The following is a conversation with Dan Gokodov, 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, Athletic
Greens, Only One Nutrition Drink, Blinkist App that summarizes books, Business Wars Podcast,
and Cash App. So the choice is health, wisdom, or money. Choose wisely, my friends, 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 software, that comes along and just makes my
life way easier. Examples are Adobe Premiere for video editing, Azitope RX for cleaning up audio,
Auto Hotkey on Windows for automated keyboard, 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 guests. 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,
review an Apple podcast, follow on Spotify, support on Patreon, or connect with me on
Twitter at Lex Freedman. And now here's my conversation with Dan Gokodov.
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. 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 because a 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's 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
specification of Pong. I think Pong was pretty much like 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...
So I left Russia in 1991, right? 1991, okay. So I was one of the few like-it-kids because my mom was
a programmer. So I would go to her work, right? I would take the metro. I've got her work and play
like on, I guess, the equivalent of like a 286 PC, you know? Nice, with floppy disks. Yes. It's okay,
put back to Dune. What do you get? Back to Dune. And by the way, the new movie, I'm pretty interested
in, but they're 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, like most any adaptation.
And like Dune is so much about kind of mood in 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 Lito,
one of the characters, he's become this weird sort of God Emperor. He's turned into a gigantic worm.
I mean, 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.
So he kind of like merges with this worm and becomes this tyrant of the world and 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 like go on to colonize new worlds
and kind of renew the forward momentum of humanity, right? And so to me, that's kind of
like fascinating, right? You need a little bit of pressure and suffering, right? To kind of like
make progress, not get too comfortable. 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
up work, I think. 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,
you know, 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. 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, you know, all in a standardized format.
I don't know. It was truly a joy. So I thought I had, you know, just for the hell of it,
talk to you that 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 Isotope RX. It's for audio editing.
And like, 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,
it can, 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. They've used
audition, Adobe audition, and these are all kinds of other things with plugins and you have to kind of
figure it all out. You have to do it manually. Here's just, it just worked. So that's another
one in this whole pipeline that just brought joy to my, 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. Same thing, I guess. 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 today 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. 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 similar idea. Yeah. Okay. So what is Rev? Before I launch into what is Rev, I was going
to say, you know, like you're talking about like Rev was music to yours. Yeah. Your spiel was music
to my ears. Yeah. 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 an early employee of Upwork. So he's very familiar with that. Upworked the company.
Upworked 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 us, if you want to hire, you know, someone to help you
go to a little site, right? You could go on Upwork. You could like browse through a list of freelancers,
pick a programmer, you know, have a contract with them and have them do some work. But it was kind
of a difficult experience because for the, 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 somebody
else better? And naturally, you know, 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 it's kind of like a lot of potential regret, right? What if I choose a bad
person, they can be late on the work, it's going to be a painful experience. And for the freelancer,
it was also painful because, you know, 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?
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 where we'll pick a few verticals that are fairly standardizable.
You know, 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. You know, 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 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 one work that was done by people on the 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 price it by that. And then you
pick the language you want. And that's mostly all it is to it. So those were a few criteria.
We started with translation because we saw the need. And we picked a kind of a specialty of
translation, where we would translate things like board 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 was was that the,
so what, what is it now? Is it per word or something like that? Like, how do you,
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, that, yes.
For translation, we don't really actually focus it on anymore. But, you know, back when it was
still a main business of rabbit was per page, right? Or per word, depending on the kind of a,
because you can also do translation now on the audio, right?
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, how, well, is Russian supported?
Think so. Yeah.
It'd be interesting to try it out. I mean, one of the,
now it's only in like the one direction, right? So you start with English,
and then you can have subtitles in Russian, not really, not really the other way.
Got it. Because it's, I'm deeply curious about this. I'm, when COVID opens up a little bit,
when the economy, when the world opens up a little bit.
You want to build your brand in Russia?
No, I don't. First of all, I'm allergic to the word brand.
All right. I'm definitely not building any brands in Russia.
Nice. But I'm going to Paris to talk to the translators of
Dostoyevsky and Tolstoy. There's this famous couple that does translation.
And, you know, I'm more and more thinking of how is it possible to have a conversation
with a Russian speaker? Because 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 to wonder how can I create a compelling English Russian experience
for an English speaker? Like if I, there's a guy named Gregoriy Perlman, who's a mathematician,
who obviously didn'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, like a three, three person thing where it's like a dance of work. Like I
understand it one way. They don't understand the other way. But I'll be asking questions in English.
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 because I think I could do a good job with,
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
times? That's, 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, not professionally.
He writes poetry. That was kind of always his, not a hobby, but he's, he had a job,
like a day job, but his passion was always writing poetry. And then we get to America and
like he started also translating. First he was translating English poetry to Russian,
now he also like goes the other the other way. You kind of gain some small fame in that world
anyways, because recently this poet like Lewis Clark, I don't know if you know,
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 you kind of like they
asked him and gave an intro you to radius, 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,
it's interviews. Do you remember any, any experiences and challenges to having to do
the translation that that's the got to 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 is inflections in Russian and
gender is 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 there's such
different languages. 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're mentioning that Rev was
kind of born out of trying to take a vertical on the upwork and then standardize it. So
we just kind of make the the freelancer marketplace idea better, right? Better for both
customers and better for the freelancers themselves. Is there something else to the
story of a Rev finding Rev? Like what what did it take to bring it to actually to life?
Was there any pain points? Plenty of 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. 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, Rev is a world-class freelancers.
So if there's not enough Revvers, then customers have a bad experience, right? It takes longer to
get your work done, things like that. If there's too many done, the 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. 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 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 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. To some degree, I don't like the word
gig that much, right? Because to some degree, it diminishes the works 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 want to make some
income and rough 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 wants to live the mountain top life,
right? You know, cabin in the woods, but they still want to make some money. And generally,
that wouldn't be compatible before this new world. You kind of have to choose. But like with
Rev, 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? It's from all over the world. Most of them are in the US.
That's the majority. Because most of our work is audio transcription. And so you have to speak
pretty good English. Yes. 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 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 but anyway, really, are they from all walks of life at these young folks,
older folks? Yeah, all walks of life. Really, like I said, one one category is, you know,
the work from home on students, you know, who want to make some extra income. There are some
people who may be, you know, maybe they're have some social anxiety, so they don't want to be in
the office, right? And this is one way for them to make a living. So it's really pretty, 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 want to choose 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
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
machine learning or 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 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 and I learn 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 Revvers
the best tools possible. You know, so typical day forever, 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 build to make transcription as efficient as possible. They'll start with a
speech-reg 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 the ESR would do a fairly good job. But if you imagine someone record a day 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 the ESR wouldn't do a good job.
So the person might say, like, you know what, I'm just going to 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?
Can you get, 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, that we actually encourage everyone at the company to try to be a transcriber for
their descriptions 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 going to use Rev to caption this.
They're listening to this right now. What's, what do you think is the fastest you can 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, of the podcast.
This is, this is so meta. I could just imagine the reverse working on this right now.
You're like, you're way wrong.
You're way wrong. This takes way longer. But yeah, definitely.
Oh, you doubted me. I could do real time.
Yeah. 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, you know, speech, like we're talking and
transforming it into a sequence of words, essentially, audio of people talking, audio,
audio to words. And, you know, there's a variety of different approaches and techniques,
which we could talk about later if you want. So, you know, we think we have pretty much
the world's best ASR for this kind of speech, right? So there's, there's different kinds of
domains, right? For ASR, like one domain might be voice assistants, right? So Siri,
very different than what we're doing, right? Because Siri, there's fairly limited vocabulary,
you know, you might ask Siri to play a song or, you know, word repeats or whatever. And it's
very good at doing that. Very different from when we're start talking in a very unstructured way.
And Siri will also generally like 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%? 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 calculated this, 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 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 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, 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 feet. This is hilarious. Okay. Now Google is
listening, sending it back to headquarters for these rough people. But that's the goal? No. Yeah,
I mean, we measure ourselves against like Google, Amazon, Microsoft, you know, some of the 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 podcast, some videos, some intro, 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. So it's a by the way, it
used to be a dollar per minute for captioning and transcription, things like a dollar 15 or
something like that, dollar 25, dollar 25. Now, yeah, it's pretty cool. That was the other thing
that was surprising to me. It was actually like the cheapest thing you could one of the 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,
one click, the 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
and it generates the files and Dropbox. So it closes the loop to where I don't have to go to
Rev at all, and I can download it. So I don't have to go to Rev at all and to download the files,
it could just like automatically copy them. You're putting your Dropbox on, you know,
a day later, or maybe a few hours later, 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, because 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
because looking on the download, but 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, a store company called Zapier, which kind of can connect Dropbox to Rev
and vice versa. We have an API if you want to really like customize it, you know, if you want to
create the Lex Friedman, you know, CMS or, or whatever. But this whole thing, okay, cool.
So can you speak to the ASR a little bit more like what is it?
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% rate or error rate is definitely that's 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, this is 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 label the data.
Yeah, that does get good results. And we at Rev have kind of like the best data,
like we have, like you're literally, you're literally model is annotating the data,
our business model is being paid to annotate the data. So it's kind of like a pretty magical
flywheel. And so we've kind of like written this flywheel to, 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, the audios. And we train on that. But
we in principle also have all the edits that the reveres make, right? Oh, that's interesting.
How can you use that as data? That's, 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 recurrent neural net for fixing, for fixing transcripts.
I always remember we did segmentation annotation for, for driving data. So segmenting the scene,
like visual data. And you could, you can get all those drawing people 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's hot, that, 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, you know, make that edit and stuff like that. 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 went to.
Yeah. So Rev.ai is kind of our way of bringing this ASR to, you know, the rest of the world,
right? So when we started, we were human only, you know, then we kind of created this
semi-service, I think you might have used it, which was kind of ASR for the consumer, right? So if
you don't want to pay a dollar 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, right? Then we started using TSR for our own human transcriptionists.
And then the kind of Rev.ai is the final step of the journey, which is, you know, 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, you know, 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 at Mechanical Turk, for example, how shitty the
interface is. We're talking about like Rev making me feel good. Like when I first discovered Mechanical
Turk, the initial idea of it was like, it made me feel like Rev does, but then the interface is like,
come on. Yeah, it's horrible. Why is it so painful? Does nobody at Amazon want to like seriously
invest in it? It felt like you could 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, like a meeting,
they meet once a month, like, what are we going to 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, Craigslist 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.
Possibly. Possibly. But no, I know what you mean. We used Mechanical Turk for a couple of things as
well. And it's painful. 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,
right? So yeah. But even the API documentation and so on, like it's super outdated. Like,
yeah, it's, I don't, I don't even know what the, I mean, the same, 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
shady. I should, I should actually be, I should exhibit some gratitude. Okay, let's practice
some gratitude. The, 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 want to ask that doesn't, 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 that'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 want to be. Well, it's a, 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, you know, 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, 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 white, like their new YouTube
studio, for example, there's like features that that were like begged for for a really long time,
like being able to upload multiple videos at the same time. That wasn't 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 is 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 on 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, we need to
speak to the people that like want to love our product and they don't. Maybe at some point,
you just get so fixated on the numbers, right? And it's like, well, the numbers are pretty great,
right? Like people are watching, you know, doesn't seem to be a problem, right? And you're not like
the person that like built this thing, right? So you really care about it. You know, you just there,
you came in as a product manager, right? You got hired sometime later, your mandate is like,
increase the number like, you know, 10%, right? And 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 how much people watching the videos and so on. And, and, 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, you have to want people to love your stuff,
because love is ultimately the beginning of like, a successful long term company is they always should
love your product. You have to be like a creator and have that like creators love for your own
thing, right? Like, and you're pained by, you know, these, these comments, right? And probably like,
Apple, I think did this generally, like really well, you know, they're, 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 Kosyanda. It's kind of a great book, actually, because unlike most of these business
books, where it's, you know, here's how Steve Jobrand, the company is more like, here's how life
was like for me, you know, an engineer here, the projects I worked on and here, what it was like
to pitch Steve Jobs, you know, on like, you know, think he 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, right? He was famously, let's take
a look for this kind of stuff. But because the teams were small, you really own this stuff,
right? So you're really carried. 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 what I was saying, we're going to 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 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? Yeah. I'm
now that I'm like no longer a programmer, right? And I'm a quote unquote manager. That's less like
that's less like my day as in meetings, right? Yeah. And, you know, pretty often I want to like
see what was said, right? Who said it, you know, what's the context, but it's generally not really
something that 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.
Was was zoom and so on. That's 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 want to empower creators. So one of my hopes was with Spotify that they would use the
technology like Rev or something like that to start converting everything into into text and
make it indexable. Like one of the things that 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
it's similar. 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 and 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 this cover, like all the time,
so I listened to like a number of podcasts and there's something said and I want to like go
back to that later because I was trying to remember, what do you say? Like maybe like
recommend some cool product that I want to 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 a game changer.
It would 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
rough thing has 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 transcription and so on. It seemed clear to me,
especially like CEOs and sort of like PhDs, like people write to me or like graduate students
in computer science or graduate students or whatever the heck field, it's clear that their
mind, like they enjoy podcasts when they're doing laundry or whatever, but they want to revisit
the conversation in a much more rigorous way. And they really want to transcript. It's clear
that they want to like analyze conversations. Like 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 want to write a blog post about your conversation. So they want
to 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 is what the set, you can go
listen to like this clip from the section. I'm actually trying to try 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 and so on. I mean, most of the reporters probably
have want to write 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, the Ryan Hall. And we talked about, you know, as I've been reading
The Rise and Fall, The Third Reich and a bunch of books on Hitler. 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
thing is 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 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, there's all these articles written about like MMA fight UFC fight, right?
No, like, well, no, they didn't, they were somewhat accurate. They didn't say like a love
to 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 makes it sound a lot worse than
than than it was. But I'm fine with it. That's the way that that's the way the world I want to
I want to 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, they can see it for themselves,
for themselves. There's the headline, but there's something about podcasts, like the audio that
makes it difficult to 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, they taking Reven 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, like you kind of want support from the entire ecosystem, 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? Like, it's 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 supported it, right? So any podcast you could go and see the transcripts,
right? And you're like, normal podcasts. Yeah, I mean, somebody, so I have somebody who works with
me is works with helps with advertising with advertising. Matt is awesome guy. He mentioned
Buzzsprout to me, but he says it's really annoying because they want exclusive, they want to 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 is 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 that's a that's a beautiful thing that that's why I go on exclusive
like Joe Rogan run exclusive. I'm not sure if you're familiar with, he went just just Spotify
is a huge fan of Joe Rogan. I've been kind of nervous about the whole thing. But
let's see, let's I hope the Spotify steps up. They've added video, which was very surprising
that they were so explicit meaning you can't subscribe to RSS feed anymore. It's only in
Spotify. For now, you can until December 1. In December 1, it all everything disappears in
Spotify only. I, you know, in Spotify gave him $100 million for that. So it's 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 it. 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 about the open source
spirit. The open source spirit is 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 going to hold
Spotify's feet to the fire. Like one of the cool things with Joe told me is the reason
he likes working with Spotify is that they, they're like ride or die together, right? So
they, they want him to succeed. So that's why they're not actually telling him what to do,
despite what people think they, they don't tell them, they don't give them any notes on anything.
They want him to succeed. And that's the cool thing about exclusivity with a platform is like
you're kind of wanting 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,
and 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,
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's difficult these days, right? I worry more
about the other side, right? Of too much, you know, too much 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, 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 it'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 a Sam Harris,
I don't know if you know that is wasted, in my opinion, his conversation with Jack Dorsey.
I spoke with Jack before in 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, he asked Jack Dorsey is like, how can you not ban Donald Trump from Twitter? 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. And yeah, it's, 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 going to 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, we should trust them. But I also do think it's a 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,
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, that's
Responsible. Yeah, I mean, it is, 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 that I'm in part considering entering that space a little bit.
It's difficult for them, right? Because, you know, it's kind of like well known that,
you know, people are kind of driven by, you know, rage and, you know, outrage maybe is a
better word, right? Outrage drives engagement. And, well, these companies are judged by engagement,
right? So it's 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 to like, you should be able to optimize for that. You don't need to necessarily
optimize for engagement. Yeah, and they'll be good for society too.
Yeah, no, I mean, I generally agree with you, but it requires a patient person with, you know,
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
because they believe in your vision. But that requires being really good at what you do.
It 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? There's maybe a handful of other people, but it's not
that many. It's not many. I mean, people say like, why are you 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 a 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?
Yeah. 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 just like you said, I mean, it gives you a reason to wake up in the morning
and dream the forest 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 many other fields. You have that with
some other kinds of engineering, but you're maybe 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 godlike what you do 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 made you fall in
love with computer science? I don't know. 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. So I always loved about, you know, being a program
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 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're 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 a then, you know, slowly, you kind of see,
yes, your teams are doing amazing work, right? And you, you can take pride in that.
You can get like, what is it, like a ripple effect of a dope or somebody else's dopamine?
Yeah, yeah, you live off other people's dopamine.
So is there pain points and challenges you have to overcome from becoming 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 you 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 the limit. And there's some people that I had to nonstop compliment
it, 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 how that, the complete difference in people. Definitely people respond to different
motivations and different loads of feedback. And you kind of have to figure it out. It's like a
pretty good book, which some reason not the name escapes me about management. First break all the
rules. First break all the rules. First break all the rules. It's a book that we generally like
ask a lot of like, first time managers to read the ref. And like one of the kind of philosophies
is managed by exception, right? Which is, you know, don't like have some standard template,
like, you know, here's how I, you know, tell this person to do this, or the other thing,
here's how I get feedback, like manage 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 a little tangent on that? Is how many Dune books out there?
Like, do you recommend people start with the first one? If you, if that was, yeah, you're
gonna have to read them all. I mean, it is a complete story, right? So you start with the
first one, you got to read all of them. There's not like a tree, like that, like a creation of
like the universe. You should go in sequence. You should go in 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 up. 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, like, what
a brave new world might be like, right? You know, you kind of see a genetic sorting in this book,
right? Where there's like these alphas and epsilons and how from like the earliest time of society,
like they're sort of like, you can kind of see it in a slightly similar way today, where
one of the problems with society is people are kind of genetically sorting a little bit, right?
Like, there's much less, like most marriages, right, are 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 as ideas, right, being put
into these bins of these little echo chambers and so on. Yeah. And so that's the book that's
I think a worthwhile read for everyone. I mean, 1984 is good, of course, as well, like if you're
talking about, you know, 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 little bit more.
Yeah, 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 and I know I need to watch it.
But yeah, because it's in, is it in English or not? It's an English movie. And it's a sort of like
dystopian movie of authoritarian and competence, right? It's like, like, nothing really works very
well, you know, the system is creaky, you know, but no one is kind of like willing to challenge it,
you know, and just things kind of amble along and kind of strikes me as like a very plausible
future of like, you know, what authoritarians it might look like. It's not like this, you know,
super efficient, evil dictatorship of 1984 is 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 are 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
what much more realistically is its 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 system, the story,
the 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 called The Death of Stalin. Yeah. I like that. I wish it
wasn't so. There's a movie called Inglourious Bastards about, you know, Hitler and well, you
know, so on. For some reason, those movies pissed 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 Dawnfall that people should watch. I think
it's the last few days of Hitler. That's a good movie. Turn into a meme. 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. Let's try to see that. I actually,
so I agree with you on Inglourious Bastards. I didn't love the movie because I felt like kind of the
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 of the comedy to begin with. This is not what 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 is probably like this, right? Like a bunch of kind of people, they're like, oh,
shit, right? Like, you're right. But like, the thing is, it was so close to, like, what probably
was reality. There was caricaturing reality to where I think an observer might think that this
is not like, they might think it's a comedy. Well, in reality, this is that's the absurdity of
how people act with dictators. I mean, that's, I guess it was too close to reality for me.
Yeah, the kind of banality of like, what were eventually like fairly evil acts, right? But
like, yeah, they're, they're just a bunch of people trying to survive.
Because I think there's a good, I haven't watched yet the good movie on the movie on Churchill
with Gary Oldman. I think there's Gary Oldman, I might be making that up. 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 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,
just the whole feel of it. No, it's good. Yeah, I saw the series.
Yeah, it's incredible. It's made me, made me wish that somebody did a good, like 1930s,
like starvation as Stalin led to like leading up to World War Two. And in World War Two itself,
like Stalingrad and so on, like, I feel like that story needs to be told. Millions of people died.
And it's, it's to me, it's so much more fascinating that Hitler, because 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, the so interesting, like the bureaucracy of it, it's so fascinating that it potentially
might be happening in the world now, like they were not aware of like 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, you know, I guess the archives should be maybe more open
nowadays, right? I mean, for a long time, they're just with it now, right? Or 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, it's so fascinating to,
to, to talk to somebody like he knows Stalin better than Stalin himself. It's crazy. Like
you have, so he's, I think he's a Princeton. He is basically his whole life is studying Stalin.
Yeah, it's, 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, English
biography of Putin, I need to read some Russians. Obviously, I'm mentally preparing for a possible
conversation with Putin. So what, what, what is your first question to Putin when you have him on
your, on the podcast? I, it's interesting you bring that up. The first of all, I wouldn't tell you,
but I can't go away now. But I actually haven't even thought about that. So my current approach,
and I do this with interviews often as, 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 good fellows 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, you know, Hannibal, of course,
like, sounds like a lamb. But there was TV show as well. And if focused on this guy, Will Durant,
who's a character like extreme empath, right? So in the way he like catches all these killers,
he pretty much, he can empathize with them, right? Like you 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?
Like, but I mean, I definitely try to do that with with other. So you should do that in moderation.
But I think it's a pretty safe place, safe place to be. Like, one of the cool things with this
podcast, and I don't know, you didn't sign up to hear me listen to this bullshit. But
that was interesting. I, and what's his name, Chris Latner, who's a Google,
oh, he's not Google anymore sci-fi. He's legit. He's one of the most legit engineers I talk with.
I talk with him again on this podcast. And whether 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. It's kind of, 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 full to go so far to the opposite side. And it's like demystifies it a little bit, right?
There is a person behind all of these things. And that's the cool thing about podcasting,
like three, four hour conversations that, that it's very different than a clickbait journalism
sake, 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? 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,
like our conversation now, there's somebody I guarantee you, there's somebody in Russia
uh, listening to this now, like jogging, there's somebody who is just smoke some weeds,
sit back on a couch and just like enjoying, like I guarantee you that we're right in the
comments right now that yes, I'm in St. Petersburg, I'm in Moscow, whatever. And we're in their head
and they have a friendship with us. And I'm the same way. I'm a huge fan of podcasting.
I mean, it's a beautiful thing. I mean, it's a, it's a weird one-way human connection. Like
before I went on Joe Rogan, uh, and still I'm just a huge fan of his. So it was like surreal.
We had, I've been a friend with Joe Rogan for 10 years, but one way.
Yeah, from this way, from the, 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. It's, and that's a 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 that I don't know what to do
with it, but it's people listen to three, four hours. Yeah. We evolved over, you know, millions of
years, right? To be very fine tuned to things like that, right? Yeah. Well, expressions as well,
of course, right? But, uh, you know, back, back in the day on the, you know, on the Savannah,
you had to be very tuned to, you know, whether you had a good relationship with the, with the rest
of your tribe or very bad relationship, right? Because, you know, if you had a very bad relationship,
you're probably going to be left behind and eaten by the lions. Yeah. But it's weird that the tribe
is different now. Like you could have a connection, one way connection with Joe Rogan,
as opposed to the tribe of your physical vicinity. But that's, that's why, like, you know, 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. Yeah. Because you don't hear the
voice. You're connecting with like an abstraction, right? It's like some, 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, 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, why are we descended to vapes even on this
planet? What's, 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 slightly way, 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, taking joy in 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, that's the meaning of life.
It's in the living and then the creation and 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 on 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 recreation 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. I mean, if you're a religious person, maybe you could even say, right, like,
we were, 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, that's, that's part of it. Yeah, that HTML
button is the creation in God's. Maybe hopefully it'll be something a little more dynamic, maybe
bigger. Yeah, maybe some JavaScript, some React, and so on. But no, I mean, I think
that's what differentiates us from, you know, 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. Allow me to sort of fanboy over some of the things I love. So thanks for wasting
your time with me today. Well, it was awesome. Thanks for having me on and giving me a chance
to try this out. Awesome. Thanks for listening to this conversation with Dan Kokodov. And thank
you to our sponsors, Athletic Greens, only one nutrition drink, Blinkist app that summarizes
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means the limits of my world. Thank you for listening. I hope to see you next time.