Video · 2026-08-14 · 58m · 6 moments

$39B founder: “AI will eat the whole internet”

✦ AI generated

timeline · colored by role

Prediction◆

AI will be a hundred times bigger than the internet, fundamentally transforming every sector of the economy and society.

Brett Adcock makes a sweeping prediction that AI's impact will dwarf the internet's, driven by the speed and breadth of deep learning breakthroughs he's witnessing across his companies.

transcript

Brett Adcock: I think at a high level, I think the AI work that we're seeing here now is going to be so much it's going to be like a hundred times bigger than the internet. It's just like everything is just so it's just working so well. Like the system is working well like deep learning works and everything's happening faster than I would have think and my like you know having done like 15 years of like software and internet like it was just like nothing was happening faster on a trend line here it's happening like that in AI

provides context · 1supports · 1

Mechanism

You cannot build useful autonomous robots by relying on APIs and MCPs—you must give AI the ability to see a screen and use a mouse and keyboard like a human, because most services lack APIs.

Adcock explains that Hark's breakthrough is enabling AI to use computers like a human—moving cursors, typing, reading screens—because only one in a thousand websites have APIs, making API-based approaches fundamentally limited.

transcript

Brett Adcock: Fundamental to that thesis was like you got to figure out how to get AI to use computers general purpose. You would never hire an assistant that couldn't use a computer. So you got to be able to like give things out to it that can like do everything you can do. financial models, book flights, like order Door Dash, whatever you need to do, you need to be able to do it all autonomously, but only one in a thousand websites have APIs... That's what you have to do to solve like general purposeness for around a computer is you can't rely on API or MCP. You have to figure out how to like navigate like a human can.

Claim

Current phones and computers are fundamentally the wrong interface for AI—they were designed 20 years ago and are 'complete rubbish' for AI use cases, so entirely new device form factors are needed.

Adcock argues that smartphones and laptops are antiquidated interfaces for AI, and Hark is designing radically new hardware to replace them—an AI operating system on purpose-built devices.

transcript

Brett Adcock: You have like um AI over here and a human and you have like an old hardware system in between like a call like a MacBook or iPhone. They were designed 20 years ago. They're complete rubbish for AI. They're not the right interface. So, we went out and we are out there designing what we think comes like after the iPhone for AI... We're designing what we think are the next generation of AI devices that will kill the phone and computer.

provides context · 1

Data

There are only 20 to 30 people in California who truly understand how to build world-class AI models, making top-tier AI talent extraordinarily scarce and expensive.

Adcock explains that Meta's aggressive hiring strategy is rational because the pool of people who truly understand pre-training, post-training, and supercomputing infrastructure is vanishingly small—perhaps 20-30 people in California.

transcript

Brett Adcock: I think there's probably my rough calculus now is probably like a rough back of the envelope is probably like 20 to 30 people in California know how to build really good AI models.

provides context · 1supports · 1

Mechanism◆

Working on hard problems is often easier than working on easy ones because hard problems have less competition, attract better talent, offer outsized returns, and the difficulty increase is nonlinear relative to the payoff.

Adcock argues that doing hard things is paradoxically easier because there's less competition, better people want to work on them, investors prefer binary-payoff bets, and the difficulty-to-reward ratio is nonlinear.

transcript

Brett Adcock: Everybody's trying to do easy things. When you work on harder things, you have like less generally like overall probably there's like first order like less competition. You have probably like a hard thing probably means like it could be a potential like really big TAM, really big exit if it works. You have this like you know risk reward trade. You have folks that probably want to work on hard things probably like the best overachievers in the world that kind of want wants to work there. Generally like you know hard things have this like binary payoff for investments. They like really want to fund those things because we could have like a 100x return for the portfolio and I think there's like a nonlinear curve to scaling like here the difficulty here meaning like I think a lot of the hard things are not like 10 or 100 times harder I think the hard things sometimes are like two or three or four times harder maybe five times harder but they're not 100 times harder so you might have a hundred times better payoff but it might be like three or four times harder

extends · 1supports · 3

Example

Humanoid robots are only about 3-4 times harder to build than quadruped robots, but offer a million times higher payoff because quadrupeds have no real mass market.

Adcock uses the example of humanoid versus quadruped robots to illustrate his nonlinear difficulty-reward thesis: humanoids are modestly harder but open a trillion-dollar market versus a niche one.

transcript

Brett Adcock: I'll give you an example in robotics I think like largely building like quadruped robots like four-legged dog robots versus humanoids. Like probably humanoids are probably like three times harder than that. Maybe four. That's it. But like there's really no I don't think there's like really a real market for for humanoid like like those dogs, right? I think it's just like a niche thing. I don't think there's a real business for it... So like you do humanoids, it's like okay, three times harder, but it's probably like a million times higher payoff. Probably like a million x or a billionx higher ROI for that.

gives example · 1

Highlight slides

AI: 100x Bigger Than the Internet✦ from: AI will be a hundred times bigger than the internet, fundamentally transforming every sector of the economy and society.Speed of AI Progress✦ from: AI will be a hundred times bigger than the internet, fundamentally transforming every sector of the economy and society.The Paradox of Hard Problems✦ from: Working on hard problems is often easier than working on easy ones because hard problems have less competition, attract better talent, offer outsized returns, and the difficulty increase is nonlinear relative to the payoff.Nonlinear Difficulty-to-Reward Curve✦ from: Working on hard problems is often easier than working on easy ones because hard problems have less competition, attract better talent, offer outsized returns, and the difficulty increase is nonlinear relative to the payoff.Why Hard Problems Are Easier✦ from: Working on hard problems is often easier than working on easy ones because hard problems have less competition, attract better talent, offer outsized returns, and the difficulty increase is nonlinear relative to the payoff.

Related episodes

Video · a16z Podcast

Ben Horowitz on the Global Race for Tech, Power, and Influence

→

Audio · All-In Podcast

SpaceX-Cursor Deal, SaaS Debt Bomb, New Apple CEO, SPLC Indictment, Colon Cancer Spike

→

Video · Lenny's Podcast

The rise of taste, human authenticity and judgment in an AI world | Adam Mosseri (Head of IG)

→