Steven Swanson

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I’m thrilled to share what I’ve been cooking up. My team is launching a new kind of social network – think less content, more commerce – and we’re offering early access to a select group of trailblazers and investors. Sign up now for consideration. list-lab.org/m/steven?follo…

Intelligence and understanding powered by curiosity and imagination. 🤔 #ActiveInference #FEP

@dwarkesh_sp Karl Friston, the most cited neuroscientist with 338k research.com/scientists-ran…

Looking for a neuroscientist to interview on my podcast. Keen for someone who can draw ML analogies for how the brain works (what's the architecture & loss/reward function of different parts, why can we generalize so well, how important is the particular hardware, etc).

Either you crack general intelligence -- the ability to efficiently acquire arbitrary skills on your own -- or you don't have AGI. A big pile of task-specific skills memorized from handcrafted/generated environments isn't AGI, not matter how big.

@craigss of @EyeOn_AI sits down with Professor Karl Friston to discuss the Free Energy Principle, Active Inference and and how it differs from neural net based methods used by OpenAI, Meta, Google, xAI, Anthropic, DeepSeek etc #FEP #ActiveInference #neuroscience

Former New York Times Technology journalist, Craig Smith, featured Karl Friston in his Eye on AI interview this week. The wide ranging interview covered: 1. How the brain works by making predictions - and what this means for AI. 2. VERSES' AXIOM digital brain. 3. Real world applications of Genius - including our work with Analog. 4. How representing uncertainty is critical - because it allows systems to know what they don't know - and therefore judge an action by how much it reduces uncertainty.

Jensen Huang on being a CEO. Strategy means deciding what not to pursue. The work brings pain, determination, and endurance. It’s an honorable job, but built more on suffering than fame.

Alright, let's quantify it. AI bubble, yay or nay?

@imprashantrai1 direct.mit.edu/neco/article/3…

@imprashantrai1 arxiv.org/abs/2002.12636

reinforcement learning + active inference = digital cybernetics revival

@RichardMCNgo The Free Energy Principle

I increasingly believe that there are fundamental principles which simultaneously govern the designs of well-functioning minds, organizations and societies. Once we pin them down with mathematical precision, we’ll understand the world more deeply than we can currently imagine.

Fascinating convo on the state of AI: #LLMs, #worldmodels, #agency etc @GaryMarcus perfectly describes the current zeitgeist as a #monoculture Still love Karl's description of deep learning: #rubbish 🗑️😆 #activeinference youtube.com/watch?v=cSYOiJ…

VERSES highlights 2025 physical AI breakthroughs with Genius: youtu.be/vKwJgc78bVQ

A video made by pixl8studio recreates the impossible, maze-like world from M.C. Escher’s famous artwork “Relativity.”

@humanoidsdaily This is promising research that answers LeCun's call for systems with world models and planning. verses.ai/blog/real-worl…

Our tweet on Yann LeCun's critique of the humanoid industry (that they "have no idea" how to build general AI) went viral. But his point is more specific than it sounds. He argues "generative models" (LLMs, video generators) are a dead end for robotics. He claims the only path forward is non-generative "world models" (like his JEPA) that learn physics by predicting in abstract space—not by generating pixels. So, what are the major players actually building? A thread... 🧵 x.com/humanoidsdaily…

@humanoidsdaily verses.ai/blog/real-worl…

Meta's Chief AI Scientist Yann LeCun offers a critical take on the humanoid robot boom. Speaking at MIT, LeCun claimed the "big secret" of the industry is that current companies "have no idea" how to make their robots "smart enough to be generally useful." He argues that while humanoids can be trained for narrow manufacturing tasks, a truly autonomous domestic robot is impossible without fundamental AI breakthroughs. For LeCun, this means moving beyond current generative models and toward "world model planning-type architectures"—systems that can learn to understand and predict the physical world. The future of these billion-dollar startups, he says, depends entirely on this next wave of AI research.

To spot consciousness, we must provoke it. Agency is the system's fight to minimize surprise (Friston's Free Energy Principle). ​When an agent breaks its pattern, it causes a massive belief update (high KL Divergence). This is only meaningful if the resulting action has high, non-algorithmic complexity (Kolmogorov). The energy required to process this surprise and update the model is dictated by Landauer's Limit. ​In real life, this "Bayesian inference" isn't digital: biological systems may use analog resonance—where internal frequencies (priors) couple with data—to instantly estimate new beliefs. Consciousness is the energy-costly process of constantly managing this chaotic update cycle. 🤯 AI generated image [Gemini].

NEWS: VERSES Recognized in Gartner® 2025 Emerging Tech Impact Radar: Spatial AI “The Spatial Web, where digital + physical systems converge, is the infrastructure needed to enable the next frontier in AI.” — Gabriel René, CEO 🔗 hubs.li/Q03PymVQ0 #AI #Gartner

The reason it is so important for everyone to keep pretending that AGI is definitely right around the corner is that there is now over $1T of investment riding on this belief (either already expended, or committed) Current (and recent past) capex cannot be justified by current use cases and technology (currently spending $10-15 to make $1). To ever be in the black you'd need dramatically better tech/applications, and you'd need them fast -- before current datacenters depreciate, which is a 3-5 years timescale

@TrueAIHound He’s either lying or a sucker being lied to

"If GPT-6 is 30 IQ points above GPT-5 and can work for days to months, the economic value will skyrocket" Imagine pretending to have high-IQ intelligent machines in datacenters powered by 30 GW of electricity (aka massive statistical cheating machines) but none of them is intelligent enough to walk into a random kitchen and boil and egg. 🤦‍♂️ I know intelligence when I see it. This is not it. 🙄