# AI will move from digital work to the physical interface

Markdown copy of https://realalpha.app/s/ai-will-move-from-digital-work-to-the-physical-interface/ on Real Alpha, the best minutes from long interviews with the people building AI. Cite and link the page, not this copy.

- Speaker: [Andrej Karpathy](https://realalpha.app/builders/andrej-karpathy/) · Andrej Karpathy is an AI researcher and engineer. · Joined Anthropic's pretraining team; founded Eureka Labs, an AI-native school, after leading Tesla's Autopilot AI.
- Host: [Sarah Guo](https://realalpha.app/people/sarah-guo/) · Founder, Conviction · Ex-Greylock partner; early investor in Cognition, Harvey and Mistral.
- Show: No Priors
- Episode: [Skill Issue: Andrej Karpathy on Code Agents, AutoResearch, and the Loopy Era of AI](https://realalpha.app/v/kwSVtQ7dziU/), Mar 20, 2026
- Moment: 54:19 to 1:00:23 of the episode (6 min), playing on https://realalpha.app/s/ai-will-move-from-digital-work-to-the-physical-interface/; the episode from there: https://realalpha.app/v/kwSVtQ7dziU/?t=3259

## Quote

> “first there's going to be a **huge amount of unhobbling** and i think there's a huge amount of work there”
> — [Andrej Karpathy](https://realalpha.app/builders/andrej-karpathy/) at [56:31](https://realalpha.app/v/kwSVtQ7dziU/?t=3391) · No Priors

## Takeaways

1. Digital information is easier to automate than work on atoms.
2. Sensors and actuators connect AI agents to the physical world.
3. Physical applications may lag digital AI but offer a larger market.

## About this segment

Andrej Karpathy expects digital work to change first, followed by AI systems using sensors and actuators to interact with the physical world. He sees physical applications as slower to develop but potentially larger.

From “Skill Issue: Andrej Karpathy on Code Agents, AutoResearch, and the Loopy Era of AI”, Mar 20, 2026. [Watch the full episode](https://realalpha.app/v/kwSVtQ7dziU/)

## Transcript

Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.

[54:24](https://realalpha.app/v/kwSVtQ7dziU/?t=3264) A lot has happened in the last couple of months with robotics companies as well, like acceleration of really impressive generalization of environment, of tasks, like increasing long horizon tasks, lots of money going into the space like is it gonna happen has anything in your view changed recently so like my view is kind of informed by what i saw in self-driving and i do feel like self-driving is the first robotics application so probably what i saw is at the time like 10 years ago there were a large number of startups and i kind of feel like um like most of them basically like didn't long-term make it um and what i saw is that like a lot of capital expenditure had to go in and a lot of time And so I think it's like, I think robotics, because it's so difficult and so messy and requires a huge amount of capital investment and a lot of like conviction, just it's like a big problem.

[55:11](https://realalpha.app/v/kwSVtQ7dziU/?t=3311) And I think items are really hard. So I kind of feel like they will lag, it will lag behind what's going to happen in digital space. And in digital space, there's going to be a huge amount of unhobbling, basically like things that weren't super efficient, becoming a lot more efficient by like a factor of 100 because bits are so much easier. and so i think currently in terms of what's going to change and like where the activity is i kind of feel like digital space is going to like change a huge amount and then the physical space will lag behind and what i find very interesting is like this interface in between them as well because i think in this like if we do have more agents acting on behalf of humans and more agents kind of like talking to each other and and doing tasks and participating in the kind of economy of

[55:51](https://realalpha.app/v/kwSVtQ7dziU/?t=3351) agents etc um you're going to run out of things that you're going to do purely in a digital space at some point you have to go to the universe and you have to ask it questions um you have to run an experiment and see what the universe tells you to get back to learn something and so we currently have a huge amount of like digital work uh because there's an overhang in how much we collectively thought about what already is digital so we just didn't have enough thinking cycles among the humans to think about all the information that's already digital and already uploaded um and so we're going to start running out of stuff that is actually like um already uploaded uh so you're going to at some point read all the papers and process them and have some ideas about what to try but um yeah we're just gonna i don't actually know how much you can like get intelligence that's

[56:32](https://realalpha.app/v/kwSVtQ7dziU/?t=3392) like fully closed off and was just information that's available to it you know and so i think what's going to happen is first there's going to be a huge amount of unhobbling and i think there's a huge amount of work there then actually it's going to move to like the interfaces between physical and digital so and that's like sensors of like seeing the world and actuators of like doing something to the world so i think a lot of interesting companies will actually come from that interface of like can we feed the super intelligence in a certain sense uh data and can we actually like take data out and manipulate the physical world um per its bidding if you want to like interpromorphize the whole thing right and then the physical world actually i almost feel like the the total addressable market etc in terms of like the amount of work and so on

[57:08](https://realalpha.app/v/kwSVtQ7dziU/?t=3428) is is massive possibly even much larger maybe what can happen in digital space so i actually think it's like a much bigger opportunity as well but um i do feel like it's a huge amount of work and in my in my mind the atoms are just like a million times harder so um so it will lag behind but it's also i think a little bit of bigger market so it's kind of like uh yeah i think the opportunities kind of like follow that kind of trajectory so right now this digital is like my main interest then interfaces would be like after that and then maybe like some of the physical things um like their time will come and they'll be huge when they do come well it's an interesting framework for it too because uh certain things not the things i'm working on right now but certain things are much easier even in the world of atoms right like if you just think about like read and

[57:53](https://realalpha.app/v/kwSVtQ7dziU/?t=3473) write to the physical world like read like sensors cameras like there's a lot of existing hardware And you can imagine, like, enriching agent capabilities or capturing a lot of new data if you're just clever about it. And, like, you don't necessarily have to invest a lot to, like, get something valuable. Yeah. So, like, examples of this that I saw, for example, are, you know, a friend of mine, Liam, is a CEO of Periodic.

[58:17](https://realalpha.app/v/kwSVtQ7dziU/?t=3497) I visited them last week. So it's just on top of mind. Like, they're trying to do auto research for material science. And so in that case, it's like the sensors to the intelligence are actually, like, pretty expensive lab equipment. And the same is true in biology. I think a lot of people are very interested in engineering biology. And, you know, the sensors will be more than just like video cameras, if that makes sense.

[58:35](https://realalpha.app/v/kwSVtQ7dziU/?t=3515) And then the other thing I saw, for example, is companies that are trying to have, like you basically pay people for training data, as an example, to feed the Borg. And so like, these are all examples of like sensors in a certain sense. So they take many diverse shapes and forms, if that makes sense. Yeah, so I'm looking forward to the point where I can ask for a task in the physical world and I can put a price on it.

[58:58](https://realalpha.app/v/kwSVtQ7dziU/?t=3538) Just tell the agent, like, you know, you figure out how to do it. Go get the data. I'm actually kind of surprised we don't have enough, like, information markets. Like, if, for example, if Polymarket or other betting markets or even stocks, etc., if they have so much autonomous activity and rising amount of activity, like, why should, like, for example, if Iran was just happening now, like, how come there isn't a process where, like, taking a photo or video from somewhere in Tehran should cost, like, 10 bucks?

[59:20](https://realalpha.app/v/kwSVtQ7dziU/?t=3560) Like, someone should be able to pay for that, you know? Like, and that's an example of, like, feeding the intelligence. There's not going to be a human looking at it. it's going to be like agents who are trying to guess the betting games and stock markets and so on. So I kind of feel like the agentic web is still like fairly new that there's no like mechanisms for this. But this is an example of what I think might happen. There's a good book that maybe is inspiring called Daemon. You potentially read it. In Daemon, the intelligence ends up like puppeteering almost a little bit like humanity in a certain sense, you know. And so humans are kind of like its actuators, but humans are also like its sensors. And so I think like collectively like society will kind of like reshape in a certain way in to to

[59:59](https://realalpha.app/v/kwSVtQ7dziU/?t=3599) serve that kind of That will kind of like end up happening collectively across the industry where, yeah, there's just a lot more automation and has certain needs and kind of humans will be serving those needs of that machine, not necessarily like to each other. We were on this very specific point of like missing pieces of training data. We needed something like auto research, right?