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Video · 2026-08-14 · 58m · 6 moments

4 wild AI predictions from a $39B tech founder

✦ AI generated

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01
Prediction

AI will be 100 times bigger than the internet, becoming the dominant technological and economic trend of the next few decades.

Brett Adcock predicts AI will dwarf the internet in scale and impact, calling it a new type of computer that will transform everything from physical work to digital assistance.

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

02
Prediction

The future will split into two directions: AI in the physical world via humanoid robots, and digital AI-human symbiosis via personal AI assistants that function like a superhuman version of Iron Man's Jarvis.

Adcock describes AI's two future paths—humanoid robots for physical tasks and a digital AI partner that knows everything about your life, has perfect memory, and acts as a superhuman assistant always with you.

transcript

Brett Adcock: I strongly believe like AI will head in two directions like uh like and then at some point maybe even like maybe like head together like the first is we'll have AI out in the physical world that will like do everything in the in in the environment for you like laundry, dishes, cooking like run the supply chain and be in healthcare. The vessel for that is a humanoid robot. It's just a human form and it will just go out and do like you like want one piece of hardware that can like you know the hardware is capable of doing everything and you put like smart AI into it and it'll go off and do everything in the world. That's what Figure is working on. Separately than that, there's going to be this like really close like digital like AI to human symbiosis that forms. You're going to have like this very special thing that you can like talk to that's with you everywhere you go that will know all your stuff, have access to all your memories, have access to all your accounts and systems and be able to actually go do things for like a superhuman assistant. It'll be like um maybe the closest thing is like Jarvis from Iron Man and it will be able to do like it'll be like super human in almost every way. It'll know everything about your life. You'll be able to access it at any moment whenever you need it. It'll be in the background helping you out at all times.

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03
Claim

Current phones and computers are fundamentally the wrong interface for AI—HARK is designing a radical new AI-native device to replace them, not an incremental improvement like AI glasses.

Adcock argues that MacBooks and iPhones were designed 20 years ago and are 'complete rubbish for AI,' and that HARK is designing entirely new AI-native devices that will replace phones and computers, dismissing smart glasses like Meta's as poorly designed peripheral products.

transcript

Brett Adcock: you need to have um you need to fix the the interface to AI. 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. And it's like an upgrade cycle... They're going to be all AI computers and phones and systems and they're going to be great. They're going to be all real time. You can always access them... You'll be able to abstract away most apps. You'll probably not have an app store. or you probably have an AI operating system... In fact, like the metaglasses are probably one of the worst products I've ever bought. They're just horrible. They're horrible. Like I I can't even like figure out how to use it. It doesn't have its own network. It piggybacks on the iPhone network. It means your app needs to be open on your phone. The pairing's long. Like it doesn't work well. Like I can't think of any reason why I would need this thing strapped to my head for 14 hours a day. Like it's just like the wrong device.

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04
Claim

The real constraint for humanoid robots is not manufacturing scale but building true human-level intelligence—robots that can generalize to new environments they've never seen before, driven purely by neural networks.

Adcock explains that manufacturing robots is straightforward compared to making them genuinely intelligent enough to operate autonomously in novel environments. He spends 3-4 hours daily on the generalization problem and believes solving it would create a trillion-dollar company.

transcript

Brett Adcock: The hard problem is not that. We think we believe now the most important constraint to really solve is like building a really intelligent robot system to the world. Like there's a bunch of robots you can go buy now. You can buy some from China and you get them and they're complete crap. They can't do anything... Robots are like that now. Like where you can we can go manufacture a ton of them, but like if they're not really smart, like it's not really going to be that helpful. We're trying to crack like the true human level intelligence of figure... we really want to tackle like how do we make it so I can put it into any home. It can do every every every job I'd want it to do.

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05
Prediction

By 2027, AI voice agents will pass a full Turing test over the phone—humans will be unable to distinguish a real person from an AI system in a phone call.

Adcock predicts that within about a year, AI speech technology will advance to the point where a phone call from an AI system could fool anyone, with both a human and a robot calling and the recipient unable to tell them apart.

transcript

Brett Adcock: I don't know if we'll hit it this year, but certainly in 2027 you will hit like a full human Turing test with speech. You'll be able to take a phone call from an AI system on your phone and I'll be able to fool you guys. I'll be able to have like a human call you and a robot call you and I don't think you guys will be able to tell the difference. Uh that's that's a 2027 event I feel pretty strong about.

supports · 1

06
Claim

Working on harder problems is actually easier than working on easier problems because hard problems have less competition, attract better talent, offer non-linear payoffs, and are only incrementally harder relative to the massive increase in potential reward.

Adcock argues that hard problems are disproportionately under-served: they may be only 3-5x harder but offer 100-1000x the payoff, attract more committed people, and face less competition. He uses the example that humanoid robots are only ~3x harder than robot dogs but have a million times the market potential.

transcript

Brett Adcock: I believe that doing hard things is easier in many ways than doing easier things. Could you explain... 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... 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... you do humanoids, it's like okay, three times harder, but it's probably like a million times higher payoff.

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