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, All In 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 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, review on the 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 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 goddamn fur 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 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 like

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 right in that age. So you didn't get color?

You didn't get like... Well, so I left Russia in 1991, right? 1991, okay.

So I was one of the few like a 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...

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? 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. 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 again. 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 not 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 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

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? 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, that's another one where it was like,

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 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's just 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. 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 to the end user services.

So it's like wordpress.com and wordpress.org. You 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 rev wordpress.org is kind of their open

source, right? And wordpress.com is sort of their hosted commercial offering. And with us,

the differentiation is a little bit different, but maybe similar idea. 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 your ears. Yeah. Your, 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 their original, or part of their original impetus, like our CEO, Jason, was a

early employee of Upwork. So he was very familiar with their Upwork company. Upwork 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 code 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 as, 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?

Let's make it simple where we'll pick a few verticals that are fairly standardizable. 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,

you know, 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 rather 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. So when it worked, 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 can 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 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 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 Revit was per page, right? Or per word,

depending on the kind of, 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,

uh, will, is Russian supported? I 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, 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,

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? 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

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 as a 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, but the, 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 and he was like one of the few. So he kind of like they asked him and gave an interview to

Radius Vabode, 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,

any experiences and challenges to having to do the translation that that's to go 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 for us all quite different than the way English is structured, right? Just

there is inflections in Russian and genderism, 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 upwork and then

standardize it. So I 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, you know, the scaling is kind of scaling the the marketplace, so to

speak, right? Rev is essentially a two sided marketplace, right? Because, you know, there's

the customers, and then there's the reverse. If there's not enough reverse,

reverse overall color freelancers. So if there's not enough reverse, then customers have a bad

experience, right? You know, it takes longer to get your work done. Things like that, you know,

if there's too many done, there was have a bad experience because they might log on to see like

what work is available. And there's not very much work, right? So kind of keeping that balance

is a quite challenging problem. And, you know, that's less like a problem we've been working on

for many years. We're still like 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,

like 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 and still a 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, you know, many of our freelancers are maybe work from home moms, right? And, you know,

they don't want the traditional nine to five job, but they want to 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, you know, someone wants to live the

mountain top, you know, life, right? You know, cabin in the woods, but they still want to make

some money. And like, generally, that wouldn't be compatible before, before this new world.

It 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?

It's from 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 someplace 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, one category is the work from home on students who want to make some extra income.

There are some people who maybe, you know, maybe they 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, 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

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 the technical terms

like a 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 that 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 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 Revvers the best tools possible. 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 track 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 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 cross talk 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. 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 a day,

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 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

doubted me. I could do real time. Okay, so you mentioned ASR. Can you speak to what is ASR,

automatic speech recognition? 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,

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, I think it's maybe 14%

word error rate on our test with that we generally use to measure some word error rate is like one

way to measure accuracy for ASR, right? So what's 14% word error rate? 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 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,

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 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,

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, 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. 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, I'm 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 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're putting your Dropbox on, you know, a day later, or maybe a few hours later,

depending on the given rush, just shows up. Yeah. 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 it 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

looking on the Rev 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 whatever.

For this whole thing. Okay, cool. So can you speak through 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 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,

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. That's going to get good results. And

we at Rev have kind of like the best data, like we have. Like, you're literally your

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. Yeah. And so we've kind of like written 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 Revs make, right?

Oh, that's interesting. How can you use that as data?

Yeah, 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? But the data is there. That'd be interesting,

like almost like recurrent neural net for fixing transcripts. I always remember

we did segmentation annotation for driving data. So segmenting the scene, like visual data.

And 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? 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 want 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. Temi 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 $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,

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 speed track 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? 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.

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, right? In a small way. Possibly.

But I know you mean we do, 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, right? So, but even

the API documentation and so on, like it's super outdated. Like 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 shitty. 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, 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 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 was missing

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 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. Let's fix that 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're just there, you came in

as a product manager, right? You got hired sometime later, your mandate is like, increase

this 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.

Yeah, 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 paint 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 a 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 Jobs ran the company.

It's 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, 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,

right? He was famously a stickler for this kind of stuff. But because the teams were small,

you really owned this stuff, right? So you 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 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, audience,

all of your meetings, you know, they're as easily accessible as your notes, right? Like so,

like, imagine all the meetings the 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 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 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. It was 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 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 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 and discovery, 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 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 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 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 a transcript. Like it's clear that they want to like analyze conversations.

Like so many people wrote to me about a transcript for your Shabach 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. And you can like embed a little thing, you know, like into your

article, right? Here's what you said, 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 it and so on. I mean, most of the reporters probably want to

write clickbait articles that are complete falsifying, which I'm fine with. It's the way

of journalism 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 of 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 fighter, right?

No, like, well, no, they didn't, they were somewhat accurate. They didn't say like loves

Hitler. They said, um, thinks that, uh, if Hitler came back to life, we should forgive him. Like

they kind of, it's kind of accurate ish, but it, it, the headline makes it sound a lot worse than,

than, uh, than it was, but I'm fine with it. That's the way the, 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 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 taking Revan, 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, 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 propose the 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? And you're like

normal podcast app. Yeah. I mean, somebody, so I have somebody who works with me,

works with, helps with advertising, with advertising. Matt is an 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. This, 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 one exclusive. I'm not sure if you're familiar with, he went to just Spotify.

It's a huge fan of Joe Rogan. I've been kind of nervous about the whole thing, but let's see.

Let's, I hope that Spotify steps up. They've added video, which was very surprising that

they were exclusive meaning you can't subscribe to 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 a hundred million dollars for that. So it's,

it's a, it's an interesting deal, but I, I, you know, I did some soul searching and

I'm glad he's doing it. But if Spotify came to me with a hundred million dollars,

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, the podcast thing, the freedom,

and that there's something, 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 feed to the fire. Like one of the cool things

we, what 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

the platform is like, you're kind of one 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, Veritas, and 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 seem as a potential person

who has racist guests on. Or like, you know, they seem as like a headache, potentially. So,

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'll, 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 has Jack Dorsey is 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 or some significant number of people think that the current president of the United

States should not be on your platform. And that'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 the

ultimate 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 has 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, 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,

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 a 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, 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, like you should be able to optimize for that. You don't need to

necessarily optimize for engagement. 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,

you know, trust from Wall Street to be able to carry out such a strategy.

This is the, 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 every, 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. So that, but that requires being really good, really good at what you do.

It requires being Steve Jobs and Elon Musk. And there's, 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 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?

Yeah. I mean, that's kind of awesome.

And it's kind of making it happen, which is like, it's, 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, right? 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.

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 mean, 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 like, right? But with a computer, you can literally imagine

any kind of program, right? So it's a little bit godlike 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. It was the first program. It's probably like trying to write one of those

games in 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 being a programmer. It's 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 with them, 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 a dope or somebody else's dopamine.

Yeah, yeah, you live off other people's dopamine.

So is there pain points and challenges yet 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 because like they're so already self critical, like

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 a

draft. 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 you 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, 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 are there? Like, do you recommend people start with the first one?

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 got to read all of them.

So it's not like a tree, like that, like a creation of like the universe that you should go

in sequence. You should go in sequence. Yeah, it's kind of a chronological storyline. There's

six books and all. Then there's like many kind of off 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, 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

epsilon's 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.

The 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,

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 a world a little 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 and I know I need to watch it. But yeah, because it's in, is it in English or no?

It's an English movie. And it's a sort of like dystopian movie of authoritarian incompetence,

right? And 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, just things kind of

amble along. It kind of strikes me as like a very plausible future of like, you know,

of what authoritarians it 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

whether it's authoritarian dystopian stuff or just basic, like, you know, if you look at

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 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. It's 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 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

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 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 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 doesn't

make light of it, but something goes probably like this, right? Like a bunch of kind of people

that are like, oh, shit, right? You're right. The thing is, it was so close to 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.

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. Because I think there's a good, I haven't watched

yet the good movie on Churchill with Gary Oldman. I think there's Gary Oldman. I might 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 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 fact that you would 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. It was 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 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 it's, to me, it's so much more fascinating than 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 so interesting, like the bureaucracy of it is 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 Steven

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. It's so fascinating to

to to talk to somebody like he knows Stalin better than Stalin himself. It's crazy. Like

you have, I think he's a Princeton, he is basically his whole life is 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, English biography of Putin,

I need to read some Russians. Obviously, I'm mentally preparing for a possible conversation

with Putin. So what is your first question to Putin when you have him on your on the podcast?

It's interesting you bring that up. The first of all, I wouldn't tell you, but

but I actually haven't even thought about that. So my current approach and I do this with interviews

is 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 extreme empathy, right? It's a little bit like Hannibal, right? Like if you ever watched

the show Hannibal, right, they had that guy. We know Hannibal, of course, like,

yeah, sounds 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,

is 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 was 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 talked with. I talked 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.

Right. You go so far to the opposite side. And it's like demystifies it a little bit, right?

Yeah. There is a person behind all of these things. Yeah. And that's the cool thing about

podcasting, like three, four hour conversations that, 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? 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

listening to this now, like jogging, and 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.

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, 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, you know, back, back in

the day on the, you know, on the Savannah, you have 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, but that's why, like, you know, it works with the podcasting, right? 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 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 you, it's

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, 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 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 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 some dynamic. 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. 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 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. And now let me leave you with some words from Ludwig Wittgenstein. The limits of

my language means the limits of my world. Thank you for listening and hope to see you next time.