AI Layoffs, Compute Costs & Agents | Naveen Rao & Alex Finn on This Week in AI Episode 16

4 Jun 2026 · 54 min · 18 chapters

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In short

This episode of This Week in AI (Ep. 16) debates why AI costs are suddenly spiking and why layoffs are being blamed on “AI efficiencies.” Guests argue the problem isn’t just model intelligence or raw tokens, but incentives and misuse: companies spend heavily on AI without producing production-quality output, and non-technical teams ship risky code. Naveen Rao (Unconventional AI) says “token maxing” (leaderboards/gamification) explains part of the spend, while real productivity per dollar still lags because frontier models aren’t always reliably production-grade. He also criticizes “doomer” narratives (specifically calling out Anthropic) for fueling misinformation and harmful legislation. Alex Finn (Creator Buddy; YouTube) claims AI is already dramatically increasing developer velocity, but benefits aren’t realized due to wrong incentives and insufficient trust/guardrails.

Notable examples

product managers/bloggers shipping production code; routing to cheaper models; internal agent tooling for hiring; and a plan to reduce total cost of ownership by targeting energy constraints (energy share rising toward 50%+).

Written by AI. May contain mistakes. Listen to the episode to check what was said.

Chapters

Tap a time to open that second in VO

AI Cost Concerns and Market Response

0:00 to 1:11

The discussion opens with concerns about rising AI costs and the market's reaction.

“Everyone is freaking out about AI costs.”

Changing AI Landscape and Spending

2:12 to 4:48

Discussion on the shifting perception of AI's value and spending trends in companies.

“Good I love to hear that glorious is how I feel.”

Challenges of AI Intelligence

4:48 to 7:21

Exploration of the limitations of current AI models and their production quality.

“I want to double click on what you said about the return isn't quite there yet or the intelligence isn't quite there yet.”

Navigating AI Usage in Companies

7:21 to 10:57

Conversations about the practical use of AI and the necessity of technical knowledge in coding.

“That's the fundamental issue is you see what all these companies, the CEOs doing layoffs are saying in their kind of canned announcement.”

Company Structures and AI Integration

10:57 to 14:00

Naveen discusses unconventional company structures and the role of AI in modern startups.

“I spent a lot of time studying the different models.”

The Role of Agents in Workflows

14:00 to 15:20

Explore how agents are changing the way companies operate and hire.

“So, and what's interesting is this whole idea of like putting software developers out of work is completely false.”

The Need for Human Developers

15:20 to 16:58

Discussion on the ongoing need for human developers despite AI advancements.

“and then gave himself the need for more human headcount, which from a high level sounds backwards to me.”

Understanding TCO in AI Infrastructure

16:58 to 18:47

Delve into the concepts of total cost of ownership in AI infrastructure.

“Yeah, no, I don't understand the whole narrative around developers are disappearing either.”

Energy Constraints in AI Growth

18:47 to 23:01

Examine the energy constraints affecting AI development and deployment.

“So I'm curious when you're going to arrive like Gandalf on the white horse, when the sun rises on the third day and save us.”

Exploring Non-Von Neumann Computing

23:01 to 24:22

Learn about non-Von Neumann architectures and their implications.

“So I'm kind of pricing in that acceleration, if you will, on the timeline.”
Show all 18 chapters

Leveraging Local Models for Opportunities

24:22 to 28:00

Discover how local models can be used to find and exploit opportunities.

“Alex, I want you to weigh in on what we're talking about here and kind of where you're seeing TCO as one of the leading lights of kind of the personal agent space.”

Personal Agent Setups and AI Tools

28:00 to 30:20

Explore personal productivity tools and the transition to AI assistance.

“I don't have this pulled up, but that's close enough.”

AI Marketing and Public Perception

30:20 to 33:18

Discuss the challenges of AI marketing and public misconceptions about technology.

“Yeah, I think there's many things to it.”

The Impact of Layoffs and AI Narratives

33:18 to 36:54

Examine the relationship between AI narratives, layoffs, and corporate responsibility.

“We have we have politicians going on X going, yeah, we have to stop all AI research.”

Political Implications of AI Development

36:54 to 42:01

Debate the political landscape surrounding AI and its implications for the future.

“over and over again it's going to destroy the earth and this and that it doesn't help it really doesn't freaking help they build amazing models great but stop it stop so i don't disagree with that, Naveen.”

Incentivizing AI Value for All

42:01 to 46:07

Discover the importance of incentivizing public access to AI for societal benefit.

“So there just has to be solutions other than seizing private property.”

Community Impact of Data Centers

46:08 to 49:46

Learn about the potential positive impacts of data centers on local communities.

“So we need to at least start to show like, hey, fertilizer came down 20 % over the last year.”

IPO Speculations and Market Insights

49:49 to 53:05

Gain insights into the upcoming IPOs of AI companies and market trends.

“I think we're all a little worried about politics and the backlash.”
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Transcript

Automatic transcript. May contain errors.

0:00Everyone is freaking out about AI costs.

0:02Alex Finn:Headlines about the problem are now absolutely pandemic. Just because you're using a ton of AI doesn't mean you're producing good things. We have product management shipping production code. That makes zero sense. You know, what are we doing? Instead of saying, hey, we've been really irresponsible the last five years, we're going, oh, well, AI efficiencies, everyone's fired. Not that we weren't prepared for market conditions. Not that we overspent like crazy. Every CEO is putting out this canned tweet that's like, oh, yeah, AI is amazing. We have product management shipping code. It's over, right?

0:31Alex Finn:Normie feels that AI is a superpower and it is a benefit to give them competitiveness. We see it as a boogeyman because somehow we've screwed up the narrative. I actually do blame the doomers, and I specifically will call out Anthropic on this. They have sown this narrative over and over again. It's going to destroy the earth and this and that. It doesn't help. It really doesn't freaking help. The worst case scenario of all these, these people have no idea how AI works They end up winning because people are so upset and they end up legislating this stuff, which kills our economy. And we have to give 50 percent of every AI company to the government, which would be the stupidest thing to ever happen in history.

1:11Alex Finn:Thanks to our friends at PayPal, the exclusive sponsor for This Week in AI. Try the payment and growth platform that's trusted by millions of customers worldwide. PayPal Open. Start growing today at PayPalOpen.com. Hello and welcome back to This Week in AI, our AI Founder Roundtable. We have some of our absolute faves on the show today. But before we get into that, I do want to talk about what we're going to cover, which is suddenly everyone is freaking out about AI costs. Headlines about the problem are now absolutely pandemic. You just can't escape them. So what's real? What's kind of BS? And what do we need to do to resolve this crisis?

1:49We're going to go deep on the AI spend problem and whether or not it should be resolved with hardware. software or both so please join me in welcoming back to the program two of our absolute favorites we have Naveen Rao from Unconventional AI. Naveen how are you?

2:02Alex Finn:Great thanks for uh thanks for having me back. Oh dude my pleasure and we also have Alex Finn from Creator Buddy and of course from YouTube and every other social platform out there. Alex how are you? Glorious good to be here Alex. Good I love to hear that glorious is how I feel. Uh I really do enjoy how I feel like the AI era has different seasons that are not multiple years like we had in the SAS days but instead about three-month sprints and we've gone from... Naveen, it's almost whiplashy just to kind of watch this go back and forth. But we had this moment a couple months ago. Everyone needs to be AI first, AI default.

2:35You got to use this now. You're not going to lose your job to AI, but to someone who uses AI, et cetera, et cetera, et cetera. And now the page has turned and we're seeing headlines about companies blowing through their budgets, spending too much on AI and freaking the frick out. So from a really high level, I don't know if you have a spicy take about why we're here right now, but I'm curious about why you think we are. And then also I thought it'd be a good segue into unconventional and how you're trying to approach an element of this issue.

2:59Alex Finn:I think, you know, we went through the token maxing phase, right. Which is like two months ago, right. So this wasn't like years ago. This is just a couple of months ago. And I think what you see is people are, people need simple rules. And I think token maxing was kind of the, the peak of what happened because people were like, Oh, I want to track something simple, like a token usage. Okay. that's a proxy for how much people are using AI. That's proxy for how much penetration I have of AI. Then you get people putting leaderboards up and trying to gamify these things. So yeah, I think probably, I don't know, let's call it 20 % or 30 % of the token costs are probably due to that sheer token maxing.

3:42Alex Finn:I think the other part of it is real in that the intelligence you get out of a model is still not the same as a human, right? I mean, I think most people will agree with that. In some ways, in some dimensions, it's massively better, right? I mean, access to knowledge, all of that. But in terms of pure reasoning capability and sheer productivity of building something or whatever, not quite there yet. So it'll get better. And I'm pretty confident of that. But I think then if we look at the sort of real productivity, not tokens, but like how much you really move a project forward per unit dollar, it's not really adding up yet.

4:16Alex Finn:And that doesn't mean this is completely wrong or it was a stupid thing to do. It was just like we're still kind of titrating that balance. And so I think what we're working on at conventional is basically, can I bring, you know, sort of unit of intelligence per dollar down drastically over time? And, you know, whatever that unit is, if it's a smaller unit that we can deliver today or a bigger one that we'll deliver in the future, bringing that cost down will make it more ubiquitous, will bring, you know, real economic shifts to how we deliver engineering output. Okay. I want to double click on what you said about the return isn't quite there yet or the intelligence isn't quite there yet.

4:53These models are not, they're jaggedly intelligent, as people love to say, but they're not kind of, you know, across the board good enough. Alex, you've been, I think, consistently pressing the edge of the envelope on A automation and using agents and also kind of testing and playing with new models. What do you think about Naveen's comments about AI intelligence still having some, let's call them blind spots for now?

5:15Alex Finn:I don't think the issue is the intelligence itself. I think it's like even if all AI innovation stopped right now, I think the world is a dramatically different place. I'm building my new startup right now, Henry Intelligent Machines. And I've been a developer my whole life, studied computer science, coded the last 15 years. The velocity in which I work now and can produce quality products right now is quite literally, and this isn't me just throwing around, a thousand times faster, a thousand times faster, right? And so that has to have benefits. That has to make companies better. The issue is we're not seeing those benefits.

5:54Alex Finn:So to me, that doesn't feel like a reflection on AI. That feels like a reflection on the incentives, which Naveen just kind of talked about, which is these leaderboards and say, hey, everyone use as much AI as humanly possible. Just because you're using a ton of AI doesn't mean you're producing good things. So I think it's more of a reflection on people are using this incredible intelligence, which I think is revolutionary the way it is already. Just using it on wrong things, wasting it, doing the wrong things. Because if you use it the right way, it's undeniable. You get so much more done. You do.

6:26Alex Finn:I mean, let me clarify a little, though. You know, I think what I mean by it's not quite there at the same level. Like if I hire a senior developer, someone who has 15 years of experience and I turn them loose to go architect and build some backend thing, you know, like they're going to make good decisions for extensibility. They're going to make it debuggable. They're going to deal with security, you know, all of this kind of stuff. You know, that's not quite true with AI today. Like, you know, it depends on how you use it. If you use it really kind of high level or, hey, go build this application, you get like weird stuff sometimes.

6:58Alex Finn:And it's not really quite production quality. And I know that as someone who's written a lot of code and most people do. But so that's what I mean. I can't turn it loose at that level. But what I can do is, like you said, make that 15 year developer very, very productive in the time that they use. But so that's that I think that's what I mean by we're not quite there where we can really trust its output to say this is production quality. That's the issue, right? That's the fundamental issue is you see what all these companies, the CEOs doing layoffs are saying in their kind of canned announcement.

7:29Alex Finn:oh we have non-technical people shipping production code which is like kind of crazy like that's where the tokens are being spent you still need technical knowledge you still need to understand how the systems work and if you understand how those systems work you have absolute superpowers the issue is we have and this is no offense to product managers or anything we have product managers shipping production code that makes zero sense it's actually where's the fence we have we have bloggers shipping code and it's terrifying to see me be able to put things on the internet. I guarantee you I'm leaking S3 buckets everywhere that I go.

7:58But I think this touches on an important point, which is if AI isn't quite to the level of intelligence that we want it to be at yet, that means that frontier models are the closest to that end goal. And all models that are a generation behind or a 0.1 release behind are further away from kind of acceptable intelligence. And that's why I think frontier models have managed to retain their pricing power in the market. Because if you could take Kimi K 2.6 from this year and take it back to 2025 this time, you'd blow minds, right? But compared to Opus 4.8, it feels a little bit lackluster. So I think that that's maybe why, Naveen, people are still willing to pay, I'm going to call it top token dollar for these models because they're at least close to.

8:38Alex Finn:Well, you know, what's interesting is, so we see this problem internally. Like I said, we use a ton of AI for everything, like software, algorithms, research, hardware design. We do all of this with AI. And what we find, and I'm actually guilty of it myself, is that I'm doing something that I don't actually know know what the output's going to look like, really. I mean, I can look at it and say whether this is good or not, but I don't really know how it's going to look. I'm not architecting it in my head up front. And so it's actually very hard a priori to say I need a great model or not so great model.

9:10Alex Finn:I would say 95 % of the times I don't need the frontier model, but the 5 % of the times I do, then, well, I just want to do it. So I just get the front, I just get the big one, you know, whatever it's 4.8 or 4.7 or whatever. And I'll just use the best model because I like that way. I'm like, I just mitigate the risk. So that's actually not a good thing for expense, right? No, no, but I was thinking about this this morning. And I think that the companies that are the most enthusiastic about AI and think that it's going to improve quickly and are in the most competitive spaces are the ones least likely to take out, just to stay with Anthropic for the sake of examples, Opus 4A and Jopin, Sonnet 4.6, right?

9:43But if you're more of a middle market company, I mean, dear God, Sonnet must feel like a revelation. So I mean, to me, it sounds like almost like a routing problem, Devine. Something needs to be there to tell you what you need to use. Alex, how do you handle the routing question? I know there's tools for this. Some people do it by hand. What's your kind of advice on this front?

10:03Alex Finn:There's kind of the way I handle it and there's the way I think businesses should handle it. For me, I have every subscription. I have the$200 Claude, the$200 Chat GPT. And if you understand kind of how these systems work and you're not just trying to rack up as many tokens as possible, these subscriptions are still unbelievably generous. Like I literally use it beginning of the day to end of the day, seven days a week. And I'm not getting anywhere close to the limitations on these$200 plans because I'm going in like a surge and I know exactly what I want the AI to change, right? I think a lot of people are kind of shotgun blasting, changing things.

10:39Alex Finn:So point being is like if you're struggling with limitations, you're just kind of a solopreneur or something, I would try to spend more time understanding your systems better so that you don't have to keep doing these shotgun blast prompts, which cause you have to go back, fix things, or you're doing the wrong thing. I'd also educate yourself too. I spent a lot of time studying the different models. I have Quen 3-7 running on a DGX Spark right now. There are some tasks that I don't need done this moment, and I don't need maximal intelligence. And for those things, I hand it to the Quen, and I come back an hour later, and the code's done.

11:15Alex Finn:And there's different workers for every single task. You just need to understand what you're doing and what's available to do those things. Did you catch that flex Naveen? Did he, did he, what's that piece of hardware you have sitting there running Quinn? It's having a, I mean, this might be the most entitled thing anyone's ever said or a privileged thing anyone's ever said, but it's having a, like the entry level NVIDIA computer, like a flex now of DGX, but it's$4 ,000. I mean, I don't know. It's not a, it's not, not a flex. I mean, people used to be proud of their new iPhone. I feel like we've got up several price echelons.

11:45I mean, if I were to flex. Sorry.

11:47Alex Finn:Maybe I'm the poor on the show, but I mean, it felt like a flex. If I were to flex, I'd mention the three Mac Studio Topline 512GB I have on my computer, but I'm not going to mention that, so I'm not flexing. I'm just going to flex on the 512 B300s that we have to play with. Damn. What do those cost each? I mean, we don't have them physically. Oh, okay. Oh, man. What do they cost? I would say B300 is probably about$40 ,000 each. something like that and then the supporting yeah that's well yeah I have a I have an iMac M2 that I run Olama on sometimes so can you buy B300s Naveen if I wanted to right now could I buy one like if you want to physically buy one if I wanted to get access to one could I do it you mean access or physically buy it like those two different point being is these 512 Mac studios they're not they don't exist anymore you can't buy them anymore so like yours might be more expensive but mine's like a yours vintage it's vintage all right can't get it this raises and actually a good point which is like where we're putting our money there's been a lot of talk about you know people now are spending more on tokens than people which is to me kind of a a blip in time not kind of a problem totally but people are really rebuilding how they build companies i've talked to so many founders that are working on super flat structures super small teams um really developer led approaches to going to market.

13:14And Naveen, you've sold a couple of companies, one to Intel, one to Databricks that I have in my notes, just from memory, actually. Databricks is a big company now. You left, you're building a small company now. You have learnings from, you know, really the starting days to megacorp status. How are you structuring unconventional? And do you think that's a model that other people should mimic? Because Alex has talked a lot about the solo kind of like one man plus agents model. I'm curious about the new trad startup with agents model, if that makes sense.

13:44Alex Finn:Yeah, we're more on that range of things. I think we're about 40 people now, actually not quite 40 yet. It's flat, flat, flat. Like, I mean, everyone can talk to me or anyone else. We do have kind of general areas, of course, where people focus and do their research, but each person uses tons of agents. So, and what's interesting is this whole idea of like putting software developers out of work is completely false. I'm seeing it in real time. So we are, I would say, leading edge on the way you build a company because we just started from scratch several months ago. My CFO, I'm not joking. My CFO is not your traditional CFO.

14:21Alex Finn:He has a kind of finance background, but he also has an engineering degree from Waterloo. So it's not your traditional CFO. So he's a super smart guy. He's actually come in and said, like, you know, there's a bunch of things we need to do. And he built a, uh, basically a system that takes in every candidate cross references it with all the papers that we look at. And so like this candidate just applied and they were on this paper that you discuss and highlights it basically built these like ongoing agents. And so actually what's interesting is he did that it's taken him a lot of time, but he was able to figure it out and use a vibe coding and things to get it done.

14:57Alex Finn:And now it's a tool that we use internally as production. And he is now overwhelmed. He has too much to do. He needs software developers to help him do these things and support the requests. So I'm sorry, Naveen. Glad that you have such a technology forward leadership team, but is that net positive or is that a net negative? Because it sounds like your guy got busy with the code and then gave himself the need for more human headcount, which from a high level sounds backwards to me. No, no, no. So what happened is like, it basically allowed us to just do a lot more than we would have done individually.

15:31Alex Finn:So everyone has these things where, you know, you have like your greenhouse, right? And people are sending resumes in and whatnot. And, you know, there'll be a person who sat in your in your greenhouse for six months. And you're like, oh, crap, why don't we reach out to this guy? Right? That is literally what happened here. We had someone who sat in the pipe and for like three months, and we like, how do we miss this? So he started like building an agent to comb this stuff. And now we don't miss anything. So I think what we do is have way better coverage than what we had before, because of those agents.

16:01Alex Finn:And now we need people to basically come in because it's worthwhile. To me, 100 % worthwhile to hire someone to make sure that stuff works well. No, that makes sense. Now, Alex, on the other hand, you're doing kind of the one person plus agents. Now, Naveen's people are building agents and then therefore need more people. Have you reached a point in your journey with your current companies in which you need to actually span your flesh and blood staff? Yeah, I mean, I am approaching that point. I raised pre-seed about a month ago and we're gonna do another round in about a month. and we need as many developers as possible.

16:30Alex Finn:Luckily, I live near Stanford. I'm looking for as many kids that just graduated who are desperate for jobs as possible. I know a Stanford graduate. He's here on the show with us. You should get Naveen to come work for you. It would be fantastic. Oh, perfect, Naveen. I didn't graduate. Oh, I'm so sorry. You have to have a degree. Sorry, Naveen, can't work here. Well, no, I have plenty of degrees. I just dropped out of Stanford specifically. You need a Stanford degree. I'm going to stick this in right here. Naveen got his PhD at Brown, right, Naveen? Yeah, yeah. Yeah, yeah, yeah. So up the street from me, up the street from my in-laws, there is Brown, an excellent school, and everyone should consider it, not just David.

17:03Okay, Al, it's about to you.

17:05Alex Finn:Yeah, no, I don't understand the whole narrative around developers are disappearing either. We are not even close. And again, I believe AI is revolutionary and has totally changed the world. But we're not to the point where, like, you don't need technical knowledge anymore. You still need technical knowledge. You just have superpowers if you have technical knowledge. And that means two things. One, still valuable at technical knowledge. You still need developers. Two, if you're able to superpower these people, it doesn't make sense why you'd want to get less of them rather than more of them. If I have these superheroes, I want as many superheroes as possible.

17:45Alex Finn:I'm not using all the productivity to get rid of them. I want as much productivity as I can. So I think the narrative is kind of made up by doomers, to be quite honest. Let me try to frame that. So we talk about Jevon's paradox a lot. as things get cheaper, we use more of them. If developers can do a lot more, they become more effective and therefore cheaper on a per dollar basis and therefore people want to consume more. That actually makes good sense to me. But we're seeing these agents that people are putting out in the market. Finn, you do a lot of this. Naveen, sounds like you are doing it as well, which are driving up just massive token numbers, if you will.

18:18So we're seeing this come up in the CPU space, the GPU space, memory, Naveen. It's kind of a pretty wide range of bottlenecks. So where do you think unconventional is going to fit into this and how soon? Because what I would not like to see is the world go, American AI companies are too expensive. We're now going to pivot entirely over to open weight Chinese models and move the center of gravity away from the good old US of A. So I'm hoping that we can find a way to make the cost of frontier intelligence as we improve models cheaper quickly. So I'm curious when you're going to arrive like Gandalf on the white horse, when the sun rises on the third day and save us.

18:54Alex Finn:Yeah. So maybe let's go through some of those, some of those constraints and bottlenecks. You know, if you look at it, ultimately, what we call it TCO, total cost of ownership is what matters. So it's like, when you pay, you know, three bucks, a GPU hour or something like that, what is what is going into that three bucks? So the fundamental constraints are clearly manufacturing of the chips, and packaging of the chips, and then, you know, components of the of the of the whole package, like memory, then there's the that's like on the capex side so there's like a you know uh how much it costs to actually build and deliver the equipment then there's actually running that equipment which is now primarily dominated by energy what's happened over the last several generations is uh it was much more of a capex game like call it 10 years ago running a data center was much more about the equipment cost amortizing the equipment cost than it was about energy I, you know, like the A100 generation, you know, these numbers, you know, take them with their error bars on them.

19:54Alex Finn:But we ran them pretty tightly at Mosaic. And, you know, A100 was, let's call it between 7 % and 10 % of that TCO was energy. And roughly, yeah, that's it, right? And, you know, there's cooling and energy. Those things go together usually. But then you have networking and floor space. and you know but most of the most of the cost was actually capex amortization of capex then every generation that's come along we've gotten cheaper at manufacturing silicon and putting more stuff in it uh and potentially have new features like lower precision all that kind of stuff so what's happened at that is you get more performance but you scale that performance with power and the cost per unit area of the chip dropped so now you start to move more and more toward the opex which is predominated by energy so uh every generation a good rule of thumb is we've roughly doubled the amount of the percentage of tco that became that's that's energy so okay so wait a100 h100 uh then we did uh grace hopper then it was vera now it's blackwell so that's six five generations i less than that really it's a i would call it a100 then the h100 series like GH100 is still an H100.

21:08Alex Finn:And now we're in the black well. So GB and Vera, all of those things are kind of variants of that. So really three major generations, you can call it A100, H100, B200. So what is the now percentage of TCO for current gen NVIDIA GPUs in terms of power? Yeah, it's pushing up against 40 % now. And so the next generation, I think, will exceed 50%. So we're going to be in this place where basically that's where I project in three to four years, we're completely energy constrained. It's actually not manufacturing constrained at all. So people talk a lot about the energy wall and all, I'm sorry, sorry, the, the, the memory wall and all of that.

21:46Alex Finn:And it's all true, but I think energy is going to dominate in the sort of five, six year timeframe. And that's really what we're trying to solve is like, we actually don't have an, a memory wall per se, because we're, we're part of our system is largely von non von Neumann, which we can talk about, but ultimately what we're trying to solve is, can we make something two to three orders of magnitude more power efficient? So deliver a token at two to three orders of magnitude less energy, and then we get around this energy constraint. You have politely dodged my timeline question. So I love all of this, and I appreciate that you're building a lab, and that involves research with uncapped timelines to some degree.

Read the full transcript

22:24Not uncapped.

22:25Alex Finn:No, not uncapped. Let me do that again. A research lab that involves perhaps longer timelines than a quarterly result there we go correct uh so just ballpark me am i am i gonna see something from you guys that i can that i can use or test or buy in the next three years five years three months i just don't have a good vibe for what your pace is going to be yeah i would say when we have our full-blown products uh we're probably three years away from that right now which is faster than i anticipated i had actually said it would be five years uh initially things are going faster and i do see that those will accelerate because of AI.

23:01Alex Finn:So I'm kind of pricing in that acceleration, if you will, on the timeline. So I do think we'll probably be in about three years. Now, that being said, we are building artifacts right now. So we'll be releasing a new model that works on top of what we call dynamical systems, which is a key non-Von Neumann concept. And so that's going to be released in several weeks, actually. I want to get over to Alex, but tell me, explain for people who don't know Von Neumann in the way that you're using it. I think people have mostly heard of Von Neumann probes as a sci-fi concept. moving. So just break that down for us.

23:30Alex Finn:Yeah, von Neumann is really the concept on how we build computers today, where we have kind of siloed memory and compute. And there's basically a connection between them. It's a memory interface, if you will. So basically, you have to you pull some some data from memory, you do something to it, like an arithmetic operation, and you write it back. Every computer that we know of that we built works this way. Non von Neumann means that we don't have a strict separation between compute and memory and actually dynamical systems or physical systems like your brain work in this way. They actually do both together.

24:04Alex Finn:And that's a concept that we're, we're, we're going to be exploiting. So just to double click on that, essentially my brain is full of, of neuron soup and the, the computer is the software. The software is the computer is the just there. That's right. And also the memory is the compute and the compute is the memory. All right. Alex, I want you to weigh in on what we're talking about here and kind of where you're seeing TCO as one of the leading lights of kind of the personal agent space. Interestingly enough, my first job at a startup, we had a load balancer in a closet and we were so happy we could afford a load balancer.

24:37We were very proud of ourselves. And we've gone all the way back now to look at my hardware in the closet, amazingly enough. And you're politely saying, hey, I got some serious hardware, but it's weird to me that we're talking about that as an edge in a very software focused line of technology.

24:55Alex Finn:Yeah, I, you know, it's funny. Every time I talk about hardware, local models on Twitter, I immediately get 90 % replies going, oh, those models are stupid. Why would you ever use them? Opus is so much better. Well, there's advantages to being able to have unlimited, dumber intelligence, right? It's not as smart as Opus 4.8, but it's still, you know, six months behind. It's still Sonnet 4.5 level, the local intelligence. And there's an edge to that, right? Because now you have unlimited intelligence that can run 24 seven, three 65, and that unlocks a new level of use cases. So one thing I'm doing right now is I have a Hermes agent powered by Quinn three seven on my multiple Mac studios and spark.

25:39Alex Finn:And it's constantly all day scraping Twitter, Reddit, other social media sites for opportunities. So my new startup I'm building, Henry, it's around the idea of finding autonomously opportunities online and exploiting those opportunities for the user. I'm basically running the prototype for that right now on my local models, on my computers, and they're able to go all day, find data, find information, and then ping me when it finds specific opportunities I can exploit. And this is something people don't really understand is that when you have unlimited intelligence, when you have local models running, you can unlock whole new things you can do, things that can watch your computer all day.

26:23Can we talk about the opportunities that you're unlocking here? I think that's a really interesting point that I want to better understand. You did a video recently on Hermes use cases, and I think getting from what it can do in broad to what it can do in micro is going to be useful for folks that are listening.

26:37Alex Finn:Yeah. So I am a strong believer that the reason why the sentiment is so low about AI in America is that most people are not getting value out of AI. They go on chadgbt.com, they say, tell me a fart joke, and then it tells a joke, and then you're like, oh, this is stupid, I'm never using this again, right? They just don't know how to use it. They don't know how to get value out of it. And so I'm trying to figure out how to fill that gap. So to be more specific about what I'm doing, I'm trying to build a system where you can go in, Alex, it learns about you, your skills, your interests, learns you got kids, you're an excellent father.

27:12Alex Finn:And then it goes and it finds opportunities online. Okay. Here's Alex's skillset. Here's a challenge someone's having on Reddit r slash parenting that Alex can solve. And then autonomously builds the system for you to exploit that challenge. So you to build the solution for that challenge based on your skillsets. This is only possible if you have kind of this autonomous intelligence, always watching. Right. And so I think if we built a system for people where an AI got to know them deeply, their skill sets, what they're doing, and constantly looked for opportunities to use those skill sets to create value, that could turn a lot of people onto AI in America.

27:53Alex Finn:And so that's why I think the advantage of local hardware is you can have intelligence doing things like that for you at all times. It's actually really funny that you bring this up right now because there's a company that announced funding just in the last day or two called Townie. I think Andreessen may have backed it. I don't have this pulled up, but that's close enough. And it's literally what you're describing. It's like an AI that's supposed to be able to kind of go out there and find all your personal contacts and help you. Naveen, based on what Alex just said, I'm curious, what is your personal agent setup?

28:22Because on one hand, you can just hire an assistant to go forth and do your schedule for you. Or you could spend the time setting up your own automation. So what have you chosen to do as a startup CEO today?

28:32Alex Finn:You mean in terms of like how I do my scheduling, that sort of thing? I mean, are you an open-claw guy? Are you a Hermes guy? Or are you just going to your Google Calendar yourself and looking at your day like some sort of troglodyte Neanderthal? I'm still a troglodyte. Me too. Yeah, I look at my Google Calendar. I sort of like, I have an assistant who's a human who still does this. I encourage everyone to use AI to make their job easier and faster. But yeah, I'm still a troglodyte. I use Apple Notes for everything. Um, you know, I, I have like 10 plus years of Apple notes of all of my thoughts.

29:05Alex Finn:I write them in there religiously. Um, yeah, that's Google docs for me. Like I, I, my last two jobs ago at crunch base, I got totally Google docs pilled, uh, before we even use that phrase. And now it's how I think, but here at the twist, we use notion and I've had to completely relearn how to do work. Yeah. And after being dragged by my non-existent hair, kicking and screaming for two years, I've come around to it. But yeah, it's interesting how we've become wedded to tools. Like, do you guys remember when they changed Office to have the ribbon up top versus the traditional bar? My parents had a small business and they were, it was months of complaining about that change.

29:42Alex Finn:I remember that too. It's like, why is this thing here? They had the little thing where you could disappear it also. Yeah, but I mean, like it was better. Having all those horrible dropdowns was not good. Alex, how are we going to get people like, you know, not my parents per se, but let's say people that are less AI forward that have gone to chadgpd.com, asked for a, I'm going to change your example, a sonnet about flowers and getting them to go, hey, that was not what we're talking about. When you see headlines about data centers, headlines about AI, headlines about people trying to do more with this technology, how do we get them into this world that we all think is progressing quickly and will unlock, hopefully, a lot of GDP growth?

30:20Alex Finn:Yeah, I think there's many things to it. I think you look at countries that are doing it well. One of those countries that are doing it well is China. In China, when Open Claw was released, they literally had festivals in public spaces where grandmas were lining up to get Open Claw installed. Right. But here everyone thinks it's like the worst and it's drinking all our water or something. And like that water thing. Yeah. Yeah. I'm not even going. It's so crazy. I might even go into it. But it's I think there's multiple sides. I think the biggest issue is the marketing. I think we have absolutely horrendous marketing right now.

31:01Alex Finn:And I think it's a lot of people's faults. I think one of the biggest people's faults is the CEOs that are laying off people right now. Right. In 2020, we had 0 % interest rates. I was in middle management at a public tech company, MongoDB, at that time. Not to out anyone, but the command to all middle managers at that time was hire as many people as you possibly can and pay them literally whatever they want. I'm not even, that was the command in 2020. It was a beautiful time. Well, it lasted. It was. I wish I was an IC at that point, not a middle manager. I was asked for anything. But point being is, now we're paying for those mistakes because we've had elevated interest rates for years now.

31:47Alex Finn:And what are we doing? Instead of saying, hey, we've been really irresponsible last five years, we're going, oh, well, AI efficiencies, everyone's fired, right? AI is incredible. Everyone's fired. Not that we weren't prepared for market conditions. Not that we overspent like crazy. Every CEO is putting out this canned tweet. That's like, oh yeah, AI is amazing. We have product manager shipping code. It's over, right? But we talked about flat structures, small teams. And I don't think you can have a company of 50 ,000 people if you're going to have this flat series of small teams to Devin's point about how he's building his startup.

32:21So how do we mesh this idea that to take advantage of these tools intelligently at the corporate level, we have to be super flat and not that wide with the idea that we all also agree with, that a lot of these layoffs have nothing to do with actual AI automation, but they're just using that as a false flag to wave over the top of them to avoid saying, we screwed up at MongoDB, we hired Bob for 400K a year, and Bob's worth 40.

32:43Alex Finn:Yeah. Yeah. I mean, I think there's different things to it, right? Yes, the structure of a company changes with AI implemented, but at the same time, if the company was responsible the last several years, they're not laying off 30 % of the company to make it so there's no middle managers. Why can't middle managers just become ICs? Why do we just have to fire literally every single middle manager in the company? Right. And so the point being to come back around to it is we have a marketing problem in America. People think AI is the devil because the CEOs, because the politicians that are profiting off of saying AI bad, here's a bill to ban AI.

33:22Alex Finn:Right. We have we have politicians going on X going, yeah, we have to stop all AI research. Stop it all. It's done. You know, I'm not going to mention Bernie Sanders name, but we have politicians going out there doing that. right profiting so we we just like we just have such a major marketing issue that we we have to kind of fix here in this country i was actually in dc this week uh and i was talking with people from the government i'm not gonna call out who but you know all the big all the big people that were that they would that way you think about involved in this like commerce and stuff like that sure and uh this is actually exactly what i said i said we we have a perceptional a perceptual problem.

33:59Alex Finn:And people right now are starting to protest data centers being built near them. And a lot of it, almost all of it is based on misinformation. The water thing is completely false. You know, that cancer rates are higher is completely false. I think when you have energy generation, that may be true, but with data centers, it's not. And I think this actually hits at a more fundamental part of the problem is that, so yes, you have this thing that feeds into that narrative of like, oh, CEOs are saying they're firing people. But I don't think those people are, the middle America people who are protesting data centers aren't the ones who are getting laid off.

34:39Alex Finn:So that's not where they're feeling it. I think the perception is that there's Silicon Valley that's running away and the billionaires are being created and we're not part of it. And so I actually put it back on myself and our industry a bit more to be a bit more thoughtful of how do we involve the public? Like weird things have happened. You know, my previous employer is, is guilty of this. They've stayed private for very long. I've told, I have brought this up ad nauseum with the CEO of Databricks, as I'm sure you've been told, but like, I, yeah, you care more than I do, but I'm still pissed off about it.

35:16But your, your point is that companies stay private so long, all the values extracted before they list. And then the upside is essentially precluded from the normies.

35:23Alex Finn:Exactly. And I think people are feeling that like, hey, this thing is happening. It's running away from me. All the quote unquote elites in the coasts in New York or in California are getting all the value and we're getting fucked. Right. That's basically what people are feeling. And I think the sentiment of like, I hate AI is more about that than it is about like all the things that people are talking about overtly. So what do we do? Because I talk to founders, I mean, three to four or five a week for Twist, and everyone's just excited, optimistic, full of energy. The future to them is bright.

35:59The trees are green. The sun is out. And then I go on the local Providence, Rhode Island subreddit, and people are talking about their energy bills. And they do have a boogeyman in mind, correct or not. It is precisely and exactly AI and data centers. And this is just me reading the normie room, if you will. Yeah.

36:18Alex Finn:But what's interesting is before 2020, when I was at Intel, I used to go to China quite a lot. They were my customers when I was at Intel, and I spoke to people there. And there was an energy there. People were hungry. They wanted to win. And the younger people there were super focused on AI. So I think what we see in China is a different sentiment where the normie feels that um ai is a superpower and it is a benefit to give give them competitiveness we see it as a boogeyman because somehow we've screwed up the narrative i i actually do blame the the doomers like and i specifically will call out anthropic on this like they have sown this narrative and over and over again it's going to destroy the earth and this and that it doesn't help it really doesn't freaking help they build amazing models great but stop it stop so i don't disagree with that, Naveen.

37:11But I do have a question about how you think about Anthropic. Do you think they're being sincere?

37:15Alex Finn:So, you know, I had this conversation with Jason, actually, Calacanis, last time I was on the show. And he seems to think, yes, they are sincere, that they believe that they are building, you know, the next deity or whatever. That's the way he put it. Maybe they are. From my experience, I think a lot of people there are sincere in that they think AI could destroy the world, but I'm like, why are you working on it then? Right. If you, if you seriously believe this, why do you feel righteous in what you're doing? And that's, what's weird to me. I'm like, then maybe work on a way to make it better or safer or something.

37:53Alex Finn:And they claim they are like, yeah, they would argue that they are with project last wing and, and, you know, making the world secure with mythos and so forth. But I don't see a way to fix the PR problem that AI has in the near term. And I'm really worried that it's going to become such a political issue that we're going to see this block progress on the hardware and power generation level. The two things, Nibian, that you're talking about that matter so much. And we're going to end up with Alex talking to a smaller room of people about how to get going with AI, how to build cool things because everyone's going, absolutely not, I don't want that.

38:24Get that AI slob out of my face. And it could retard our own growth, our own progress. I mean, it's just, it's an overall net negative, but I don't have a pitch. I don't have a solution or anything to bring to the table. So I don't want to complain too much, but we got to do something.

38:37Alex Finn:Well, one of three things are going to happen. One of three things will happen. Either there's the best case scenario, which is the leadership decides, hey, we're putting this country in the wrong path. We're going to have chaos and lose to China if we continue on this path and telling everyone AI is the devil. Let's we don't need to exactly work together, but let's like make our messaging what the truth is, which is this is an incredible technology that empowers everyone. That's number one. That'd be the best case scenario. Then there's the medium case scenario, which is there's chaos in the streets and people get angry in these protests around data centers drinking water.

39:12Alex Finn:It just gets to the point where the hands are forced by these companies or they'll keep getting rocks thrown through their windows. That's number two. And then there's the worst case scenario of all these, which is the Bernie Sanders of the world win and are able to legislate. These people have no idea how AI works or really capitalism or the economy works. They end up winning because people are so upset and they end up legislating this stuff, which kills our economy. And we have to give 50 percent of every A.I. company to the government, which would be the stupidest thing to ever happen in history.

39:42Alex Finn:Those are the three ways. All right. All right. I want to I didn't mean to get political. That's not political. That's just like, you know, guys, I'm going to get political. I got to go political. Naveen didn't have to. He used to go to D.C. He went to China. Now he has to go to D.C. to figure out what the hell is going on. This is inherently political. Let's spend one minute on this and then we'll get back to fun technology whiz bangs for the audience. But the Bernie Sanders idea of putting a chunk of equity from these companies into the national trust, to me, is not that far off from the government buying a stake in all the quantum companies, backing individual foundry firms.

40:14Agreed. So I feel like, ironically, the theoretical party of free market has already taken us into state capitalism as an acceptable way to approach industrial policy in the AI era. So why are we so opposed to Bernie's idea? Other than that, 50 % is way too high. But, you know, I mean, I don't know. I wouldn't mind if 5 % of Naveen's company and Alex's company were both in the National Trust. And that could save Social Security as birth rates fall. Maybe we need something radical to solve this.

40:42Alex Finn:So I actually don't disagree. I don't think it's a crazy idea. I think, like you said, 50 % is crazy high. And you can't destroy the incentives we have right now. That's the key. We cannot do that. But we do need to involve the public somehow in the upside. We need to show the public that AI is a win, is a competitive advantage, and somehow let them share in the benefit. it. Yeah, that has to happen. And the problem with Bernie's thing is that I think you go and own it. And let's say, you know, the value goes up and basically gives you more revenue to the government and then it feeds into bureaucrats who do nothing with it.

41:21Alex Finn:And that sucks, right? You're not you're not putting money where it's going to be used to actually drive stuff forward. I think that's what I have a problem with. But I do almost feel like, hey, if there's some way to, you know, provide training for people to use AI more effectively. To Alex Finn's point, somehow we use that money in a way that continues to compound the advantage. Just one point I'll make here is the reason why taking 50 % or 25 % or even 1 % of every company and putting into some trust, seizing private property is fundamentally un-American. We should never have policy where seizing private property is the fix to things.

42:01Alex Finn:So there just has to be solutions other than seizing private property. The moment you start seizing private property, you're messing with all of the incentives, which fundamentally just changes how the country works, right? So as Naveen just said, instead of seizing private property, why don't we incentivize people getting value out of AI? Why don't we give everyone in the country a$20 Chad GPT plan, Plus, we have an initiative where we spin up educational services where everyone gets taught how to get value out of AI. That's how everyone gets value out of it. Why is everyone getting value out of it?

42:39Alex Finn:It's us just going around taking things from people and redistributing it. That doesn't make any sense. Well, and actually the contrast, the trust idea versus like the Lutnik idea. And I'm not necessarily saying the Lutnik idea is great. It's weird. It is state ownership. Spell it out for us if you don't mind. Well, basically, he already did this with Intel. He bought 10 % of Intel with the government. The government owns 10 % of Intel. Strange, right? But the way he's looking at it is like, all right, well, if we figure out policies that make Intel more successful, that 10 % goes up in value.

43:14Alex Finn:Now the government can invest more money into other companies and compound it. It's kind of like being a VC, right? I've met people who do that job for a living, but this takes me back to Microsoft. I used to be a Microsoft beat reporter back in the day. And I would always press them. Why don't you guys have a venture fund? Look at what Google is doing. Look at what these other companies are doing. And they always would kind of look down their nose and be like, well, you know, it's not really accretive to our balance sheet, which is a polite way of saying we're too rich for a poor man's games like VC investing.

43:42But it provided signal later on. So they got into it in 12 and so forth. And so maybe, maybe, but I'm not convinced that that's something that we could get everyone to cheer behind. We have to find something that doesn't just appeal to us, but that someone on Main Street actually goes, hey, they're doing something for me. They're giving something in my domain. A government stake in Intel is a highly technical, well, for the average person, a highly technical transaction they don't really understand. I thought it was a public company. What does public ownership mean? That's the level they're at.

44:15Alex Finn:Also, it's not clear what the government, even though it appears their investment was a really good one. And I don't think it's clear to 99.9 % of Americans how they benefit from that. Right. The average Americans. Oh, Trump, you, you, you know, you have a five X, your Intel investment, but they just don't see the connection between that and their life getting better. But they can see their life getting like that might be true as well. Let's be honest. Intel going up in value since since the U.S. bought a chunk of it has zero impact on my life. It doesn't even really impact that month's increase in the national debt.

44:49It's it's it's small potatoes. Welcome potatoes, but small potatoes.

44:54Alex Finn:It's like a corporate VC kind of in the government. But I think, like, let's look at examples where at least perceptually there's a technology that helps people. You know, like people, for whatever reason, have gotten behind like auto manufacturing, right? They're like, oh, I can see it because there are jobs created and they know what a car is, right? And somehow they see it as like, well, you know, when there's government intervention here, I benefit from it. So we kind of need to come up with a narrative where we show that, right? We show that the everyday person is getting a benefit. Their cost of something is coming down.

45:28Alex Finn:Their access to something is going up. Like we need something tangible because right now we're all living in our Silicon Valley bubble. Every one of us, myself included. And talking about agents and this and that, the person in Nebraska has no freaking idea what an agent is, nor do they care. It doesn't impact their life. I mean, I hope Alex gets them to care. Yes, I hope you do. I'm working on it. And shout out to you. I think you're actually, no BS. I think you're actually a very important AI educator and evangelist. And I think it does matter. But to Naveen's point, the guy in Nebraska cares about the Cornhuskers football record and the price of fertilizer, neither of which are currently being assisted by AI.

46:07That's right. Yeah.

46:08Alex Finn:So we need to at least start to show like, hey, fertilizer came down 20 % over the last year. You know, this is why. like create those narratives right and and we do this i think then we'll have to me this is this is incredibly important to national security because otherwise we lose this race right if the if the if the public is not supportive of ai no matter how much silicon valley cares it's it's not going to matter that's gonna be what about so another idea that i've seen people talk about and by the way i didn't mean for us to end up so much on the how to save the public conversation about ai but i think also all the startups founders that are watching this care about this so we'll stay with it for for one more question.

46:46What about when you build a data center in a community, let's say it's near your house and it does plug into your grid and does use some of your water. I'm not gonna say that very loudly, but what if there was something that came to a voluntary tax by companies that are building these data centers or operating them or getting value from them to directly pay into that municipality, county's coffers, and then people could see directly in their community that bench, that bench came from AI because we put a data center in us And then people could compete to have access to data centers in their community.

47:16It could become a net positive versus a, my electricity bills are going up. And honestly, I don't think it would be that much of a cost compared to the, the CapEx and so forth of building at one gigawatt data center, which is like, what, 50 today?

47:31Alex Finn:Something like that. Yeah. Yeah. I don't know, Alex, what do you think about my, my brilliant voluntary tax idea? It depends how it's executed. I just my gut fundamentally, as opposed to any sort of seizing or taxation, because I, you know, and again, not to get political, I just don't believe increasing taxes all of a sudden creates things. I think if there was a very specific system put in place where the money taken from the data center with no middlemen taking a dollar out of that goes into building something productive, right? What if you built a data center, tax it at a small percent, and then literally 100 percent of that money went to giving AI accounts to everyone in that area?

48:11Alex Finn:I think that is not bad. The issue is our system overall in this country, Republican, Democrat, doesn't matter. when you take money from one place and put it somewhere else, somehow along the way, 80 % of that money disappears and we don't know where it went. Right now, as long as that's the way, I just don't think taxation is the solution. But if we had a system in place where it was like very clear, this money goes here and every single one of those dollars is back in helping the people, then I think that's pretty good. This actually goes to an old school model, right? If you look at old companies, like old automotive companies, or pharmaceutical companies, any manufacturing company in a local community, they did exactly this.

48:48Alex Finn:They improved the community and they did it voluntarily because they know they learned through iteration that the backlash is worse. And I think we in Silicon Valley haven't done that. And I actually blame SaaS inadvertently because I think SaaS is just sort of divorced from the physical world, right? Very much so. You don't really have to interact with the physical world, but now it's coming back hard. We're interacting with the physical world in real ways. and you can't go in and just be like the guy that's going to be the wrecking ball that kind of puts in a data center and screw all you guys, whatever you think.

49:21Alex Finn:You got to think holistically. Like, all right, well, yeah, we're putting the data center in, but you know what? We're also building a better rec center. We're improving road access. We're doing things that the public will feel. Yeah, if I was doing this, if I was going to bring a data center near Providence, I would be like, I'm going to pay for the buses for five years. Just like buses are free now in Providence. And you know why? know why? Because your community supports AI and AI supports you. It's a good sales pitch. It totally is. Okay. Bringing us to a conclusion, I want to end that somehow we ended up in kind of a bummer there for a bit.

49:52I think we're all a little worried about politics and the backlash. So let's have a little fun to wrap up. I'm so glad I have you both here because I think we'll all have different views about this. But Anthropic, finally, filed to go public. Everyone's very excited about this. It's a private IPO filing, so we don't have the numbers yet. We're still waiting. But the fact that they've gotten to that point, I think, shows quite a lot of maturity and an imminent IPO, maybe Q3 this year. So Alex, if you had to guess, what is the IPO valuation for Anthropic? And are you a buyer at that price?

50:21Alex Finn:It feels like it's probably going to land somewhere around 1.2 to 1.5. Am I a buyer? I'm actually not going to be a buyer of any of these major IPOs coming up, OpenAI, Anthropic, or SpaceX. I'm a big believer in all three companies. I'm a big believer in all their leaders. I'm a big believer in all their tech. I think they are cornerstones to the country and our economy and will be for a very long time. I just can't remember a time where there was an extremely hyped IPO. And then a few months later, the price was higher than where it was when it came out. And there's also some interesting things happening on where rules are being bent for these companies as well.

50:57Alex Finn:SpaceX is going into like the S &P and the Nasdaq on like day one, when typically it takes like a year to do that. So there's just too much weird things, too much hype, too much weird things. I'd rather let price discovery happen and then make up my mind from there. It just seems like it typically when anything is money based, you want to zig when other people zag. That's just kind of how it works. And right now it feels like 99 % of people are zigging. And so I'm just going to kind of play it safe and zag. Naveen, same question to you being a brat, guess of price and also interest in purchasing.

51:33Alex Finn:Yeah, I think Anthropics, yeah, around the 1.2 range. I mean, okay, positives. I'll answer your question in a second, I promise. Positives are we do involve the public and the retail investor, which is great. I think SpaceX has bent some rules. Some of it has been around trying to involve the public more. So they actually want to bring thresholds down for people who can get into the IPO price, stuff like that, which I think are all good things. I think retail investors tend to distort value and price discovery quite a lot because they're not super analytical. Yeah. Yeah. So I don't know if it's a good thing or a bad thing, but at least we involve the public, which is sort of the intent of the market.

52:15Alex Finn:Whether I'll buy or not, I mean, I don't know. I mean, I agree with Alex that the leaders are all, I believe in all of them. Elon is hard to bet against, as we've all seen. But man, the market, the actual revenue of SpaceX just doesn't feel that it justifies the valuation. If this was like$500 billion IPO, 100%, I'd be there in a heartbeat. But at 1.75, I'm like, oh, crap. I saw this one as well. This is pretty funny. The Elon magic multiple of 10. That feels too high to me. I probably will not buy into that one. and I probably am wrong. You know, but... This is why all of my money is in zero cost index funds because no offense to the world, I've done a lot of fantasy stock trading and let me tell you, I'm worse than the masses.

53:11So I'm fine with that. Guys, a real trade. I want to give you some shout outs before we go. One, Naveen, unconventional AI is unconf.ai. Anything else you want to shout out? Roles you're looking to fill? Things you want to stress before we go?

53:24Alex Finn:Yeah, I mean, people who are interested in nonlinear dynamics and how that works with AI. Absolutely, we're looking for you. People who are interested in new kinds of hardware circuits, weird, wacky stuff, physical design, any of that stuff, come talk to us, even like modeling these kinds of things. So yeah, we have some really interesting roles going on right now. Awesome. And then Alex, meethenry.ai is where Henry Intelligent Machines PVC lives. Anything else you want to shout out? No, if you are looking to get into AI agents, which I really think you should, check out my YouTube. but meethenry.ai is my next startup I'm building, building an AI agent for everyone to create value.

54:00Alex Finn:So check it out. Hell yeah. I appreciate y 'all. This has been This Week in AI. We're back with more awesome founders from the world of AI here on your podcast feed. My name is Alex. We'll see you next time. Bye.

From the publisher

The future of AI isn't about whether the model is smart enough. It's about whether we can afford to run it. We dug into the AI cost panic, the energy wall that's coming for compute, and why "developers are disappearing" gets the economics exactly backwards.This week's roundtable: Naveen Rao (CEO of Unconventional AI, building brain-inspired analog chips, formerly sold companies to Intel and Databricks) and Alex Finn (founder of Henry Intelligent Machines and Creator Buddy).Thank you to our exclusive sponsor: PayPal Open, One Platform for All Business: http://paypalopen.com/Timestamps:0:00 Cold open1:21 Welcome to Episode 162:44 Is the AI cost panic real, or just "token maxing"?5:08 It's not the intelligence, it's how people use AI9:40 Surgeons vs. shotguns: prompt discipline & matching models to tasks13:10 Naveen's path from Intel and Databricks to Unconventional15:08 Why developers aren't disappearing18:37 How energy overtook CapEx in the cost of compute21:34 The energy wall & getting to 3 orders of magnitude more efficient25:52 AI's PR problem & the data center backlash27:55 China's hunger vs. America's AI boogeyman30:38 Data center taxes, equity stakes & the politics of AI upside37:54 The Anthropic IPO & how these founders actually invest🔗 Guests:Naveen Rao, Unconventional AI: https://unconv.ai | https://x.com/AlexFinnAlex Finn, Henry Intelligent Machines: https://meethenry.ai | https://x.com/NaveenGRao🔗 Host:Alex Wilhelm, This Week in Startups: https://x.com/alex🔗 Referenced in this episode:Unconventional AI (analog chips for AI): https://unconv.aiMosaicML (acquired by Databricks): https://www.databricks.com/research/m...Nervana Systems (acquired by Intel)Creator Buddy: https://creatorbuddy.ioQwen (open-weight model Alex runs locally): https://qwenlm.aiNVIDIA DGX Spark: https://www.nvidia.com/en-us/products...Anthropic (filed to go public): https://www.anthropic.comHenry Intelligent Machines: https://meethenry.ai/🔗 Subscribe and follow:Newsletter and all platforms: https://thisweekinai.ai#ThisWeekInAI #AI #UnconventionalAI #NaveenRao #AlexFinn #AnalogComputing #AIcompute #AIenergy #TokenMaxing #AIlayoffs #AnthropicIPO

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