LLMs, robotics, ML infrastructure, and AI applications.
# MiroFish Brings Swarm Intelligence to Forecasting, Backed by Shanda *A student-built project leveraging CAMEL-AI's OASIS simulation engine is gaining traction for predicting everything from public opinion shifts to novel endings.* MiroFish, an open-source prediction engine built on multi-agen...
The U.S.
# DeepMind Pioneer David Silver Departs, Betting LLMs Won't Reach Superintelligence The architect of AlphaGo is going his own way — and he thinks current AI is heading down the wrong path. According to The Decoder, David Silver, one of DeepMind's first employees and the lead researcher behind A...
# Anthropic's New Measure Finds AI Hasn't Yet Displaced Workers — But Could Anthropic is trying to build a better early warning system for AI-driven job displacement.
# OpenAI Launches ChatGPT Go, an $8 Monthly Tier OpenAI is adding a new entry point to its ChatGPT subscription lineup.
# Claude Now Draws Charts and Diagrams Right Inside Your Conversation Anthropic is giving Claude a whiteboard. Starting Thursday, Claude can generate charts, diagrams, and other visuals inline during conversations — not as generated images, but as interactive HTML and SVG elements that render d...
# NanoClaw Puts AI Agents in a Virtual Cage With Docker Partnership The security problem with AI agents is getting a new solution: put them in a box.
# A Father-Son Duo Just Raised $5.3 Million to Give AI Agents a Memory AI agents are getting ready to make purchasing and scheduling decisions on your behalf.
# Google's Genie 3 Can't Hold Its Worlds Together for More Than a Minute Google DeepMind is being unusually honest about Genie 3's limits. According to a talk at the Game Developers Conference, as reported by Gamefile and covered by GamesIndustry.biz, the company's generative AI world model sta...
# South Korea Wants Its Own OpenAI.
Four decades after the 1983 film WarGames imagined a teenager battling an AI-controlled supercomputer threatening nuclear war, that science fiction scenario feels eerily prescient.
# Berkeley Researchers Build Algorithms to Identify Which LLM Features Actually Matter When something goes wrong inside a large language model — a biased output, a nonsensical answer, a safety failure — the natural question is: *why?* Which specific combination of inputs, training examples, or i...