How Focus Killed Sora and Saved Anthropic | This Week in AI with Victor Riparbelli, Nick Harris & Jeremy Fraenkel

26:09And it's all in service of powering technologies like Jeremy and Victor's. It's really about the apps that run on top of this and getting the cost to the right point, because the AI models are incredible, but we've got to keep driving down the token cost and driving up the inference rate. And then we'll be able to keep unlocking incredible things like custom movies. And you're going to need blazingly fast interconnect for that. Jeremy, I'm assuming you're building on CUDA, which is the proprietary layer for coding and sending jobs to NVIDIA hardware, correct? Correct. And if you were to consider other platforms, other hardware platforms that were non-NVIDIA, Have you considered that?

26:53And is there a path for you? Or would you have to maintain, you know, CUDA plus some other open source software? I guess there's some abstraction layers for CUDA now to get on AMD processors. So as the CEO, how do you think about where to spend your energy? Is it just too much to even consider other platforms? Or are you like Amazon, Meta, and Google saying, hey, we need to have two swings at bat? I very much think that's not. We are in the process of exploring different chips as well. You mentioned Traniums, one of the chips we're in the process of exploring. And the idea here is that we don't want to just be dependent on one hardware, one type of chip.

27:35Of course, it comes with, like, QDA gives you a lot of advantages. And it's not easy to switch away from QDA, but it's definitely something that we're in the process of exploring. And what Nick is doing is really exciting. Because the funny thing about everyone knows, but with video, you know about the amount of data that is being moved from one place to another. But people also don't realize that you have the same problem with tables. If you think about a table with 10 million rows and 100 columns, which is not even that big of a table, it's like when you have a billion cents, that's orders of magnitude more than the context the largest LLMs can even take in.

28:14The largest LLMs can maybe take 100 ,000 rows. But when you're working, for example, with banks on fraud detection, you're working with billions of rows. So like you just need and, you know, and they're like, you know, millisecond matters, right? Like you make like a decision, like when you strike a credit card, you don't want to be waiting for 10 minutes before you get an answer. You just want to get an answer right away. And so the amount of data out there in tables is just massive. Like we've been, you know, talking to a few companies where like they think about every IoT sensor. Every time you get some data, that comes in some form of structure form.

28:50And the amount of data that they are dealing with is like petabytes of data. And so being able to move data much faster and having a lower latency, and as Nick said, also lower cost, will really be essential. Yeah, I mean, if you were to think about, I have these air things. I don't know if you guys care about air quality in your homes, but it turns out like in your office, in your home, like CO2 and radon, all this stuff, very important for health, very important for like cognitive function, especially CO2. So I have these era things and it's taking recordings in six rooms in three different houses for me.

29:26The amount of data that just one person consumes or let alone your whoop or your Fitbit, like how many heartbeats is whoop and shout out to whoop. They just raised money on a$10 billion valuation. What's the data processing there when they have to do my sleep and my recovery and my run and my heartbeat? I mean, my Lord, it's a huge amount of data. Yeah, exactly. It's unfathomable amounts of data. And as you said, you don't spend your day thinking about all the data that's being collected, but there's so much data. And I think that if you look at just in terms of volume, I think 70 to 80 % of enterprises' data comes in structured form.

30:06Not all of that data is valuable and not all of that data is used, but the volume of data is massive. Well, it's not used because big data as a discipline wasn't able to use it. But if AI and this new hardware layer makes it affordable to do it, who knows what you could find in that data like we it really is great and that's that's exactly that's it that's exactly what we do right like that's literally where we're at where like we realize that if i now go to you like if you go for example to whatever an energy company and they have petabytes of data what will end up happening is that some internal some data scientists will summarize their data into a whatever two-page document and give it to the ceo but like that's a compression of you know of the information you much rather work on that raw data as opposed to a compressed form of that data.

31:00And that's essentially what language really is. And what we do is really work directly on the raw data to get you much better predictions and decisions than you could get by just compressing that data into higher forms of - The way to think of that would be whenever you work with some sys-op or somebody who's working in data engineering, you would do a roll-up. You'd say, hey, what is it costing us to store all this data for the last 10 years? And like, yeah, just make a roll-up table, average it out for the last by hour or by day or by week, and we'll just throw that data away. It's not worth storing.

31:37We can't process it anyway. And this opens up a whole new world for healthcare, for finance, for Uber, tracking rides. They may not have the fidelity to know every ride in every city on New Year's Eve. They probably just have some roll-up table with that, but they could actually unlock all 20 years of that data by car, by second. It could be all kinds of interesting things in that data. Correct. And getting inside of that data is much more valuable than the cost it takes to store that data. Right. The analysis is now more than the storage. The storage was the issue 20 years ago. Storage is essentially unlimited and free now.

32:15It's kind of done. It's a solved problem. When will Nick and Victor, when will compute be, you know, when will we be talking about compute like we talk about storage here, which is it's a non-issue, it's trivial? Yeah, so that's an interesting point. Right now, if you profile the runtime for a program like an AI model running on one of these, you know, supercomputers, these AI supercomputers, most of the time is spent on networking. So moving the data between the GPUs and moving the data from memory. Compute is actually a pretty small fraction. So it's funny you say that. Right now, compute is not the limitation at all.

32:50We have these incredibly intelligent, ultra-high throughput processors from NVIDIA and everybody else. And those guys can just work really quickly, but they can't talk. You know, a lot of people are like this too. When you get smart enough, it ends up getting hard to talk. And that's where the GPUs are, and we're trying to help those people talk. Yeah, it's a pretty great analogy. Like you've got too much flowing out of your head at once, and you've got to figure out a way to structure it. so that other people can process it. This is where Neuralink will solve that problem for all of us. We'll be on this podcast just Neuralinking, connecting our brains, and then there'll just be one output stream that'll be like, the four of them think this.

33:28The four of them debate this. It's like, it sounds science fiction, but it is coming. Yeah, Victor? No, I think it's definitely coming. I love the discussion because I'm much more focused on the application there, right? But there's a similar kind of thing with things like video, right? Video is a much higher bandwidth way of communicating, as opposed to, you know, if you're like, language and text is amazing. It's made the world what it is today. But ultimately, it's very, very high compression way of sharing your ideas or your knowledge or whatever. Like the archetypical example would be like, you know, describing an image to someone is impossible, right?

34:05Like it's literally impossible to like, I call you on the phone, Jason, and I explain an image to you and you see exactly the same thing I'm seeing in front of me. There's so much compression that happens when we communicate in text, which is why I think people prefer video and audio so much more in the modern world. And I mean, this goes all the way down to how our GPUs and data centers work as well, which is interesting. So it just feels like the world is going into overdrive, right? We can create and disseminate information at a faster and faster pace, which is fascinating. It's funny, the way that content is delivered now, I mean, I think, Victor, you were talking about this.

34:42people kind of create a video and then they ship the video to everybody. And it's the same, it's the same video for everyone. And then, you know, with, with databases, people are looking at, you know, Jeremy, like you're talking about, they provide an analysis, they give it to the CEO and it's a compression of the underlying data. It seems like one of the principal things that AI is doing is it's allowing us to deliver the data and a genius along with it to interpret it in any way that you want to ask the question. And that's this new thing. It's like data is now completely interactive, but it's going to come with an enormous cost because like typically with infrastructure today, we write programs, the program programs are easily distributable and you don't need to do all the work of designing that program every time.

35:22Now AI is taking on the job of it's going to rewrite the program every single time. Like there's an enormous amount of right. Yeah. Literally it's like, okay, I opened up Slack and it just coded Slack and customized it for me for my use case and then just ran it. And I think that was, you know, I was talking to elon about this not to name drop but you know he's talking about the idea of like you know the somebody was talking to him about like are you going to make a phone a spacex phone a tesla phone or whatever and he thought you know there's a decent chance we'll just buy a slab it'll just be like a black mirror and you you just have an operating system of some type it's a dumb terminal maybe it's got some processing bar and it just boom your software's here boom your app is here for meditation boom your abstraction of the uber app for when you're in tokyo is different than the abstraction of the Uber app when you're in your home city.

36:13It's very hard to conceive of this. I think even in enterprise software, right? Like what's going to happen to Salesforce and ServiceNow, like this whole discussion that's going on. I think often we have a tendency to think that the world's going to look like it is today and the agents are going to take a lot of the work. And that's in many cases, I think true. But I also think what we're going to see is that today, the world's largest companies all have customized integrations of Salesforce, ServiceNow, SAP, like pick your like big software vendor. And probably what's going to happen in the not so distant future, right?

36:44It's just that no matter how small your company is, you're actually going to get like a completely customized software stack that works like just exactly the way that you want it to work. Because most small businesses today, they're kind of like fitting into like the paradigm of like the software that they buy as opposed to the other way around. But with agents and vibe coding, right? You're probably going to have like 50 % of what you're using. It's probably still like the system of record. It's the thing that makes it safe to use. It's the core of the product. But then the last 50 % is probably just going to be either just in time for every single user.

37:13I think definitely it's for every single company. I think that's going to create a whole new category of mix between salespeople, forward deployed engineer, product manager, whatever you want to call it. How do you take a mid-market business and you actually generate an entire software stack that works just for them, right? That feels like the way all the stuff's going to go. And it's just going to be such a different world, I think in three or four years. I'm seeing it. Go ahead, Jeremy. No, I was saying, I agree that, and I don't think that it is, I think we'll see the beginnings of it now, right?

37:44How many companies, how many startups do you know that still use Salesforce? Very few, right? We've built our own agent system. I actually disagree with that, but I can come up to you. I'm curious to hear your thoughts. Yeah, go ahead, Victor. We like a little debate, yeah. I think one of the lowest EV things you could do right now as a founder is to try and replicate a CRM system. If you have 10 amazing engineers, I think you should just buy Adio, Salesforce, whatever thing that you're using and focus those 10 engineers on building something that's not just going to remove... But why would it be engineers?

38:18You could just literally have the sales, customer success person tell their open claw or clawed code or whatever, or perplexity computer, yeah, just VibeCode me this and build it. I mean, I think that's what's actually happening. That's exactly what we've done. We've built our own system that's called Fetch. We essentially integrate it within Slack. And then you can just, it's essentially your CRM. You can ask any questions, get you the answers, get you anything you want. You've via-coded your own CRM for the sales team. How big is your team? The sales team is relatively small, 15 people. So it's not like a massive team of hundreds of people.

38:58And I agree that Microsoft or Amazon is not going to via-code Salesforce, But my point is like small startups can definitely do that because, you know, you don't need to have the same reliability as a big enterprise player. It's an interesting thing. Like the main problem with this is your CRM is so important. If it screws up, you've really got an issue for the business. And so one of the central challenges with Vibe coding is how do you build a verification framework to make sure that software actually works? And I think most of the work that goes into building these things is in the verification.

39:33I think if you go to Google and you talk to software engineers there, they're not spending their time on like writing the lines of code as much as they are writing the hooks to test the software and make sure it works every time. So I think it really depends on how mission critical it is, whether you'd build it yourself and verification is everything. When I'm prompting a lot of the time, I'll do engineering stuff, finance, sales, marketing, you know, all sorts of stuff, a technical background. But I usually start out by describing the problem. I say, we're going to fix this. But before you give me a solution, I want you to come up with a whole verification framework.

40:05And really working on that piece, I think that's one of the really important parts of kind of developing solutions that you can use because there's a lot of ways to get trash out of these AI models. Yeah. So if the fidelity is there and if the redundancy and the security, the stability is there, then we're going to see more people vibe code or just take me take vibe coding out of this, just build internal solutions versus external. And there's that natural tension, Victor, of, hey, what is the highest use of our tech team? Is it what we do? Make videos, work on photonics, you know, make our LTM.

40:46Like we need to really think about that resource. And I'm having this experience internally all the time because these tools, I think, are getting better every two weeks. I was kind of feeling like they were getting better every month and you could keep up with the cycle. But now it feels like every two weeks, Claude Code, Perplexity Computer, and OpenClaw do something so good that it makes you wonder, am I using the right platform? Maybe I should move platforms. And it's becoming disorienting for my team because we did this big investment in OpenClaw. And then people were like, wait a second, CloudCode gives better results.

41:26And then somebody else in another group is like, perplexity is computer is just trouncing everybody. And then up the next week, a CloudCode's got skills. So how do you think about managing multiple platforms? And are you having the same experience, Jeremy, where these multiple platforms are lapping each other? And is it disorienting for your team when you're making these solutions? I agree with both Victor and Nick that, you know, you need to make sure that you have verification in place. And like, you know, it depends on what, where you apply those models. But like, essentially not using them is also a decrease in productivity, right?

42:03Because at the end of the day, like if you want to build something and something is fully, and now, you know, enterprises especially, but startups as well, expecting to be fully customized, right? And like, if I can have something that's fully customized to me and works fully for my team in the way we want it, it's just going to make everything much faster as opposed to having to teach people to learn a new system, sorry, an old system, and to go the old ways. Now, if you can marry that with the proper amount of verification and knowing when to use them and when not to use them, I think that you will just see more and more startups and enterprises start using them.

42:42Yeah, I mean, just to make sure, of course, this is the way the world is going. I'm not saying it's not. And I think these things are extremely powerful. I just think to your point, right? I don't know how big your team is, Jason. I don't know what you would spend on like a CRM system. Okay. So let's say a CRM system for 21 people. I don't know how much is that, like 10, 15K a year, maybe something like that. If your team has to constantly like fight battles with like new models that come up, open, close, delete half the code base, you have to vibe code again. It's like very fun. I just think your team could probably like make more than 15k if they took that time and they you know spent their time to do exactly yeah but victor why do you have to redo it every single time you don't have to redo it every single time right you can you can i don't even think it's bad i don't i don't think it's about redoing it so like we just had a perfect example we just had a perfect example of this that is exactly what victor's talking about so i have this team that's doing chip verification work and they're spending so much money on tokens.

43:40They keep coming back. You're like, hey, can we get more tokens for this? And, you know, it's quite expensive at this point. We're looking at it. And what it looks like from a spend perspective is we just hired another two engineers. And so you sort of, you start to take on this view of, is it going, how much am I going to spend in tokens to do this task? And you can really quickly quantify whether it's worth it. Because you look at a subscription cost for a tool, like what you're saying, you know, Victor, you're talking about Salesforce. course, if the subscription cost is a lot cheaper than how much you're going to spend in tokens to try to make it, then don't do it.

44:13Don't waste your time. It's funny because there's such a really clear economic way to measure this. Just are you going to spend half a million or are you going to spend 30 ,000 a year? I think what's often is lacking in that calculation is like there's a monetary cost, which you can calculate like you just did. And then there's a focus cost, right? Which I think OpenAI is learning the hard way right now, like, you know, trying to do like 16 things at once. If you also need to have a team that's like building all your tools, that can't do that. then it breaks half the time because they don't really know what they're doing.

44:39Like, I think if the world is going to go this way, I just think I would rather just pay 15K and then focus on like value because the cap, the maximum amount you can make on that team, right, is 15K if you're just automating like a piece of software. So I think there's a bit of like, sometimes with this bytecoding thing, I think there's a bit of like what I call the AR-SDR fallacy, which people are like, oh yeah, now like, you know, like my open clock, I like do the job of an SDR now. But that's like, that's thinking of an SDR's job, it's like emails, right? That's a part of an SDR's job, but an SDR's job is a lot more than just writing emails.

45:09I think we're going to get there. I think we are going to get there eventually, but I think that we're in a little bit of a bubble sometimes in the tech world, but I'm not sure that a lot of focus is going towards the most productive thing. I think we're in the middle of the... We're in the eye of the storm, Victor, is a way to sort of say it. Like it is choppy waters and we're in the soup as like people in, you know, maybe flying a plane through a hurricane might say it's like it's a little bit soupy right now. So it's hard to understand. I was using I wanted to get like root access to Slack so that my open claw could be like, here's everything that occurred on Slack.

45:47Here's every DM. Here's every private chat room. Here's the report. You're the CEO. I have God mode. Give me everything. And I'm like talking to Benny off about it. And it's like, well, you don't really have God mode. Like it's kind of our data. I'm like, well, isn't it kind of our data? And like, so we use Slack bot. I'm like, I don't want to use Slack bot. I want to pull them all my data out. And so finally my open call was like, I'm like, how do I get everything? They're like, well, you could export everything and then we could analyze it and you could just export it every Friday. And I'm like, well, that doesn't work.

46:14And they're like, and the export feature on Slack is like 50 bucks a person or something. It's like some crazy amount to be able to export. And I'm like, oh my God, they've locked up my data here. This is making me mental. and then I looked at what I'm spending and it's like would you like me to make you with matter post I think it was or something there's some open source version of slack and my open call was like this weekend we'll make a open source version of slack and we'll just convert everything over pay for the highest level export everything and then uh cancel it in the same month and you'll only have to pay one month to get all your data and like even down to the likes on the post and And I'm like, how much are we spending on Slack?

46:53They're like$6 ,000 a year. I'm like, you know what? No, forget this. If I'm spending$300,$400 a year on Slack, I'm not replacing it. It's just too much headache. But when it came to SDRs, Victor, I was like, wait a second. How much are we paying our Athena assistant to do this work? It's like$3 ,000 a month. Go to athenawow.com and you'll get like a month off with my discount code. I'm an investment company. I'll give them a little promo here. I had the Athena assistant going through the sales for the podcast and making like a sales report every day. We were able to get open claw to do it. Now that Athena assistant was able to move up the stack to do better work.

47:31Then when you're doing a podcast company and you might look at who's advertising on the other podcasts. So they would in their spare time, if the Athena assistant had nothing to do, they would go look at other podcasts and say, okay, who's advertising on Bill Simmons or Joe Rogan. Put it into the database and put it into the CRM. Open Claw, we were able to automate that. So it's just every level of what an SDR does has been given to the Open Claws. Every time we get an iteration, I'd say it happens every two to four weeks, like is the cadence right now, we're able to automate another thing that took somebody 10 hours a week.

48:10And where do you spend your time, Nick? How do I reconcile this? Is my time to free up everybody's time as the CEO of the corporation? Or is my job to focus on the thing that we do better than everybody else in the world? And how do I allocate my resources to do that? I mean, I think that's what we're kind of getting at here is what do we do as CEOs of companies, as leaders? You know, it's so interesting. One thing I'm taking away from hearing all of you talk is we're able to so clearly put a price tag on how much a piece of software is worth. That's really weird because it's a new thing. That's totally it's totally new.

48:44So so I guess the way I'm using my time, obviously, there's so much going on. One of the fun things about the company growing, you know, as the way that it has is there's so much data. I wake up. There's so many cool emails, new partnerships, new things to build all this stuff. But it's too much to keep track of. And so I've always got an anthropic, you know, Claude session up and it's summarizing, you know, emails and Slack and everything else. Just like you were saying, Jason. And I think that gives enormous leverage. And it's also the case that there's so many micro details that really matter.

49:13And these AI tools let you zoom in on those. I'm not missing anything. Like my hit rate is very, very high at this point. That's incredible. As a leader. I can keep the tension. Yeah. You know, when you're running a company, I don't know if you guys have felt this, but I can feel the tension on the rope. If you are not pinging the team, you're not checking on things, the rope slack. Something happens and you all get jerked by it. But the real task is to keep it tight. And these AI tools are allowing that to be possible. And meeting prep's amazing. You go and meet with other CEOs and you understand their whole worldview.

49:48Everything they've said, their personality, whatever it is, it's just an enormous leverage. And I feel like you can taste the singularity at this point. I can't even imagine the end of this year is going to be shocking, I think. I feel like you could be, what was it, Dr. Manhattan from that superhero show where you're just like omnipresent. You're everywhere at all times. It's kind of like a Jesus. I'm not saying I'm a Jesus CEO, but it kind of feels like we're, watch me with the show. I feel like we're moving into like Jesus CEO. When I was a kid and you're Catholic, they tell you Jesus is everywhere.

50:24When you're like eight or nine years old and you're like, is he here right now? It's like, yes. And it's like, was he at lunch? Yep, Jesus was there too. too. I have now said there is there's Dr. Manhattan from Watchman. He's just like omnipresent. But Jeremy, like I set up root access, obviously Slack, Notion and Gmail and everything. So I was just working with one of my people and they're like, I'm going to be on vacation next week. I'm going to check email every day at like six o 'clock every morning at like seven o 'clock. I was like, don't bother. Here's the operations person. And I said, check in report, CIR.

50:55I built a skill for my open claw agent to just summarize and prioritize the person's emails every day at noon and 6 p.m., put that in categories, investments, operations, human resources, and then rank them by importance. And if we needed to get back to the person, the person's got vacation message on. And then the person's like, oh, you know, there was one email in there that like maybe people shouldn't see or whatever. And I had to like remind them like, please, it's a corporate email. It's like the company's property. We're a finance company. All emails are seen by all people. But like, we just have perfect clarity into their inbox, their Slack, when they're not here.

51:35Then my team was like, would you like us to bring these three former employees back to work and make them an open claw persona based on their old email and Slack, Jeremy? And I was like, am I allowed to do that? Because that's kind of like, what's the Stephen King cat's paw or something? Pet cemetery where they bring the pets back to life. I'm like, I'm not sure if that's a good idea to bring past employees to life. But yeah, let's do it. So we just turned on the Slack, turned on the Gmail, turned on the Notion edits of the person who left two years ago. And now you can talk to them and say, hey, tell me about this deal we did four years ago that we invested in the company.

52:13Give me the whole history. Very strange. How is it affecting you as a CEO, Jeremy? Are you becoming an omnipresent, keeping the strings nice and tight on the guitar? How do you? I mean, to the point back, the reason why we build this is just to have access to all of that data, to essentially have one system where all the data flows into. And it's not just me, but pretty much everyone at the company has access to everything. And that's really amazing because now you can know what's happening at the company as opposed to just knowing what's happening within your own team or your own departments or your own reports.

52:50And I think that to us has been a massive boost in productivity. How about from your perspective, Victor, how has it changed you as a CEO and a leader having this omnipresence and this cadence and all these tools that didn't exist three years ago? Hugely. And also, to set the record straight, it's not because I'm anti-AI. I just try to be very intentional about where I think there's actually value to be gained versus just playing with toys. And that's something I try and instill in the organization. even though that can also in itself be valuable. But I think stuff like I'm right now building one for kind of what I call like an executive changelog, which just scans like everything that's happening in Slack, emails, et cetera, and just on a daily level, just like which decisions did we make today in which team, right?

53:39And that's actually really cool. Like you'll get a list of decisions that's been made and that could be anything from like, we decided to like buy this platform, we churned on this product, this customer upgraded with like X amount. And I used to always, you know, read every single Slack message in the entire, we're 650 people, right? So like six months ago, that started to become like pretty challenging. But I thought it was really important always because it gave you the pulse of the company. You know what's happening in every single team, right? And this is like one way I think of trying to scale that.

54:08You have to use it in so many like areas of the business, like going to go to market team. It's hugely valuable for things like call prep, customer research, coming up with use cases. But you trained it specifically to say, if a decision is made, I just want to know who was involved in that decision and what was it. So it's the change log. So you've narrowed the focus of this operation of this cron job, just tell me the changes, the decisions people made, and you can just checkbox them or check in on them. Exactly. And the level of granularity is the thing that's difficult because if it's just a decision, at first it would show me everything that's going on in linear GitHub.

54:45That's way too much information for my level. So you have to fine-tune a little bit to figure are like, what's the kind of right level? But that's one of the things I've done recently that's hugely valuable. Obviously, connecting all your calls, even just the fact that you've recalled your calls and that becomes part of the context for whatever LLM you're using. As a sparing partner for strategy stuff, it's just amazing. I think there's no strategic decision I don't make where I don't discuss it with a GPT or an LLM first. And the other thing I'd say, which is very basic stuff, but starting to use like Whisperflow to actually talk.

55:22Oh, Whisperflow is awesome. That's the thing that's been one of the biggest productivity things for me because you really realize - Did you get a foot pedal yet? Did you get the foot pedal? No. Oh my God. Explain Whisperflow and why it's special versus just typical text to, speech to text. Yeah. Like Siri. I think so. The way Whisperflows works, you install it in a computer and you set a hotkey and then any text field that you operate on, no matter if it's a Slack, if it's an email you're writing, anything like that you just hold down the key and you speak i think what they've done well is that like there's some of these things that just transcribe you like directly and that's not always like that doesn't always like sound great but they they fixed the last five percent of like grammatical errors yes speaking or stuff like that so it actually comes out sounding like you know pretty reasonable i think that's like a super cool feature and i think they did that better than than any other product i've learned what i've had to learn myself is that it's when you talk to whisper flow, right?

56:18It's okay to take a 15 second thinking break. That's weird if you're speaking to another human being. So the way I speak or you speak to it, I think you kind of have to learn, right? Because I'll be like, you feel this like a pressure of like, I'm like right now, if I stopped speaking for 15 seconds, one of you would interject, right? But with whisper flow, you can sit in silence for five minutes if you don't know the next thing to say. And once I mastered that, which took me, it took me probably like a good week or so to like really internalize like how to use it. It's just like amazing. When you make a bullet point list as an example, you're like, okay, there's three things we need to focus on.

56:50We need to make sure that everybody's got a great microphone for the podcast. We have to make sure that we have great show notes. It will make it one, two, three. It'll format it for you. If you say somebody's last name and it's like Frankl, it's like, okay, I know Jeremy Frankl. It's going to spell his name correctly. It's really bizarre when you start using it. and everybody gives up on Siri because the mistakes are, there's so many mistakes that you wind up spending more time fixing Siri than you do the gain from not having to type. So you just instantly are like, I'll just type this. Siri is retarded.

57:28Whisperflow is like a genius editor who, or like the greatest executive assistant ever taking a memo. Like they know the context of what you're doing. They know your last name. producer Oliver, get everybody's address on the show. I'm sending everybody a foot pedal. This$26 foot pedal is my gift to you guys. It's a$26 foot pedal for your hour. Jason, how often do you use that foot pedal yourself? I just started. I'm on the road right now. I didn't bring it with me. I looked at it when I left and I was like, should I bring that with me? I used it 20 times a day in the first week because I was like, let me just try this.

58:06You put the foot pedal down and I could be drinking my coffee, I'm talking, I could be writing in my notepad, I could be doing whatever and moving a window around the screen. But it's in that text box, as Victor was saying. And then when I release it, that's when it puts the text in. So as Victor was explaining, Nick, you know, you could be brainstorming here. Hey, here's my to do list for today. This is now add that to talking to an open claw agent. Yeah. You know, I go on walks all the time with my team and by myself and I'm thinking, and I'm constantly at this point, like, I wish I had an AI model that could keep track of this thought process because I've just come up with a bunch of things that I lose them every time.

58:48I feel like the probably companies are working on this. Okay. You've got something. I'm going to send everybody on the show. This is becoming like the Johnny Carson show. Our guest today got like these three things yeah not only am i sending you each a paddle i'm sending you each a plod pin i'm not i didn't get them free i'm gonna pay for these like 150 bucks each the plod pin uh you can pin on your jacket i put it on my ski jacket when i'm skiing then you press this button boom it turns red it vibrates got a haptic now it's recording everything then when you get back and you put it in this little cradle to charge it it connects to your wi-fi automatically it then transcribes it it makes a summary and then you can do whatever you want with that so and it will do a mind map so it's got like all these templates so after i'm on my walk here we go this when this combines i believe plot at some point will have a native open claw agent in it and i told them like why don't you build like an earpiece that connects to the plot and like maybe we could have like a little back and forth they didn't tell me anything I don't have any inside information.

59:57I am so taken with this company. And they make one that goes like on the back of your phone too, like a MagSafe. Let's talk about AGI. It feels like to me that AGI has been achieved and we just haven't deployed it yet. That's my personal belief. Here's Dario who talks a lot. It is surprising to me that we are, you know, in my view, so close to these models reaching the level of human intelligence. and yet there doesn't seem to be a wider recognition in society of what's about to happen. It's as if this tsunami is coming at us and, you know, it's so close. We can see it on the horizon and yet people are coming up with these explanations for, oh, it's not actually a tsunami.

1:00:41It's, you know, that's just a trick of the light. And I think along with that, there hasn't been a public awareness of the risks. And, you know, therefore, governments haven't acted to address the risk. There's even an ideology that, you know, we should just try to accelerate as fast as possible, which, you know, I understand the benefits of the technology. I wrote Machines of Loving Grace, but I think there hasn't been an appropriate realization of the risks of the technology and there certainly hasn't been actions. Just specifically with Dario, he is on a heater. I don't think like we've ever seen an AI added more revenue in a month than like anybody in the history of capitalism has ever added.

1:01:19I'm not sure if there's like the top drug dealers in the history of like moving heroin and cocaine and fentanyl around the globe. You put them all together. They didn't add as much revenue in a month as he added. This is just a generational run, I think, is probably a good way to sort of frame it. But he kind of thinks the shit's going to hit the fan. He kind of thinks we're here. And we were talking about singularity before. Or where do you sit on the, hey, this could get acute, this could be society disruptive? And where are we in the AGI scale? How do you define AGI? I would say I'm not on the alarmist camp.

1:01:58I think technology is fundamentally interesting and useful, and it's a tool. I'd say the rate of progress you talk about every two weeks, I'm seeing releases from Anthropic daily, it looks like. To me, looking from the outside, it feels like the rate of progress is accelerating. So you had an exponential, but now this is like a double exponential. It feels like something very big is coming. I think that the world doesn't appreciate that it's happening because most people are not very good at asking questions. When I go around my company, I'll sit with engineers, I'll sit with people from any team.

1:02:34And what I find out is they're not that good at asking questions. And when you're not good at asking questions, it's hard to see the value in these things. And so I think most of the world isn't quite experiencing it yet, but they're going to realize it. There's sort of two skills with seeing the value in these, asking really good questions, which is a core skill from science. And the other one is management. because they're kind of like a person that you have to manage. So I think that's why the people don't see the wave. But from what I can see, it's just wild. The rate of progress is accelerating.

1:03:11Yeah. I mean, Dario Escobar is just delivering the good. He's got the high-quality good stuff. It's crazy. Jeremy, your thoughts on agent. So I very much agree with Nick. But to me, I guess, taking a step back, I don't really like the term AGI because to me, it's a moving goalpost with no real benchmark. If I showed you what we have today, 10 years ago, you would have definitely said it's AGI. But now, we're constantly moving the definition of what AGI really means. and from my perspective and I definitely think that from my perspective when I look at AGI I also look at the fact that I look at it as the two halves of the brain we have one half of the brain that understands language and creativity and all of those things and we're doing really well with that the other side of the brain which does math and understand structural data there we've done very little progress so far and humans generally are really bad at statistics and I think that for whatever definition you really have of AGI, I think that if we want to get to true AGI, we really need to do both of those well.

1:04:24And I don't think that we're not there yet. And that's really where we are focusing on, on improving that other side of the brain. But to Nick's point, I definitely agree that most people have absolutely no understanding of what's happening. Like I was talking to a friend of mine in London and she's an accountant and she told me, oh yeah, in my lifetime, accounting is never going to be replaced by automation. I'm like, what are you talking about? It's probably one of the first things that's going to be replaced. And I think that it's funny because people talk always about creative destruction and the fact that it's the same thing as the agricultural revolution or the industrial revolution.

1:05:02And it's true that we've seen there's going to be new opportunities and new jobs. But the difference, I think, between those past periods and now is that it's the first time we're really automating cognition as opposed to just automating the physical part of a job. And I don't think that people comprehend it. And I think that, you know, in Silicon Valley, we often live in a, you know, in an amazing bubble where like, you know, we see like, we see the world as it will look 10 years from now or like, you know, as people expect it to look 10 years from now. And I think that that's, and so, yeah, I very much agree with Nick here in terms of the rate of change is just unbelievable.

1:05:40And the physical is coming, by the way, the physical. Yeah, correct, exactly. Okay, great, great. The physical is coming. I mean, I think that, you know, physical, it's a bit more, it's a bit further away. I saw, I was at an event a few days ago, and I saw a bunch of, you know, robots, like, whatever, like an event with a bunch of robots and whatever. And it was just like, it's still lagging where, you know, where we are in terms of like, you know, the, on the LLM scale, I guess. But, but yeah, I agree that, you know, whatever we do in a few years, we'll definitely get there on the physical side as well.

1:06:13So, Victor, I'll open it up to you with the additional context of Americans are scared. Generally speaking, they're in the doomer camp for whatever reason. Chinese people seem to think it's going to be awesome and it's going to make life more fun and more efficient. Americans, they think 70 % in this Quinnipiac poll from yesterday, 70 % of them think they'll have a decrease in job opportunities. Last year when they asked that question was 56%. Interestingly, only 30 % of Americans are worried in the same poll about themselves. So they all think it's happening to somebody else. But who's right here?

1:06:57Are the optimists, Nick and Jeremy, right? Like, hey, this is going to be awesome. Is the 70 % of Americans who think this is going to impact jobs correct? Is Dario correct? AGI is kind of landing this year. What are your thoughts? I tend to agree with Nick and Jeremy. I think obviously the rate of progress is insane. We've seen how it works for techs. Now we're seeing it for video. We're seeing it for voice. We're seeing it for physical intelligence. in the next couple of years, that will definitely also start to get there. And I think, as Jeremy's part, right, AGI, I think it's a word that doesn't really have any meaning.

1:07:34It's a moving goalpost. Like, if you took this 50 years back, you'd almost be burned at the stake, right? Or how many years back is burned at the stake? And people would definitely say, this is definitely like artificial general intelligence, which is what the word stands for. I tend to be more optimistic. I do think that humans will want to play status games. I think we'll find other jobs. I think we'll probably be doing less numerical and logical jobs. And I think actually maybe a lot of the value that will accrue in society is going to go more towards things we actually all of us enjoy more.

1:08:01Things like going to a great restaurant, working out, listening to live music, like all those things that most of us like to do in our free time. I think increasingly jobs are going to move more towards like that's where like the value in society accrues. Less on the like I'm really good at maths, I'm really good at like software development. And I just think that's like a positive thing that most people would want to see. but I am a bit worried about there's a book by Alvin Toffler called Future Shock which was written I think 30 or 40 years ago which talked about this idea that if we see the rate of change happening too fast we get this lag where that can create things like civil unrest huge job losses so on and so forth and I'd say I am in the camp of optimists but I don't think that's a completely non-zero scenario that something like that happens we got to keep the rope tight right you know i think you have to tell everybody that you can about what's about to happen so that everyone's in on it and it's not so shocking like i try to evangelize it everywhere i can i think also to your part right i think one thing i've also learned for the last nine years building a tool for essentially creative expression is that you cannot underestimate enough how little creativity most people have which is another version of like the same thing you said nick of like people don't know how to ask questions or like work with these things and they'll have to change.

1:09:20Right. I think that's kind of interesting because if you go, you know, far enough back in time, the philosophers were like the most well-paid people in society. Right. They were like the titans of industry. They were going to go back to a world in which actually like those kind of skills are going to be valued a lot higher than the kind of technical execution of like writing code or working in finance or those kind of jobs. Well, wasn't there a survey that said that most Americans hate AI or hate the term AI or believe that data centers is the main reason why energy prices are going up, let alone inflation or what's happening in the Middle East, people are really scared of it.

1:09:57And so to your point, Victor, about sin and unrest, how do you prevent that when the rate of change is happening so quickly? And I think also, unfortunately, the populace is not always right, right? But they'll want to find an explanation for potentially other things that's happening in the world. I think that's a different discussion, but I think in general, the West is definitely in jeopardy. AI may help or may work against it. That can be a great scapegoat also, right? That's what I mean, right? It can end up becoming kind of like a scapegoat. Yeah, well, we got to teach everybody we can. This is the most hilarious thing ever.

1:10:39We'll start from the bottom. 61 % of people feel negative about the leadership of Iran. 52 % feel terrible about the Democratic Party. 46, AI. Yeah, just below ICE and Iran is AI. It also matches Gavin Newsom almost perfectly. Yeah, exactly. Yeah, which, by the way, Gavin Newsom, I actually think is an AI. I think that's like Optimus 4 with great hair. He does not feel to me like a human. I actually think he's like a bot sent from the future by Elon to then be a Manchurian candidate. Manchurian candidate Gavin Newsom. All right, gentlemen, this has been amazing. Let me thank our guests, Nick, Victor, and Jeremy.

1:11:26Gentlemen, you guys were so great together. What a great team effort here, passing the ball around. I'm going to ask you each to come back on the same show, So we're going to try to coordinate your schedules. Hopefully you guys will, you know, have such a great reaction to this episode of This Week in AI that you'll come back in maybe four or five weeks and we'll chop it up again. All right. Awesome. Thanks, everybody. And we'll see you all next time. Bye-bye.