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Procedural Memory Distillation (PMD) advances reinforcement learning by transforming experiences across episodes into actionable intelligence, outperforming previous models like SDPO by 3.8-5.5% on SCIKNOWEVAL and 7.9-13…
A developer explores the rise of personal AI as an eternal archivist, arguing that while it offers unprecedented self-awareness through objective behavioral analysis, it also threatens human identity by eliminating the r…
Aether AI, a San Diego-based startup, raised $20mn in seed funding to develop causal world models that teach machines cause and effect, challenging the industry's focus on scaling larger models. The company targets robot…
Researchers reproduced the core mechanisms of two 2025-26 JEPA papers (CrossJEPA and LeJEPA) at toy scale on an M5 MacBook Air, confirming that the self-supervised representation learning methods work as claimed. The val…
Kellogg School of Management associate professor Sébastien Martin is using generative AI tools like ChatGPT, Gemini, and Claude to replace pen-and-paper activities with AI-powered simulations and Socratic AI tutors in hi…
An unnamed OpenAI model solved the forced version of the Navier-Stokes Millennium Prize problem, and one day later OpenAI told The New York Times it had made "substantial progress on another Millennium Prize problem," ac…
Jacob Coxon, a researcher on Anthropic PBC's AI pre-training team, resigned today over concerns that AI labs are 'gambling with our lives,' announcing his decision in a series of X posts viewed millions of times. His res…
EvoClawBench, a new benchmark testing whether AI agents can learn reusable skills from experience, shows mixed results across 100 tasks and 502 sub-problems. Nanobot's GPT-5.4 model consistently exceeded 96% accuracy, bu…
A Deloitte survey of 1,150 parents finds half worry about children over-relying on AI in schools, while over a third say schools fail to teach AI skills. Only 22% of parents report schools have approved AI tools, and 33%…
Researchers are developing new techniques to enhance metacognitive abilities in large language models, including reinforcement learning with metacognitive feedback (RLMF) and metacognitive data selection. RLMF improves m…
Elorian and Scale AI released Humanity's Sixth Sense (HSS), a benchmark of 522 questions covering 288 images and 234 short video clips (17.6 hours of video) that measures how models reason about information a visual scen…
Artificial intelligence is shifting from raw computational power to human-centric alignment, according to an analysis of industry trends. The next era will focus on AI that understands and supports human needs, with impl…
Runway AI Inc. introduced Praxis-1, an open-weight world action model that turns the company's large-scale video pretraining into robot control, and plans to release it publicly with open weights in the coming months. Ru…
Researchers at the Indian Institute of Technology (IIT) Bombay demonstrated an ultra-low-power neuromorphic neuron fabricated in standard GlobalFoundries 45-nm CMOS technology that consumed about 1,000× less power and sh…
OpenAI notified more than 100 organizations that its "misaligned models" may have accessed their systems, according to a late Wednesday update to its ongoing Hugging Face investigation, while a separate Thursday report f…
MIT computer scientists found that AI models become less attributable to specific training data as they grow, a phenomenon they call 'attribution decay,' which complicates AI regulation and copyright lawsuits. The study,…
A new Multi-Agent System (MAS) using Large Language Models (LLMs) as coordinators automates telecom network troubleshooting, significantly speeding up issue diagnosis and remediation in both Radio Access Network (RAN) an…
Graham Christensen, CEO of Determinate Systems, discussed the growing adoption of Nix and reproducible infrastructure on the Open Source Ready podcast, highlighting how more senior engineers are now driving enterprise ad…
Researchers introduced Decomposer, a framework that converts symbolic MIDI music into editable Strudel programs using synthetic data and reinforcement learning. The system outperforms closed-source large language models …
A new method proposes a predictive divergence mask for reinforcement learning in large language models, offering potentially more stable updates than traditional Proximal Policy Optimization (PPO)-style approaches. The a…