Jason Fox

Founder at Noumenal Labs. Building Physical AI.

[Jason Fox @JasonGFox]

@aryind_ @AveaRobotics what is the actual latency though? in milliseconds

[Jason Fox @JasonGFox]

@arian_ghashghai 100% - we started out solving world models for robotics, then pivoted to building a vertically integrated robot to solve a real customer pain point. The deployment gap is a huge opportunity right now. Meanwhile, billions are going into humanoids, and they are still very far out.

[Jason Fox @JasonGFox]

@vytalow Just wanted to drop in and say that, first - awesome work! second, as you have rightly pointed out in your work, neurons don't learn using gradient updates. Take a look at predictive coding and active inference. Would he happy to connect you with my team for a chat if interested.

[Jason Fox @JasonGFox]

@mcuban Bandwidth may be an issue, but I'm more worried about latency. I don't care how much data I can pass around if I can't do it in less than 20ms.

[Jason Fox @JasonGFox]

@asimovinc Is that a transparent speaker I spy embedded in the chest?

[Jason Fox @JasonGFox]

@JacklouisP Pick any humanoid company in the West. Vertical integration is a part of the raise narrative and one of the reasons why they are closing such large rounds.

[Jason Fox @JasonGFox]

@asimovinc Honestly, if you can make a modular hand system that enables a user to choose along a spectrum of grip strength and dexterity for different tasks, that would be ideal. Right tool for the job, you know?

[Jason Fox @JasonGFox]

@cixliv I keep wanting ask. What are you using for remote control? Any teleoperation?

[Jason Fox @JasonGFox]

I think @cixliv has it right. Hard not to conclude that the near term use of humanoid robots that makes the most commercial sense is entertainment. Especially, since every demo video from Chinese manufacturers is literally robots performing martial arts moves.

[CIX 🦾 @cixliv]

Why humanoid robots, why not? A rant.

The humanoid form is the right form if you want generalized “physical AI”. As the method to train it will be human data, into a human-like robot.

Then economies of scale will make humanoids cheaper than specialized robots due to mass production. Thus making it lucrative to get generalized AI.

But there are four main issues: economics, data, hardware and distribution.

Economics are a problem because unlike ChatGPT that can be a pocket lawyer (thus saving you $1000 an hour) most blue collar labor is much cheaper. Replacing a $15 an hour job with a $50,000 robot (that will perform more poorly) is not economical.

Data estimates are Humanoid robot training data ≈ 0.000001% to 0.00000001% of LLM training data. The only way we bridge this gap is a massive data collection effort or very robust life like simulators burning through GPU farms all day.

Hardware: Humans have around 250 DOF while the top of the line humanoids have around 40 DOF. Although we don’t need all this degrees of freedom that a human has to solve most tasks. Humanoids now only last about 1-2 hours on battery life, most aren’t water proof, and still far from parity with the human body.

Distribution: Say we solve all the above 3 issues, we still need to mass produce the robots. “Physical AI” isn’t something we can simply access with a browser or a phone. You need to ship millions of robots in excess of 100-150 pounds that are more complex than cars all over the world. With huge raw materials and rare earth requirements. This will take time.

So while everyone knows the future is humanoid, it will take longer than people realize to become disruptive. So don’t worry about those blue collar jobs being taken by robots for a while.

But you know what will be lucrative in the meantime? Entertainment.

That is why at @rek we are aware of the limitations of humanoids, and will bridge that AI gap with entertainment. Entertainment that will set the framework for a product category that will forever change our world.

To become the next F1, with humanoids.

[Jason Fox @JasonGFox]

@theonlyAyo I agree that teleoperation is a fundamental part of the new robotics stack, but could one restate this as “human demonstration is the new programming language”?

[Jason Fox @JasonGFox]

@tkipf Sweet! I’ve had a similar idea for years. Just never the team nor time to execute on it. Glad somebody is. Great work!

[Jason Fox @JasonGFox]

We are officially entering into the humanoid robotic “gladiator” phase. A natural evolution given where the technology is(strong locomotion, limited agency) and humanity’s enjoyment of sport and entertainment.

[Jason Fox @JasonGFox]

@GoingBallistic5

[Noumenal Labs @noumenal_labs]

During this year’s NeurIPS afterhours, we’re hosting an intimate gathering of researchers, founders, and investors exploring the intersection of computation, thermodynamics, and embodied intelligence.

If you’re working at the edge of alternative architectures, stat-phys-inspired ML, or embodied intelligence, you’ll feel right at home.

What to expect:
• Thought-provoking conversations on alternative compute paradigms
• A curated group of technologists & builders
• Great food, great drinks, great company

Hosted by cyber•Fund, Noumenal & collaborators. Registration & approval required: https://t.co/bO6sNYhQJT

Looking forward to connecting with the people shaping the next chapter of intelligent systems.

@mjdramstead @cyberfund

[Jason Fox @JasonGFox]

@IntuitMachine @Scobleizer @kscalelabs This. There is also a broad belief that humanoids are not viable in any reasonable timeframe. The handful of VCs who do believe in them have already made their bets - Figure, Apptronik, etc.

[Jason Fox @JasonGFox]

@jloganolson Awesome work! Be sure to burn it all with fire after Halloween.

[Maxwell Ramstead @mjdramstead]

New blog post by @noumenal_labs: “WTF is the FEP? A short explainer on the free energy principle”: https://t.co/oZEuxaLJZZ

Really happy to share this one! We discuss the free energy principle: What it is, what it is not, what promise it holds, why it can be extremely useful, and why it has yet to live up to the hype.

[Maxwell Ramstead @mjdramstead]

New blog post by @noumenal_labs: “Grounded rewards in the era of experience: A commentary on ‘Welcome to the era of experience’”: https://t.co/80Y44Pudgv

Here’s the tl;dr:

• This post is a commentary on a new paper by Silver and Sutton, entitled “Welcome to the Era of Experience” (2025).

• Silver and Sutton (2025) provide a thought-provoking discussion of the last decade of research and development in the field of artificial intelligence (AI), and where the field is heading. The core idea is that we have reached a performance ceiling for AI agents trained via supervised learning from human data — and that we have entered a new epoch in the development of AI, which the authors call the “era of experience.”

• The era of experience, as the authors describe it, is a forthcoming phase in the development of AI that will be characterized by “grounding” in the real world, online action-perception loops, physical embodiment, environment-sourced reward signals, and online real-time experiential learning.

• In particular, Silver and Sutton argue that the era of experience heralds a shift from hand-crafted, user-specified reward functions and the heavy use of human expert feedback and supervision, towards “grounded rewards,” which are measured and evaluated by AI agents themselves by continually assessing the sensory consequences of their actions in real time.

• Here, we review and evaluate their argument. We enthusiastically embrace several aspects of their discussion and offer some constructive feedback pertaining to the learning of grounded reward functions.

[Jason Fox @JasonGFox]

Physical AI is a new frontier that presents challenges beyond the scope of current approaches to AI. Deep Learning works great in use cases where data is abundant, but in the physical world data is sparse and ever-changing. This necessitates a new set of architectures. Let's go!

[Maxwell Ramstead @mjdramstead]

I’m thrilled to share a blog post by @noumenal_labs: “From Natural Intelligence to Physical AI”:
https://t.co/FQMZV38IQO

Here’s the tl;dr:

• Physical AI is the next big wave of research and development in the field of artificial intelligence. Its proponents claim that Physical AI holds the promise of revolutionizing industry.

• But state of the art AI will not deliver on these promises, because it is not capable of understanding the structure, variability, and complexity of the physical world that we inhabit.

• Noumenal Labs is a newly formed deep tech company that is laser focused on building digital brains for Physical AI — so it can be deployed profitably, efficiently, safely, and at scale.

• We are using our unique, proprietary macroscopic physics discovery technology to build object centered world models that will power the brains of autonomous systems — unlocking machines that can act in intelligent and situationally appropriate ways in the real world, and that can adapt to a changing world in real time.

• Driven by key insights from statistical physics and cognitive science, in particular by Karl Friston’s active inference framework, the approach pioneered at Noumenal Labs unlocks the capability of machines to represent the physical world in the same way we do, enabling them to act safely and in alignment with human values — and thereby, to deliver on the promise of Physical AI.