AGI may arrive by turning humans into data. RGI won’t. Robots can’t learn the real world from scraped text alone. They need humans to show them, in space, in motion, in context. We’re seeing this in our simulation: people teaching a robotic arm how to water a flower. The

Santa’s newest intern is a bit stiff, but he’s got great precision ✱✱🎄 Holiday vibes in the sim today. May your latency be low and your rewards be high ✱✱

In 2026, decentralized robotics will enter a phase of rapid expansion, increasingly shaped by data-centric drivers. Crypto-native protocols make distributed data contribution and world modeling economically viable at scale, laying the groundwork for long-term advances in RGI.

the boundaries of "human intelligence" that VLA (Vision-Language-Action) models can acquire depend on the diversity coverage of their training data across tasks, environments, and interaction modes. Simulation provides a viable pathway to approximate a high-fidelity, highly

Simulation is, in essence, the formal reconstruction of the Robot-Environment-Task interaction process. As an intelligence hub, it offers a unified solution across multiple dimensions: Scalable and High-Fidelity Data Engine, Generalizable Model Pre-training, Embodiment-Agnostic

The paradigm repeatedly validated in language models is that "more data leads to better models." Robotics also follows the Scaling Law. Yet, when this paradigm is directly transposed to the field of robotics, the entire industry encounters a systemic bottleneck: the Robotics

We’re building an end-to-end intelligent stack — from simulation and synthetic data to robotics foundation models — to accelerate the emergence of robotic intelligence. At the core lies a crypto-powered loop: - Data Platform — incentivizing diverse human participation and

Full article on substack: https://t.co/5Pn9g3UScL

Bridging Worlds: Transferring Diverse Human Intelligence to Robotics General Intelligence — The Axis AI Manifesto We are moving from AI that Chats (LLMs) to AI that Acts (Robotics). But reality is messy. To master it, we built Axis--the End-to-End Scaling Infra for Physical AI.

(1/6) I’ve been reflecting on the "Why" behind Crypto x AI/Robotics. A recent post by @Old_Samster on Bittensor nailed it: Crypto coordinates human effort at an unprecedented scale. But as a founder building in this space, I want to take this back to first principles. What are

Ilya’s latest comments hit something fundamental: Humans display astonishing generalization from tiny samples and messy real-world feedback—the kind of capability no benchmark score can capture. In a future with stronger AI, he even imagines human–AI fusion as the natural

The future is now

Decentralized Intelligence is the undisputed operational logic for real-world robotics. We move beyond theoretical concepts, proving that AI’s greatest leap forward stems from universal collaboration, not isolation.

Transferring Human Intelligence into Robotic General Intelligence. Progress: 🟧⬛️⬛️⬛️⬛️