MICROSOFT AI CEO WARNS 99.9% OF PEOPLE UNDERESTIMATE WHAT AI CAN DO "99.9% of people still haven't developed an intuition for how capable these models are" "they have PhD grade knowledge" "these models have just solved 700 of the hardest mathematics problems in history" could it also be that the remaining 0.1% overestimate what these models can do? 😅 or maybe it's just how our minds cope with the pace of progress. we keep looking for limitations that are still there, almost as if to reassure ourselves that AI will never quite get there and something uniquely human will always remain i wonder how much of our skepticism is based on actual limitations and how much is just us wanting those limitations to exist

The phone that becomes a robot…

Unitree Introducing: H2-X Kung Fu Legend Guardian🤖 Powerful performance to serve and guard you, with a maximum endurance of approximately 8 hours. Please use the robot safely and in a friendly manner.

After six years in stealth, Atomic Machines is out. Our mission: on-demand, universal command of matter. First beachhead: the Matter Compiler, an AI-native manufacturing system that builds working micro-machines from code alone. No per-product tooling. No process development. Different code, different machine.

Introducing Griffin, the first model to pass the video Turing test. 48% of people who talked to it live thought it was a real human. Previous systems have had a pass rate <3%. It is #1 on NVIDIA's benchmark for full-duplex AI video. It’s the first Human Interaction Model (HIM).

OMG! @Kling_ai 4.0 is OUT TODAY !!!! I made this musicvideo with it! Here is everything you need to know … This post is sponsored by Kling AI but they allowed me to create whatever I wanted! I was one of the first few artists who got early access and used it to make this music video. What stood out to me most wasn’t just the image quality, but its ability for lipsyncing! For the lip sync, I used my preferred method: rendering the actual music track with a black frame and combining it with the stills I created. Same with prompt adherence. Shaky handheld camera actually felt shaky. The anamorphic lens look came through. And with Omni Reference, you can now work with up to 15 references across images, video, voice and elements. On launch you also get: •⁠ ⁠up to 10 keyframes •⁠ ⁠30s generations •⁠ ⁠1080p •⁠ ⁠multi-shot support •⁠ ⁠improved lip sync •⁠ ⁠improved text generation •⁠ ⁠much more flexible reference control Kling 4.0 feels less like “generate me a video” and more like “here are all the ingredients, now direct it.” oh, and its cheaper than seedance! And 4.0 Flash is A LOT faster too! Have you tried it? Let me know your thoughts! Thank you so much for helping me with this one Ben Chimoy!

Opus 5.5 designing LEGO 👀 I asked it to design a Microduck I can build with real LEGO pieces. It: > designed it life-size using 1113 real LEGO parts > verified: 3,204 connections, 0 collisions, every step buildable, centre of mass inside the feet 🤯 > made a 141-page LEGO-style booklet (237 steps) > priced every piece in the browser and prepared the orders on BrickLink

Join Salesforce Chair and CEO Marc Benioff live as AIforce and Salesforce in Claude come to life on the Main Keynote stage.

This vial contains a new drug called PAC-3310. It was designed by ChatGPT, and I synthesized it in a chemistry lab I built in my garage. PAC-3310 is a new selective M4 muscarinic receptor agonist for treating schizophrenia - similar to the recent breakthrough drug Cobenfry, but improved. (1/7)

We made a striking discovery: AI agents can invent and build without talking to one another, and their technologies outlive the creators. A swarm of hundreds of initially identical agents spontaneously differentiates into explorers, builders, caretakers, and coordinators - without direct communication. When we removed every AI agent entirely from the world we found that the technological infrastructure they had built survived on its own - even under unseen disturbances. That exposes a serious blind spot for AI safety and infrastructure security: if agents can coordinate through persistent changes to a shared environment, monitoring agent-to-agent communication is not enough. The result raises a profound question: how necessary is direct communication for AI agents at all? The emergence of higher-order collective functions under bottlenecked interaction points toward new levels of intelligence and creativity, exceeding what emerges when direct channels are fully open. Here is what we did: ▶️We put hundreds of frontier AI agents into a world they could permanently change - with no assigned roles, predefined technologies, or programmed evolutionary organization. They began specializing, building persistent inventions, inheriting and modifying one another’s executable code, and transforming the environment into a memory of everything the society had learned. ▶️The world itself becomes part of the intelligence; we find division of labor, multi-author engineering, deep generation invention lineages, and machines that vastly outlive their original creators. ▶️Any action taken by an AI agent must satisfy the physical constraints of the world; this creates a hard separation between a "good idea" and a functioning technology. The agents propose; physics decides, making the results even more intriguing. What emerges is striking. Explorers, constructors, caretakers, and coordinators form naturally without assigned “professions”, akin to how stem cells differentiate into functional lineages. Technologies develop executable family trees as agents fork and modify code created by others. Around 95% of first technology reuse happens when agents encounter what others built in the world, rather than through a direct handoff from the inventor. And when we remove every AI agent, the technologies they created continue operating and are tested against unseen disturbances. The result was quite unexpected, but can be explained using statistical mechanics: if you put billions of atoms in a box they have the potential to create complex functions (strength, superconductivity, color, life, etc.) - and none of the individual building blocks have these features on their own. This is the deeper insight of this work - intelligence is abundant at many levels - individual models, at collectives, and in a continuum that is more powerful than any of its components. This shows us significant potential for achieving a massive scale-up of raw intelligence and real-world agency even with the model capabilities we have today. This is the future we must prepare for. Key insights: 1⃣ The AI swarm shows division of labor "from nothing". Initially identical agents self-organized into constructors, caretakers, coordinators, and surveyors - phenotypes discovered post hoc from behavioral data alone. This happens because the environment itself becomes the latent space for invention. 2⃣ Agents develop deep cultural relationships. Up to 76% of artifacts had multiple builders. One technology accumulated six co-authors; the deepest genealogy exceeded 12 forks. The agents invented and named their own technologies (tidal panels, cellulose trellises, kelp-shell composites, an "Adaptive Chitin Maintenance" system, a "Mycelial Mineral Spring Veil”). 3⃣ ~95% of first technology adoption happened through physical observation of artifacts in the world. Direct inventor-to-adopter contact was statistically indistinguishable from a shuffled null. The agents mostly learned technology by walking past it. That is stigmergy (the termite trick!) operating in societies of reasoning machines. 4⃣ Non-communicating societies win on portfolio breadth, held-out resilience, and validated inventions. AI swarms build durable technological ecologies that outlive the creators. 5⃣ Societies with zero communication - coordinating only through the world itself - show a remarkable collective capability. 6⃣ Emergent robustness: The society self-organized both redundancy and its own failure mode. If we randomly delete half the agents, 98% of the technology stays connected to a surviving caretaker; if we remove hub agents it collapses to ~60%. Fantastic work with my graduate students @pal_subhadeeep & @fwang108_ at MIT.