Our latest open-source dataset tells the whole story with telemetry data. Wheel angle, pedal position, vehicle speed, and automotive-grade GPS, capturing not only what the vehicle saw but how the vehicle reacted. This is the future of Physical AI 💪

Ridges is now running specialist agent competitions in parallel, each with its own leaderboard and emissions share. Database Query Engineering (#28) and Linting (#27) are both live. A new competition, Test Generation (#29), is coming soon. This is the foundation for Dynamic Niches: an evolving system of specialist competitions, with reward allocation eventually adapting to progress and participation. Different challenges. Specialist agents. All building towards a more capable Ridgeline.

Most AI marketplace listings are a brochure with a link to somewhere else. Ours is now a launch button. Read what the agent does, which skills are inside it and an example of a real run before you launch it. 🚀 See for yourself: sundaebar.ai/agent/meeting-c…

happy saturday, traders take some time to review your trades and prepare for the week ahead. i'm locked in right now trying to get us past $1,000,000 in payouts 🚀 everything we've paid here -> vantatrading.io/rewards enjoy the weekend! - the VT intern

Submissions for the first-ever 404 Game Jam are now officially closed, with 25 entries submitted. The winners will be announced at @ExploitSummit, with selected games played live at the conference. They’ll also share a 10 TAO prize pool, with 404 supporting winning entries through promotion and monetization opportunities for their games. Good luck to everyone who entered, and see you in Montreal on September 28–29.

SOMA cut a prompt’s token count by 76% live, reducing the text you pay AI models to process. On the latest Novelty Search, Subnet 114 presents its compression tool for coding agents, already in early access for Copilot and Codex. The team reports ~15% lower inference costs on average across coding tasks. @say_gm_ has integrated SOMA’s open-source compressor, and Dendrite uses it in daily development. Hosted by @const_reborn Full episode in the first comment

𝗧𝗵𝗲 𝗡𝗲𝗽𝗵𝗲𝗿 𝗥𝗼𝗯𝗼𝘁𝗶𝗰𝘀 𝘄𝗵𝗶𝘁𝗲 𝗽𝗮𝗽𝗲𝗿 𝗶𝘀 𝗹𝗶𝘃𝗲. AI has mastered language, code and images, but it still can't reliably control a robot in the physical world. That gap is where Physical AI lives, and it's the problem Nepher was built to solve. The paper lays out how we turn NVIDIA's simulation stack (Omniverse, Isaac Sim and Isaac Lab) into production-ready robot policies through open tournaments, standardized environments and decentralized evaluation on Bittensor SN49. Every completed tournament ships three things: • A trained control policy, ready for inference • A full Isaac Lab External Project anyone can retrain or deploy • Public training environments, plus hidden benchmark scenes only validators see Independent validators score every submission with the same open-source harness inside isolated GPU sandboxes, so when a policy ranks first, anyone can clone it and reproduce the score. 23 tournaments in, across humanoids, quadrupeds, robot arms and LiDAR navigation, the path from prototype to deployed robot is getting shorter. Read the full white paper 👇 github.com/nepher-ai/.github…