pain points.
I mean, as often the case, it's with scaling it up, right?
And in this case, the scaling is kind of scaling
the marketplace, so to speak, right?
Rev is essentially a two-sided marketplace, right?
Because there's the customers and then there's the Revvers.
If there's not enough Revvers,
Revvers are what we call our freelancers.
So if there's not enough Revvers,
then customers have a bad experience, right?
Takes longer to get your work done, things like that.
If there's too many, then Revvers have a bad experience
because they might log on to see what work is available
and there's not very much work, right?
So kind of keeping that balance
is a quite challenging problem.
And that's like a problem we've been working on
for many years.
We're still refining our methods, right?
- If you can kind of talk to this gig economy idea,
I did a bunch of different psychology experiments
on Mechanical Turk, for example.
I've asked to do different kinds of very tricky
computer vision annotation on Mechanical Turk
and it's connecting people in a more systematized way.
I would say, you know, between task and,
what would you call that, worker,
is what Mechanical Turk calls it.
What do you think about this world of gig economies,
of there being a service that connects customers to workers
in a way that's like massively distributed,
like potentially scaling to,
it could be scaled to like tens of thousands of people,
right?
Is there something interesting about that world
that you can speak to?
- Yeah, well, we don't think of it as kind of gig economy,
but like to some degree,
I don't like the word gig that much, right?
Because to some degree it diminishes
the work being done, right?
It sounds kind of like almost amateurish.
Well, maybe in like music industry,
like gig is the standard term,
but in work, it kind of sounds like it's frivolous.
To us, it's improving the nature of working from home
on your own time and on your own terms, right?
And kind of taking away geographical limitations
and time limitations, right?
So, many of our freelancers are maybe work from home moms,
right?
And they don't want the traditional nine to five job,
but they wanna make some income
and Rev kind of like allows them to do that
and decide like exactly how much to work and when to work.
Or by the same token, maybe someone is,
someone wants to live the mountain top,
life, right?
You know, cabin in the woods,
but they still wanna make some money.
And like, generally that wouldn't be compatible
before this new world, you kind of had to choose.
But like with Rev, like you feel like
you don't have to choose.
- Can you speak to like,
what's the demographics like distribution,
like where do Revvers live?
Is it from all over the world?
Like, what is it?
Do you have a sense of what's out there?
- We're all over the world.
Most of them are in the US, that's the majority.
Yeah, because most of our work is audio transcription
and so you have to speak pretty good English.
So, the majority of them are from the US,
so we have people in some other
of the English speaking countries.
And as far as like US, it's really all over the place.
You know, for some of the years now,
we've been doing these little meetings
where the management team will go to some place
and we'll try to meet Revvers.
And, you know, pretty much wherever we go,
it's pretty easy to find, you know,
a large number of Revvers.
You know, the most recent one we did is in Utah.
But anywhere really.
- Are they from all walks of life?
Are these young folks, older folks?
- Yeah, all walks of life really.
Like I said, you know, one category is, you know,
the work from home, students, you know,
who wanna make some extra income.
There are some people who maybe, you know,
maybe they have some social anxiety,
so they don't wanna be in the office, right?
And this is one way for them to make a living.
So it's really pretty wide variety.
But like on the flip side, for example,
one Revver we were talking to was a person
who had a fairly high-powered career before
and was kind of like taking a break
and just wanted, she was almost doing this
just to explore and learn about, you know,
the gig economy, quote unquote, right?
So it really is a pretty wide variety of folks.
- Yeah, it's kind of interesting
through the captioning process
for me to learn about the Revvers
because like some are clearly like weirdly knowledgeable
about technical concepts.
Like you can tell by how good they are
at like capitalizing stuff, like technical terms,
like in machine learning and deep learning.
- Right.
- I've used Rev to annotate, to caption
the deep learning lectures or machine learning lectures
I did at MIT.
And it's funny, like a large number of them were like,
I don't know if they looked it up
§04Transcript · 24:45–33:16
or were already knowledgeable,
but they do a really good job at like, I don't know.
- They invest time into these things.
They will like do research, they will Google things,
you know, to kind of make sure they get it right.
But to some of them, it's like,
it's actually part of the enjoyment of the work.
Like they'll tell us, you know,
I love doing this because I get paid
to watch a documentary on something, right?
And I learned something while I'm transcribing, right?
Pretty cool.
- Yeah.
So what's that captioning transcription process
look like for the Revver?
Can you maybe speak to that to give people a sense,
like how much is automated, how much is manual?
What's the actual interface look like?
All that kind of stuff.
- Yeah, so, you know, we've invested
a pretty good amount of time to give like our Revvers
the best tools possible.
You know, so typical day for Revver,
they might log into their workspace,
they'll see a list of audios that need to be transcribed.
And we try to give them tools to pick specifically
the ones they want to do, you know?
So maybe some people like to do longer audios
or shorter audios.
People have their preferences.
Some people like to do audios in a particular subject
or from a particular country.
So we try to give people, you know,
the tools to control things like that.
And then when they pick what they want to do,
we'll launch a specialized editor that we've built
to make transcription as efficient as possible.
They'll start with a speech rec draft.
So, you know, we have our machine learning model
for automated speech recognition.
They'll start with that.
And then our tools are optimized to help them correct that.
- So it's basically a process of correction.
- Yeah, it depends on, you know, I would say the audio.
If audio itself is pretty good,
like probably like our podcast right now
would be quite good.
So they would do a fairly good job.
But if you imagine someone recorded a lecture, you know,
in the back of a auditorium, right?
Where like the speaker is really far away
and there's maybe a lot of crosstalk and things like that,
then maybe they wouldn't do a good job.
So the person might say like, you know what,
I'm just gonna do it from scratch.
- Do it from scratch, yeah.
- So it kind of really depends.
- What would you say is the speed that you can possibly get?
Like what's the fastest?
Is it possible to get real time or no?
As you're like listening, can you write as fast as-
- Real time would be pretty difficult.
It's actually a pretty, it's not an easy job.
You know, we actually encourage everyone at the company
to try to be a transcriber for a day,
transcriptionist for a day.
And it's way harder than you might think it is, right?
Because people talk fast and people have accents
and all this kind of stuff.
So real time is pretty difficult.
- Is it possible?
Like there's somebody, we're probably gonna use Rev
to caption this.
They're listening to this right now.
What do you think is the fastest
you could possibly get on this right now?
- I think on a good audio,
maybe two to three X, I would say, real time.
- Meaning it takes two to three times longer
than the actual audio of the podcast.
This is so meta.
I could just imagine the Revvers working on this right now.
Like you're way wrong.
- You're way wrong, this takes way longer.
But yeah, it definitely works.
- Or you doubted me, I could do real time.
(both laughing)
- Okay, so you mentioned ASR.
Can you speak to what is ASR, automatic speech recognition?
How much, like what is the gap
between perfect human performance
and perfect or pretty damn good ASR?
- Yeah, so ASR, automatic speech recognition,
it's a class of machine learning problem, right?
To take speech like we're talking
and transform it into a sequence of words, essentially.
- Audio of people talking.
- Audio to words.
And there's a variety of different approaches and techniques
which we could talk about later if you want.
So we think we have pretty much the world's best ASR
for this kind of speech, right?
So there's different kinds of domains, right, for ASR.
Like one domain might be voice assistance, right?
So Siri, very different than what we're doing, right?
Because Siri, there's fairly limited vocabulary.
You might ask Siri to play a song
or order a pizza or whatever.
And it's very good at doing that.
Very different from when we're talking
in a very unstructured way.
And Siri will also generally adapt to your voice
and stuff like this.
So for this kind of audio, we think we have the best.
And our accuracy, right now it's, I think,
it's maybe 14% word error rate on our test suite
that we generally use to measure.
So word error rate is like one way to measure
accuracy for ASR, right?
- So what's 14% word error rate mean?
- So 14% means across this test suite
of a variety of different audios,
it would be, it would get in some way 14%
of the words wrong, 14% of the words wrong.
- Yeah.
- So the way you kind of calculate it is,
you might add up insertions, deletions,
and substitutions, right?
So insertions is like extra words,
deletions are words that we said,
but weren't in the transcript, right?
Substitutions is, you said Apple, but I said,
but the ASR thought it was Able, something like this.
Human accuracy, most people think realistically,
it's like 3%, 2% word error rate
would be like the max achievable.
So there's still quite a gap, right?
- Would you say that, so YouTube,
when I upload videos often generates automatic captions.
Are you sort of from a company perspective,
from a tech perspective, are you trying to beat YouTube?
Google, it's a hell of a, so Google,
I mean, I don't know how seriously they take this task,
but I imagine it's quite serious.
And they, you know, Google is probably up there
in terms of their teams on ASR,
or just NLP, natural language processing,
different technologies.
So do you think you can beat Google?
- On this kind of stuff, yeah, we think so.
Google just woke up on my phone.
- This is hilarious, okay.
- Now Google is listening,
sending it back to headquarters.
Who are these rough people?
- But that's the goal?
- Yeah, I mean, we measure ourselves against like Google,
Amazon, Microsoft, you know, some smaller competitors.
And we use like our internal tests with it.
We try to compose it of a pretty representative set of
audios, maybe it's some podcasts, some videos,
some interviews, some lectures, things like that, right?
And we beat them in our own testing.
- And actually Rev offers automated,
like you can actually just do the automated captioning.
So like, I guess it's like way cheaper, whatever it is,
whatever the rates are.
- Yeah, yeah.
- By the way, it used to be a dollar per minute
for captioning and transcription.
I think it's like a dollar 15 or something like that.
- Dollar 25.
- Dollar 25.
Dollar 25, no.
Yeah, it's pretty cool.
That was the other thing that was surprising to me.
It was actually like the cheapest thing you could,
I mean, I don't remember it being cheaper.
You could on Upwork get cheaper,
but it was clear to me that this,
that's going to be really shitty.
- Yeah.
- So like, you're also competing on price.
I think there were services that you can get like similar
to Rev kind of feel to it, but it wasn't as automated.
Like the drag and drop, the entirety of the interface.
It's like the thing we're talking about.
I'm such a huge fan of like frictionless,
like Amazon's single buy button, whatever.
- Yeah, yeah.
- That one click, that's genius right there.
Like that is so important for services.
- Yeah.
- That simplicity.
And I mean, Rev is almost there.
I mean, there's like some, trying to think.
So I think I've, I stopped using this pipeline,
but Rev offers it and I like it,
but it was causing me some issues on my side,
which is you can connect it to like Dropbox
§05Transcript · 33:20–42:29
and it generates the files in Dropbox.
So like it closes the loop to where I don't have to go
to Rev at all and I can download it.
Sorry, I don't have to go to Rev at all
and to download the files.
It could just like automatically copy them.
- Right, you put in your Dropbox and you know,
a day later or maybe a few hours later.
- Yeah, it just shows up.
- Depending on if you're in a rush, it just shows up, yeah.
I was trying to do it programmatically too.
Is there an API interface you can,
I was trying to through like through Python
to download stuff automatically,
but then I realized this is the programmer in me.
Like, dude, you don't need to automate everything
like in life, like flawlessly.
'Cause I wasn't doing enough captions to justify
to myself the time investment
into automating everything perfectly.
- Yeah, I would say if you're doing so many interviews
that your biggest roadblock is clicking
on the Rev download button.
Now you're talking about Elon Musk levels of business.
- But for sure we have like a variety of ways
to make it easy.
You know, there's the integration.
You mentioned, I think it's through a company called Zapier,
which kind of can connect Dropbox to Rev and vice versa.
We have an API if you wanna really like customize it,
you know, if you wanna create the Lex Friedman,
you know, CMS or whatever.
- For this whole thing, okay, cool.
So can you speak to the ASR a little bit more?
Like, what does it take like approach-wise,
machine learning-wise, how hard is this problem?
How do you get to the 3% error rate?
Like, what's your vision of all of this?
- Yeah, well, the 3% error rate is definitely,
that's the grand vision.
We'll see what it takes to get there.
But we believe, you know, in ASR,
the biggest thing is the data, right?
Like, that's true of like a lot
of machine learning problems today, right?
The more data you have and the higher quality of the data,
the better labeled the data.
Yeah, that's how you get good results.
And we at Rev have kind of like the best data, like we have.
- Like you're literally, your business model
is annotating the data.
- Our business model is being paid to annotate the data.
- Being paid to annotate the data.
- So it's kind of like a pretty magical flywheel.
- Yeah.
- And so we've kind of like ridden this flywheel
to this point.
And we think we're still kind of in the early stages
of figuring out all the parts of the flywheel to use,
you know, because we have the final transcripts
and we have the audios and we train on that.
But we, in principle, also have all the edits
that the Revvers make, right?
- Oh, that's interesting.
How can you use that as data?
- We basically, that's something for us to figure out
in the future, but you know,
we feel like we're only in the early stages, right?
- So the data is there, that'd be interesting,
like almost like a recurrent neural net
for fixing transcripts.
I always remember we did a segmentation annotation
for driving data, so segmenting the scene, like visual data.
And you can get all, so it was drawing,
people were drawing polygons around different objects
and so on.
And it feels like, it always felt like there was a lot
of information in the clicking,
the sequence of clicking that people do,
the kind of fixing of the polygons that they do.
Now there's a few papers written about how to draw polygons,
like with recurrent neural nets to try to learn
from the human clicking, but it was just like experimental,
you know, it was one of those like CVPR type papers
that people do like a really tiny data set.
It didn't feel like people really tried to do it seriously.
And I wonder, I wonder if there's information
in the fixing that provides deeper set of signal
than just like the raw data.
- The intuition is for sure there must be, right?
- There must be.
- And in all kinds of signals and how long you took
to make that edit and stuff like that.
- Yeah, it's gonna be like up to us.
That's why like the next couple of years
is like super exciting for us, right?
- So that's what like the focus is now.
You mentioned Rev.ai, that's where you want to.
- Yeah, so Rev.ai is kind of our way of bringing this ASR
to the rest of the world, right?
So when we started, we were human only,
then we kind of created this TEMI service,
I think you might've used it,
which was kind of ASR for the consumer, right?
So if you don't want to pay $1.25,
but you want to pay, now it's 25 cents a minute, I think.
And you get the transcript,
the machine generated transcript,
you get an editor and you can kind of fix it up yourself.
Then we started using ASR for human transcriptionists.
And then the kind of Rev.ai is the final step
of the journey, which is, we have this amazing engine.
What can people build with it, right?
What kind of new applications could be enabled
if you have SpeedTrack that's that accurate?
- Do you have ideas for this
or is it just providing it as a service
and seeing what people come up with?
- It's providing it as a service
and seeing what people come up with
and kind of learning from what people do with it.
And we have ideas of our own as well, of course,
but it's a little bit like,
when AWS provided the building blocks, right?
And they saw what people built with it
and they try to make it easier to build those things, right?
And we kind of hope to do the same thing.
- Although AWS kind of does a shitty job of like,
I'm continually surprised, like Mechanical Turk,
for example, how shitty the interface is.
We're talking about like Rev.ai making me feel good.
Like when I first discovered Mechanical Turk,
the initial idea of it was like,
it made me feel like Rev.ai does,
but then the interface is like, come on.
- Yeah, it's horrible.
- Why is it so painful?
Does nobody at Amazon wanna like seriously invest in it?
It felt like you can make so much money
if you took this effort seriously.
And it feels like they have a committee of like two people
just sitting back, like a meeting,
they meet once a month,
like what are we gonna do with Mechanical Turk?
It's like two websites make me feel like this,
that and craiglist.org, whatever the hell it is.
- It feels like it's designed in the 90s.
- Well, craiglist basically hasn't been updated
pretty much since the guy originally built.
- Do you seriously think there's a team,
like how big is the team working on Mechanical Turk?
- I don't know, there's some team, right?
- I feel like there isn't, I'm skeptical.
- Yeah, well, if nothing else, they benefit from,
you know, the other teams like moving things forward,
right, in a small way.
But no, I know what you mean,
we use Mechanical Turk for a couple of things as well,
and yeah, it's painful.
- But yeah, it works.
- I think most people, the thing is most people
don't really use the UI, right?
Like, so like we, for example, we use it through the API.
- But even the API documentation and so on,
like it's super outdated.
I don't even know what to, I mean, same criticism,
as long as we're ranting, my same criticism goes
to the APIs of most of these companies,
like Google, for example, the API for the different services
is just the documentation is so shitty.
Like, it's not so shitty, I should actually be,
I should exhibit some gratitude.
Okay, let's practice some gratitude.
The, you know, the documentation is pretty good.
Like most of the things that the API makes available
is pretty good.
It's just that in the sense that it's accurate,
sometimes outdated, but like the degree of explanations
with examples is only covering, I would say like 50%
of what's possible.
And it just feels a little bit like there's a lot
of natural questions that people would wanna ask
that doesn't get covered.
And it feels like it's almost there.
Like it's such a magical thing, like the Maps API,
YouTube API, there's a bunch of stuff.
- I gotta imagine it's like, you know,
there's probably some team at Google, right,
responsible for writing this documentation.
That's probably not the engineers, right?
And probably this team is not, you know,
where you wanna be.
- Well, it's a weird thing.
I sometimes think about this for somebody who wants
to also build the company.
I think about this a lot.
You know, YouTube, the service is one of the most magical,
like I'm so grateful that YouTube exists.
And yet they seem to be quite clueless on so many things
like that everybody's screaming them at.
§06Transcript · 42:33–51:09
Like it feels like whatever the mechanism that you use
to listen to your quote unquote customers,
which is like the creators is not very good.
Like there's literally people that are like screaming,
like their new YouTube studio, for example.
There's like features that were like begged for,
for a really long time,
like being able to upload multiple videos at the same time.
That was missing for a really, really long time.
Now, like there's probably things that I don't know,
which is maybe for that kind of huge infrastructure,
it's actually very difficult to build some of these features.
But the fact that that wasn't communicated
and it felt like you're not being heard.
Like I remember this experience for me
and it's not a pleasant experience.
And it feels like the company doesn't give a damn about you.
And that's something to think about.
I'm not sure what that is.
That might have to do with just like small groups
working on these small features and these specific features.
And there's no overarching like dictator type of human
that says like, why the hell are we neglecting
like Steve Jobs type of characters?
Like there's people that we need to speak to the people
that like wanna love our product and they don't.
Let's fix this shit. - Yeah, I mean,
at some point you just get so fixated on the numbers.
And it's like, well, the numbers are pretty great.
Like people are watching,
doesn't seem to be a problem.
- Doesn't seem to be a problem.
- And you're not like the person that like build this thing.
So you really care about it.
You're just there, you came in as a product manager.
You got hired sometime later,
your mandate is like increase this number like 10%, right?
And you just-- - That's brilliantly put.
Like if you, this is, okay, if there's a lesson in this,
is don't reduce your company into a metric of like,
how much, like you said,
how much people watching the videos and so on,
and like convince yourself that everything is working
just because the numbers are going up.
There's something, you have to have a vision.
You have to want people to love your stuff
because love is ultimately the beginning
of like a successful long-term company
is that they always should love your product.
- You have to be like a creator
and have that like creator's love for your own thing, right?
Like, and you paint by, you know, these comments, right?
And probably like, Apple, I think did this generally
like really well. - Yes, really well.
- They're well known for kind of keeping teams small,
even when they were big, right?
And, you know, he was an engineer,
like there's that book, "Creative Selection."
I don't know if you read it by an Apple engineer
named Ken Kosienda.
It's kind of a great book actually,
because unlike most of these business books where it's,
you know, here's how Steve Jobs ran the company.
It's more like, here's how life was like for me,
you know, an engineer.
Here are the projects I worked on
and here what it was like to pitch Steve Jobs, you know,
on like, you know, I think it was in charge of like
the keyboard and the auto correction, right?
And at Apple, like Steve Jobs reviewed everything.
And so he was like, this is what it was like
to show my demos to Steve Jobs and, you know,
to change them because like Steve Jobs didn't like how,
you know, the shape of the little key was off
because the rounding of the corner was like not quite right
or something like this, but he was famously a stickler
for this kind of stuff.
But because the teams were small,
he really owned this stuff, right?
So he really cared.
- Yeah, Elon Musk does that similar kind of thing with Tesla,
which is really interesting.
There's another lesson in leadership in that
is to be obsessed with the details.
And like, he talks to like the lowest level engineers.
Okay, so we're talking about ASR.
And so this is basically where I was saying,
we're gonna take this like ultra seriously.
And then what's the mission?
To try to keep pushing towards the 3%?
- Yeah, and kind of try to build this platform
where all of your, you know, all of your meetings,
you know, they're as easily accessible as your notes, right?
Like, so like imagine all the meetings
a company might have, right?
Now that I'm like no longer a programmer, right?
And I'm a quote unquote manager,
that's less like my day is in meetings, right?
And, you know, pretty often I wanna like see what was said,
right, who said it, you know, what's the context.
But it's generally not really something
that you can easily retrieve, right?
Like imagine if all of those meetings
were indexed, archived, you know, you could go back,
you could share a clip like really easily, right?
- So that might change completely.
Like everything that's said converted to text
might change completely the dynamics
of what we do in this world.
Especially now with remote work, right?
- Exactly, exactly.
- With Zoom and so on.
That's fascinating to think about.
I mean, for me, I care about podcasts, right?
And one of the things that was, you know, I'm torn.
I know a lot of the engineers at Spotify.
So I love them very much because they dream big
in terms of like, they wanna empower creators.
So one of my hopes was with Spotify
that they would use a technology like Rev
or something like that to start converting everything
into text and make it indexable.
Like one of the things that sucks with podcasts
is like, it's hard to find stuff.
Like the model is basically subscription.
Like you find, it's similar to what YouTube used to be like,
which is you basically find a creator that you enjoy
and you subscribe to them and like, you just,
you just kind of follow what they're doing.
But the search and discovery wasn't a big part of YouTube
like in the early days.
But that's what currently with podcasts,
like is the search and discovery is like non-existent.
You're basically searching for like
the dumbest possible thing,
which is like keywords in the titles of episodes.
- Yeah, but even aside from searching,
it's kind of like all the time.
So I listened to like a number of podcasts
and there's something sad
and I wanna like go back to that later
because I was trying to, I'm trying to remember,
what do you say?
Like maybe like recommend some cool product
that I wanna try out.
And like, it's basically impossible.
Maybe like some people have pretty good show notes.
So maybe you'll get lucky and you can find it, right?
But I mean, if everyone had transcripts
and it was all searchable, it would be--
- It's a game changer.
- It'd be so much better.
- I mean, that's one of the things that I wanted to,
I mean, one of the reasons we're talking today
is I wanted to take this quite seriously,
the rev thing, I've just been lazy.
So because I'm very fortunate
that a lot of people support this podcast,
that there's enough money now to do a transcription
and so on, it seemed clear to me,
especially like CEOs and sort of like PhDs,
like people write to me
who are like graduate students in computer science
or graduate students in whatever the heck field.
It's clear that their mind,
like they enjoy podcasts when they're doing laundry
or whatever, but they wanna revisit the conversation
in a much more rigorous way.
And they really wanna transcript.
It's clear that they want to like analyze conversations.
So many people wrote to me about a transcript
for Yosha Bach conversation.
I had just a bunch of conversations.
And then on the Elon Musk side,
like reporters want like,
they wanna write a blog post about your conversation.
So they wanna be able to pull stuff.
And it's like, they're essentially doing
on your conversation transcription privately.
They're doing it for themselves and then starting to pick,
but it's so much easier when you can actually do it
as a reporter, just look at the transcript.
- Yeah, and you can like embed a little thing,
you know, like into your article, right?
Here's what they said.
You can go listen to like this clip from the section.
- I'm actually trying to figure out,
I'll probably on the website create like a place
where the transcript goes like as a webpage
so that people can reference it,
like reporters can reference it and so on.
I mean, most of the reporters probably
have wanted right clickbait articles
that are complete falsifying, which I'm fine with.
It's the way of journalism, I don't care.
Like I've had this conversation with a friend of mine,
a mixed martial artist, Ryan Hall.
And we talked about, you know,
as I've been reading the rise and fall of the Third Reich
and a bunch of books on Hitler.
§07Transcript · 51:11–59:31
And we brought up Hitler and he made some kind of comment
where like we should be able to forgive Hitler.
And, you know, like we were talking about forgiveness
and we're bringing that up
as like the worst case possible things.
Like even, you know, for people who are Holocaust survivors,
one of the ways to let go of the suffering
they've been through is to forgive.
And he brought up like Hitler is somebody
that would potentially be the hardest thing
to possibly forgive,
but it might be a worthwhile pursuit psychologically.
So on, blah, blah, blah, it doesn't matter.
It was very eloquent, very powerful words.
I think people should go back and listen to it.
It's powerful.
And then all these journalists,
all these articles written about like MMA fight,
UFC fight.
- MMA fighter loves Hitler.
- No, like, well, no, they were somewhat accurate.
They didn't say like loves Hitler.
They said, thinks that if Hitler came back to life
we should forgive him.
Like they kind of, it's kind of accurate-ish,
but it, the headline made it sound a lot worse
than it was, but I'm fine with it.
That's the way the world,
I wanna almost make it easier for those journalists
and make it easier for people who actually care
about the conversation to go and look and see.
- Right, they can see it for themselves.
- For themselves, full context.
- There's the headline, but now you can go.
- There's something about podcasts,
like the audio that makes it difficult to go,
to jump to a spot and to look for that,
for that particular information.
I think some of it, you know, I'm interested in creating
like myself experimenting with stuff.
So like taking Rev and creating a transcript
and then people can go to it.
I do dream that like, I'm not in the loop anymore,
that like, you know, Spotify does it, right?
Like automatically for everybody,
because ultimately that one-click purchase
needs to be there, like, you know.
- I mean, like you kind of want support
from the entire ecosystem, right?
- Exactly.
- Like from the tool makers and the podcast creators,
even clients, right?
I mean, imagine if like most podcast apps,
you know, if it was a standard, right?
Here's how you include a transcript into a podcast, right?
Podcast is just an RSS feed ultimately.
And actually just yesterday I saw this company called
Buzzsprout, I think they're called.
So they're trying to do this.
They proposed a spec, an extension to their RSS format
to reference podcasts, reference transcripts
in a standard way.
And they're talking about like,
there's one client dimension that will support it,
but imagine like more clients support it, right?
So any podcast you could go and see the transcripts, right?
On your like normal podcast app.
- Yeah, I mean, somebody,
so I have somebody who works with me,
works with, helps with advertising, Matt,
this awesome guy.
He mentioned Buzzsprout to me,
but he says it's really annoying
'cause they want exclusive,
they wanna host the podcast.
- Right.
- This is the problem with Spotify too.
This is where I'd like to say like F Spotify.
There's a magic to RSS with podcasts.
It can be made available to everyone.
And then there's all,
there's this ecosystem of different podcast players
that emerge and they compete freely.
And that's a beautiful thing.
That's why I go on exclusive,
like Joe Rogan went exclusive.
I'm not sure if you're familiar with,
he went to just Spotify.
As a huge fan of Joe Rogan,
I've been kind of nervous about the whole thing,
but let's see.
I hope that Spotify steps up.
They've added video,
which is very surprising that they were able to--
- So exclusive meaning you can't subscribe
to his RSS feed anymore.
It's only in Spotify.
- For now, you can until December 1st.
And December 1st, it's all,
everything disappears and it's Spotify only.
I, you know, and Spotify gave him $100 million for that.
So it's an interesting deal,
but I, you know, I did some soul searching
and I'm glad he's doing it.
But if Spotify came to me with $100 million,
I wouldn't do it.
I wouldn't do, well,
I have a very different relationship with money.
I hate money, but I just think,
I believe in the pirate radio aspect of podcasting,
the freedom and that there's something--
- The open source spirit.
- The open source spirit, it just doesn't seem right.
It doesn't feel right.
That said, you know,
because so many people care about Joe Rogan's program,
they're gonna hold Spotify's feet to the fire.
Like one of the cool things,
what Joe told me is the reason he likes working with Spotify
is that they're like ride or die together, right?
So they want him to succeed.
So that's why they're not actually telling him what to do,
despite what people think.
They don't tell him,
they don't give him any notes on anything.
They want him to succeed.
And that's the cool thing about exclusivity
with a platform is like,
you kind of want each other to succeed.
And that process can actually be very fruitful.
Like YouTube, it goes back to my criticism.
YouTube generally, no matter how big the creator,
maybe for PewDiePie, something like that,
they want you to succeed.
But for the most part,
from all the big creators I've spoken with,
Veritasium, all those folks,
you know, they get some basic assistance,
but it's not like YouTube doesn't care
if you succeed or not.
They have so many creators.
- They have like a hundred other.
- They don't care.
So, and especially with somebody like Joe Rogan,
who YouTube sees Joe Rogan,
not as a person who might revolutionize the nature of news
and idea space and nuanced conversations.
They see him as a potential person
who has racist guests on,
or like, you know,
they see him as like a headache potentially.
So, you know, a lot of people talk about this.
It's a hard place to be for YouTube actually,
is figuring out with the search and discovery process
of how do you filter out conspiracy theories
and which conspiracy theories represent dangerous untruths
and which conspiracy theories are like vanilla untruths.
And then even when you start having meetings
and discussions about what is true or not,
it starts getting weird.
- Yeah.
- It starts getting weird.
- It's difficult these days, right?
I worry more about the other side, right?
Of too much, you know, too much not censorship.
Well, maybe censorship is the right word.
I mean, censorship is usually government censorship,
but still, yeah, putting yourself in a position of arbiter
for these kinds of things.
- Yeah.
- It's very difficult.
And people think it's so easy, right?
Like, it's like, well, you know, like no Nazis, right?
What a simple principle.
But, you know, yes, I mean, no one likes Nazis.
- Yeah.
- But there's like many shades of gray,
like very soon after that.
- Yeah, and then, you know, of course everybody,
you know, there's some people that call
our current president a Nazi.
And then there's like, so you start getting Sam Harris.
I don't know if you know that is wasted, in my opinion,
his conversation with Jack Dorsey.
Now, I spoke with Jack before on this podcast,
and we'll talk again.
But Sam brought up, Sam Harris does not like Donald Trump.
- I do listen to his podcast.
I'm familiar with his views on the matter.
- And he asked Jack Dorsey, he's like,
how can you not ban Donald Trump from Twitter?
And so, you know, there's a set,
you have that conversation.
You have a conversation where some number,
some significant number of people
think that the current president of the United States
should not be on your platform.
And it's like, okay, so if that's even on the table
as a conversation, then everything's on the table
for conversation.
§08Transcript · 59:32–1:08:18
And yeah, it's tough.
I'm not sure where I land on it.
I'm with you, I think that censorship is bad,
but I also think--
- Ultimately, I just also think, you know,
if you're the kind of person that's gonna be convinced,
you know, by some YouTube video, you know,
that, I don't know, our government's been taken over
by aliens, it's unlikely that, like, you know,
you'll be returned to sanity simply because, you know,
that video is not available on YouTube, right?
- Yeah, I'm with you.
I tend to believe in the intelligence of people
and we should trust them.
But I also do think it's the responsibility of platforms
to encourage more love in the world,
more kindness to each other.
And I don't always think that they're great
at doing that particular thing.
So that, there's a nice balance there.
And I think philosophically, I think about that a lot.
Where's the balance between free speech
and like encouraging people,
even though they have the freedom of speech
to not be an asshole.
- Yeah, right.
- That's not a constitutional, like,
so you have the right for free speech,
but like, just don't be an asshole.
Like, you can't really put that in the constitution
that the Supreme Court can't be like,
just don't be a dick.
But I feel like platforms have a role to be like,
just be nicer.
Maybe do the carrot, like encourage people to be nicer
as opposed to the stake of censorship.
But I think it's an interesting machine learning problem.
Just be nicer.
- Machine, yeah, machine learning for niceness.
- It is, I mean--
- Responsible AI, I mean, it is a thing for sure.
- Jack Dorsey kind of talks about it as a vision for Twitter
is how do we increase the health of conversations?
I don't know how seriously
they're actually trying to do that though,
which is one of the reasons I am in part considering
entering that space a little bit.
- It's difficult for them, right?
Because it's kind of like well known that,
people are kind of driven by rage and outrage maybe
is a better word, right?
Outrage drives engagement and well,
these companies are judged by engagement, right?
- In the short term, but this goes to the metrics thing
that we were talking about earlier.
I do believe, I have a fundamental belief that
if you have a metric of long-term happiness of your users,
like not short-term engagement,
but long-term happiness and growth
and both like intellectual, emotional health of your users,
you're going to make a lot more money.
You're going to have long,
like you should be able to optimize for that.
You don't need to necessarily optimize for engagement.
- Yeah. - And that'll be good
for society too.
- Yeah, no, I mean, I generally agree with you,
but it requires a patient person with,
trust from Wall Street to be able to carry out
such a strategy.
- This is what I believe the Steve Jobs character
and Elon Musk character is like,
you basically have to be so good at your job.
- Right, you got to pass for anything.
- That you can hold the board
and all the investors hostage by saying like,
either we do it my way or I leave.
And everyone is too afraid of you to leave
'cause they believe in your vision.
So that, but that requires being really good
at what you do.
- Requires being Steve Jobs and Elon Musk.
- There's kind of a reason why like a third name
doesn't come immediately to mind, right?
Like there's maybe a handful of other people,
but it's not that many.
- It's not many.
I mean, people say like, why,
like people say that I'm like a fan of Elon Musk.
I'm not, I'm a fan of anybody
who's like Steve Jobs and Elon Musk.
And there's just not many of those folks.
- It's the guy that made us believe
that like we can get to Mars, you know, in 10 years, right?
I mean, that's kind of awesome.
- And it's kind of making it happen, which is like.
- It's great.
- It's kind of gone like that kind of like spirit, right?
Like from a lot of our society, right?
You know, like we can get to the moon in 10 years
and like we did it, right?
- Yeah, especially in this time of so much kind of
existential dread that people are going through
because of COVID, like having rockets
that just keep going out there now with humans.
I don't know that it's just like you said,
I mean, it gives you a reason to wake up in the morning
and dream, for us engineers too.
It is inspiring as hell, man.
Well, let me ask you this, the worst possible question,
which is, so you're like at the core, you're a programmer,
you're an engineer, but now you made the unfortunate choice
or maybe that's the way life goes
of basically moving away from the low level work
and becoming a manager, becoming an executive,
having meetings, what's that transition been like?
- It's been interesting, it's been a journey.
Maybe a couple of things to say about that.
I got into this, right?
Because as a kid, I just remember this like incredible
amazement at being able to write a program, right?
And something comes to life that kind of didn't exist before.
I don't think you have that in like many other fields.
Like you have that with some other kinds of engineering,
but you may be a little bit more limited
with what you can do, right?
But with a computer, you can literally imagine
any kind of program, right?
So it's a little bit God-like what you do
like when you create it.
And so, I mean, that's why I got into it.
- Do you remember like first program you wrote
or maybe the first program that like made you fall in love
with computer science?
- I don't know if it was the first program.
It's probably like trying to write one of those games
and basic, you know, like emulate the snake game or whatever.
I don't remember to be honest, but I enjoyed like,
that's why I always loved about, you know,
being a programmer is just the creation process.
And it's a little bit different when you're not the one
doing the creating.
And, you know, another aspect to it I would say is,
you know, when you're a programmer,
when you're an individual contributor,
it's kind of very easy to know when you're doing a good job,
when you're not doing a good job,
when you're being productive,
when you're not being productive, right?
You can kind of see like you trying to make something
and it's like slowly coming together, right?
And when you're a manager, you know, it's more diffuse,
right?
Like, well, you hope, you know, you're motivating your team
and making them more productive and inspiring them, right?
But it's not like you get some kind of like dopamine signal
because you like completed X lines of code, you know, today.
So kind of like you missed that dopamine rush a little bit
when you first become, but then, you know,
slowly you kind of see, yes,
your teams are doing amazing work, right?
And you can take pride in that.
- You can get like, what is it?
Like a ripple effect of somebody else's dopamine rush.
- Yeah, yeah, yeah.
You live off other people's dopamine.
- So is there pain points and challenges you had to overcome
from going to a programmer to becoming a programmer
of humans?
- Programmer of humans.
I don't know, humans are difficult to understand, you know?
It's like one of those things,
like trying to understand other people's motivations
and what really drives them.
It's difficult, maybe like never really know, right?
- Do you find that people are different?
- Yeah.
- Like I, one of the things,
like I had a group at MIT that, you know,
I found that like some people I could like scream at
and criticize like hard,
and that made them do like much better work
and really push them to their limit.
And there's some people that I had to nonstop compliment
because like they're so already self-critical,
like about everything they do,
that I have to be constantly like,
like I cannot criticize them at all
because they're already criticizing themselves.
And you have to kind of encourage
and like celebrate their little victories.
And it's kind of fascinating,
like how that, the complete difference in people.
- Definitely people will respond to different motivations
and different modes of feedback,
and you kind of have to figure it out.
It was like a pretty good book,
which for some reason now the name escapes me,
about management, "First Break All the Rules."
- "First Break All the Rules?"
§09Transcript · 1:08:19–1:17:01
- "First Break All the Rules."
It's a book that we generally like ask a lot of
like first time managers to read a ref.
Like one of the kind of philosophies
is managed by exception, right?
Which is, don't like have some standard template,
like here's how I tell this person to do this
or the other thing, here's how I get feedback,
like managed by exception, right?
Every person is a little bit different,
you have to try to understand what drives them
and tailor it to them.
- Since you mentioned books,
I don't know if you can answer this question,
but people love it when I ask it,
which is, are there books, technical, fiction,
or philosophical that you enjoyed
or had an impact on your life that you would recommend?
You already mentioned "Dune," like all of the "Dune."
- All of the "Dune."
The second one was probably the weakest,
but anyway, so yeah, all of the "Dune" is good.
- I mean, yeah, can you just slow little tangent on that?
How many "Dune" books are there?
Like, do you recommend people start with the first one
if that was--
- Yeah, you kind of have to read them all.
I mean, it is a complete story, right?
So you start with the first one,
you gotta read all of them.
- There's not like a tree,
like a creation of the universe
that you should go and sequence?
- You should go and sequence, yeah.
It's kind of a chronological storyline.
There's six books in all.
Then there's like many kind of books
that were written by Frank Herbert's son,
but those are not as good,
so you don't have to bother with those.
- Shots fired.
- Shots fired.
- Okay.
- But the main sequence is good.
So what are some other books?
Maybe there's a few.
So I don't know that like I would say
there's a book that kind of, I don't know,
turned my life around or anything like that,
but here's a couple that I really love.
So one is "Brave New World" by Aldous Huxley.
And it's kind of incredible how prescient he was
about what a brave new world might be like.
You kind of see a genetic sorting in this book,
where there's like these alphas and epsilons
and from like the earliest time of society,
like they're sorted.
Like you can kind of see it in a slightly similar way today
where, well, one of the problems with society
is people are kind of genetically sorting a little bit.
Like there's much less, like most marriages
between people of similar kind of intellectual level
or socioeconomic status, more so these days
than in the past.
And you kind of see some effects of it
in stratifying society and kind of,
he illustrated what that could be like in the extreme.
- Different versions of it on social media as well.
It's not just like marriages and so on.
Like it's genetic sorting in terms of
what Dawkins called memes, his ideas.
- Right, right.
- Being put into these bins
or these little echo chambers and so on.
- Yeah, and that's the book that's,
I think a worthwhile read for everyone.
In 1984 is good, of course, as well.
Like if you're talking about,
dystopian novels of the future.
- Yeah, it's a slightly different view of the future, right?
- But I kind of like identify with
Brave New World a bit more.
Speaking of, not a book, but my favorite kind of
dystopian science fiction is a movie called "Brazil,"
which I don't know if you've heard of.
- I've heard of it and I know I need to watch it,
but yeah, 'cause it's in, is it in English or no?
- It's an English movie, yeah.
And it's a sort of like dystopian movie
of authoritarian incompetence, right?
It's like nothing really works very well.
The system is creaky,
but no one is kind of like willing to challenge it.
Just things kind of amble along.
It kind of strikes me as like a very plausible future
of like, you know, what authoritarians might look like.
It's not like this, you know,
super efficient evil dictatorship of 1984.
It's just kind of like this badly functioning, you know,
but it's status quo, so it just goes on.
- Yeah, that's one funny thing that stands out to me
is in what is this, authoritarian dystopian stuff,
or just basic like, you know,
if you look at the movie "Contagion,"
it seems in the movies,
government is almost always exceptionally competent.
Like, it's like used as a storytelling tool
of like extreme competence.
Like, you know, you use it whether it's good or evil,
but it's competent.
It's very interesting to think about
where much more realistically is incompetence,
and that incompetence is itself has consequences
that are difficult to predict.
Like, bureaucracy has a very boring way of being evil.
Of just, you know, if you look at the show,
HBO show "Chernobyl," it's a really good story
of how bureaucracy, you know,
leads to catastrophic events,
but not through any kind of evil
in any one particular place, but more just like the--
- It's just the system, kind of.
- The system, distorting information
as it travels up the chain,
that people unwilling to take responsibility for things,
and just kind of like this laziness resulting in evil.
- There's a comedic version of this,
I don't know if you've seen this movie,
it's called "The Death of Stalin."
- Yeah.
- All right.
- I like that.
I wish it wasn't so,
there's a movie called "Inglorious Bastards"
about, you know, Hitler and, you know, so on.
For some reason, those movies piss me off.
I know a lot of people love them,
but like, I just feel like there's not enough good movies,
even about Hitler.
There's good movies about the Holocaust,
but even Hitler, there's a movie called "Downfall"
that people should watch,
I think it's the last few days of Hitler,
that's a good movie, turned into a meme.
- Mm-hmm, mm-hmm.
- But it's good, but on Stalin,
I feel like I may be wrong on this,
but at least in the English-speaking world,
there's not good movies about the evil of Stalin.
- That's true, I was trying to say that.
I actually, so I agree with you on "Inglorious Bastards",
I didn't love the movie,
because I felt like kind of the stylizing of it, right?
The whole like Tarantino kind of Tarantinoism,
if you will, kind of detracted from it
and made it seem like unserious a little bit.
But "Death of Stalin", I felt differently.
Maybe it's because it's a comedy to begin with,
so it's not like I'm expecting, you know, seriousness,
but it kind of depicted the absurdity
of the whole situation in a way, right?
I mean, it was funny, so maybe it does make light of it,
but it, some degree, it's probably like this, right?
Like a bunch of kind of people that are like, oh shit,
right, like--
- You're right, but like the thing is,
it was so close to like what probably was reality,
it was caricaturing reality,
to where I think an observer might think that this is not,
like they might think it's a comedy,
when in reality, that's the absurdity
of how people act with dictators.
I mean, I guess it was too close to reality for me.
- The kind of banality of like what were eventually
like fairly evil acts, right?
But like, yeah, they're just a bunch of people
trying to survive.
'Cause I think there's a good,
I haven't watched it yet, the good movie on,
the movie on Churchill with Gary Oldman,
I think it's Gary Oldman, I may be making that up,
but I think he won,
like he was nominated for an Oscar or something.
So I like, I love these movies about these humans
and Stalin, like Chernobyl made me realize,
the HBO show that there's not enough movies about Russia
that capture that spirit.
I'm sure it might be in Russian, there is,
but the fact that some British dude that like did comedy,
I feel like he did like "Hangover" or some shit like that.
I don't know if you're familiar
with the person who created "Chernobyl,"
but he was just like some guy
that doesn't know anything about Russia.
And he just went in and just studied it,
like did a good job of creating it
and then got it so accurate, like poetically.
And the facts that you need to get accurate,
he got accurate, just the spirit of it
down to like the bowls that pets use,
§10Transcript · 1:17:03–1:25:50
just the whole feel of it.
- It was good, yeah, I saw the series.
- Yeah, it's incredible.
It made me wish that somebody did a good,
like 1930s, like starvation at Stalin,
like leading up to World War II
and in World War II itself, like Stalingrad and so on.
Like, I feel like that story needs to be told.
Millions of people died.
And to me, it's so much more fascinating than Hitler
'cause Hitler is like a caricature of evil almost
that it's so, especially with the Holocaust,
it's so difficult to imagine
that something like that is possible ever again.
Stalin to me represents something that is possible.
Like the so interesting, like the bureaucracy of it,
it's so fascinating that it potentially might be happening
in the world now, like that we're not aware of,
like with North Korea, another one that,
like there should be a good film on
and like the possible things that could be happening
in China with overreach of government.
I don't know, there's a lot of possibilities there,
I suppose.
- Yeah, I wonder how much,
I guess the archives should be maybe more open nowadays.
I mean, for a long time, they just, we didn't know, right?
Anyways, no one in the West knew for sure.
- Well, there's a, I don't know if you know him,
there's a guy named Stephen Kotkin.
He is a historian of Stalin that I spoke to on this podcast.
I'll speak to him again.
The guy knows his shit on Stalin.
He like read everything.
And it's so fascinating to talk to somebody,
like he knows Stalin better than Stalin knew himself.
It's crazy.
Like you have, so I think he's at Princeton.
He is basically, his whole life is Stalin.
- Studying Stalin.
- Yeah, it's great.
And in that context, he also talks about
and writes about Putin a little bit.
I've also read at this point,
I think every biography of Putin,
English biography of Putin, I need to read some Russians.
Obviously, I'm mentally preparing
for a possible conversation with Putin.
- What is your first question to Putin
when you have him on the podcast?
- It's interesting you bring that up.
First of all, I wouldn't tell you, but.
(laughing)
- Can't give it away now.
- But I actually haven't even thought about that.
So my current approach,
and I do this with interviews often,
but obviously that's a special one,
but I try not to think about questions until last minute.
I'm trying to sort of get into the mindset.
And so that's why I'm soaking in a lot of stuff,
not thinking about questions,
just learning about the man.
But in terms of like human to human,
it's like, I would say it's,
I don't know if you're a fan of mob movies,
but like the mafia, which I am,
like Goodfellas and so on,
he's much closer to like mob morality, which is like.
- Mob morality, maybe, I could see that.
But I like your approach anyways of this,
the extreme empathy, right?
It's a little bit like, you know, Hannibal, right?
Like if you ever watched the show Hannibal, right?
They had that guy,
we know Hannibal, of course, like.
- Yeah, sounds like the lamb.
- But there's TV shows as well,
and they focused on this guy, Will Durant,
who's a character like extreme empath, right?
So in the way he like catches all these killers,
is he pretty much,
he can empathize with them, right?
Like he can understand why they're doing
the things they're doing, right?
And it's a pretty excruciating thing, right?
Like, because you're pretty much like
spending half your time in the head of evil people, right?
- Yeah.
- But.
- I mean, I definitely try to do that with other,
so you should do that in moderation,
but I think it's a pretty safe place to be.
One of the cool things with this podcast,
and I know you didn't sign up to hear me
listen to this bullshit, but.
(laughing)
- No, it's interesting.
- What's his name, Chris Latner, who's a Google,
oh, he's not Google anymore, Sci-Fi.
He's one of the most legit engineers I've talked with.
I talked with him again on this podcast,
and one of the, he gives me private advice a lot,
and he said for this podcast, I should like interview,
like I should widen the range of people,
because that gives you much more freedom to do stuff.
Like, so his idea, which I think I agree with Chris,
is that you go to the extremes.
You just like cover every extreme base,
and then it gives you freedom to then
go to the more nuanced conversations.
And it's kinda, I think there's a safe place for that.
There's certainly a hunger for that nuanced conversation,
I think, amongst people, where like on social media,
you get canceled for anything slightly tense,
that there's a hunger to go full.
- Right, you go so far to the opposite side.
And it's like demystifies it a little bit, right?
- Yeah, yeah.
- There is a person behind all of these things.
- And that's the cool thing about podcasting,
like three, four hour conversations
that it's very different than a clickbait journalism.
It's like the opposite, that there's a hunger for that.
There's a willingness for that.
- Yeah, especially now, I mean,
how many people do you even see face to face anymore?
- Right. - Right, like this, you know?
It's like not that many people, like in my day to day,
aside from my own family, that like I sit across.
- It's sad, but it's also beautiful.
Like I've gotten the chance to,
like our conversation now, there's somebody,
I guarantee you there's somebody in Russia
listening to this now like jogging.
There's somebody who is just smoked some weed,
sit back on a couch and just like enjoying.
I guarantee you that we'll write in the comments right now
that yes, I'm in St. Petersburg, I'm in Moscow, I'm whatever.
And we're in their head and they have a friendship with us.
I'm the same way, I'm a huge fan of podcasting.
It's a beautiful thing.
I mean, it's a weird one way human connection.
Like before I went on Joe Rogan,
and still I'm just a huge fan of his.
So it was like surreal.
I've been a friend with Joe Rogan for 10 years, but one way.
- Yeah, from this way, from the St. Petersburg way.
- Yeah, the St. Petersburg way.
And it's a real friendship.
I mean, now it's like two way, but it's still surreal.
And that's the magic of podcasting.
I'm not sure what to make of it.
That voice, it's not even the video part.
It's the audio that's magical.
I don't know what to do with it,
but it's people listen to three, four hours.
- Yeah, we evolved over millions of years, right?
To be very fine tuned to things like that, right?
Oh, expressions as well, of course, right?
But back in the day on the Savannah,
you had to be very attuned to whether
you had a good relationship with the rest of your tribe
or a very bad relationship, right?
Because if you had a very bad relationship,
you were probably gonna be left behind
and eaten by the lions.
- Yeah, but it's weird that the tribe is different now.
Like you could have a one way connection with Joe Rogan
as opposed to the tribe of your physical vicinity.
- But that's why it works with the podcasting,
but it's the opposite of what happens on Twitter, right?
Because all those nuances are removed, right?
You're not connecting with the person
'cause you don't hear the voice.
You're connecting with like an abstraction, right?
It's like some stream of tweets, right?
And it's very easy to assign to them
any kind of like evil intent, you know,
or dehumanize them, which is much harder to do
when it's a real voice, right?
Because you realize it's a real person behind the voice.
- Let me try this out on you.
I sometimes ask about the meaning of life.
Do you, your father now, an engineer,
you're building up a company.
Do you ever zoom out and think like,
what the hell is this whole thing for?
Like why are we descended to vapes even on this planet?
What's the meaning of it all?
- That's a pretty big question.
I think I don't allow myself to think about it too often,
or maybe like life doesn't allow me
to think about it too often.
But in some ways, I guess, the meaning of life
is kind of contributing to this kind of weird thing
we call humanity, right?
Like it's in a way, you can think of humanity
as like a living and evolving organism, right?
That like we all contribute in a slight way,
§11Transcript · 1:25:52–1:28:40
but just by existing, by having our own unique set
of desires and drives, right?
And maybe that means like creating something great,
and it's bringing up kids who, you know,
are unique and different and seeing like, you know,
they can join what they do.
But I mean, to me, that's pretty much it.
I mean, if you're not a religious person, right,
which I guess I'm not, that's the meaning of life.
It's in the living and in the creation.
- Yeah, there's something magical
about that engine of creation.
Like you said, programming, I would say,
I mean, it's even just actually what you said
with even just programs, I don't care
if it's like some JavaScript thing,
a button on the website, it's like magical
that you brought that to life.
I don't know what that is in there, but that seems,
that's probably some version of like reproduction
and sex, whatever that's in evolution.
But like creating that HTML button has echoes
of that feeling and it's magical.
- Right, well, I mean, if you're a religious person,
maybe you could even say, right,
like we were created in God's image, right?
Well, I mean, I guess part of that is the drive
to create something ourselves, right?
I mean, that's part of it.
- Yeah, that HTML button is the creation in God's image.
- So maybe hopefully it'll be something a little more--
- So dynamic, maybe some JavaScript.
- Yeah, maybe some JavaScript, some React and so on.
But no, I mean, I think that's what differentiates us
from the apes, so to speak.
- Yeah, we did a pretty good job.
Dan, it was an honor to talk to you.
Thank you so much for being part of creating
one of my favorite services and products.
This is actually a little bit of an experiment,
allowing me to sort of fanboy over some of the things
I love, so thanks for wasting your time with me today.
It was really fun. - It was awesome.
Thanks for having me on and giving me a chance
to try this out. (laughs)
- Awesome.
Thanks for listening to this conversation
with Dan Kokorov and thank you to our sponsors,
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Thank you for listening and hope to see you next time.
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