Faced with software you've never used, you start by poking around and learning what happens 🧭 Until now, an agent meeting a new environment had to collect more data and retrain. That is costly, and a poor fit for private, ever-changing environments like internal tools. RSIAgent: Autonomous Exploration for Recursive Self-improvement in New Environments takes a training-free route. Three roles, a curriculum agent that picks what to explore, an actor that executes and grows memory, and a verifier that judges outcomes, find causal relations between actions and results inside the environment and store them in memory. It first explores broadly, then digs deep into hard boundary conditions, and finally freezes the memory for testing. On OSWorld 2.0, partial score rose from 71.97 to 78.98 and binary accuracy from 37.80 to 42.68. On a game development benchmark, overall quality went from 52.77 to 61.28. The authors also admit that accepted mistakes can become permanent rules, and that test-time compute is high. Raising performance with only memory from exploration, with no parameter updates, seems worth trying in production. #AIAgents# #SelfImprovement#

Faces and number plates never leave the phone. Every Vangrid capture is blurred on the device before the video is encoded. Unblurred frames are not uploaded, not stored, not recoverable. Buyers get a 3D model of the physical world. Never the people in it.

Face uniqueness checks are now live in PiVerify, and @PiCoreTeam has also attached price charts to its BlockExplorer, two usability upgrades landing on the same day. BSCN keeps every $PI story it has published in one place, from KYC migration to ecosystem apps and wallet updates.