Three arXiv papers push AI agents further: metacognitive self-modification, milestone-based RL lifting Gemma3-12B from 6% to 43% on WebArena-Lite, and hybrid workflows cutting inference costs 19x.
Terence Tao argues AI has cut the cost of mathematical idea generation to near zero, but verification remains as hard as ever - and our existing academic infrastructure wasn't built for what comes next.
OpenAI is in advanced talks to buy up to 50 gigawatts of fusion energy from Helion, the startup where Sam Altman holds a personal stake worth an estimated $375 million.
Anthropic launched the Claude Certified Architect exam and invested $100M in its Partner Network - free for the first 5,000 partner employees, $99 after. Accenture is training 30,000 people.
Krafton's CEO used ChatGPT to design 'Project X' - a corporate takeover strategy to avoid paying Subnautica creators a $250M bonus. A Delaware judge reversed everything and called it out by name.
An exclusive TechCrunch tour of Amazon's Trainium chip lab reveals how AWS is training Claude for Anthropic and now holds an $138B commitment from OpenAI.
NVIDIA's new Nemotron-Cascade-2-30B-A3B activates just 3B parameters per token, runs on a single RTX 4090, and outscores NVIDIA's own 120B model on coding and math benchmarks.
Mistral's new open-source Lean 4 agent scores higher than Claude Sonnet on formal proofs at one-fifteenth the cost, raising the bar for trustworthy AI code generation.
WordPress.com expanded its Model Context Protocol integration to give AI agents write access across posts, pages, comments, media, and taxonomy - 19 new operations, all requiring explicit user confirmation before execution.
A plain-English guide to how ChatGPT, Claude, and Gemini remember you - what gets stored, how to manage it, and what to keep private.
Every way to stay up to date with Awesome Agents - website, podcast on Spotify and Apple, social media on X, Bluesky, LinkedIn, YouTube, and RSS feeds.
A practical, step-by-step guide to using ChatGPT, Claude, and other AI tools as a personal tutor to learn any skill faster - no coding required.
Microsoft's Phi-4 reasoning family delivers near-70B-class math performance in a 14B open-weight package, but the overthinking problem is real and the use case is narrower than the benchmarks suggest.
LTX-2.3 is a 22-billion-parameter open-source video and audio generation model from Lightricks that rivals closed commercial tools - at zero cloud cost.
Mistral Small 4 packs reasoning, vision, and agentic coding into a 119B MoE under Apache 2.0 - a serious small-model contender at a price that's hard to ignore.
Rankings of the best AI models and agent frameworks on computer use benchmarks - OSWorld, OSWorld-Verified, and ScreenSpot-Pro - updated March 2026.
Rankings of AI models by safety metrics including refusal rates, jailbreak resistance, bias scores, and truthfulness across major benchmarks.
Rankings of the best text-to-speech and speech-to-text AI models by naturalness, accuracy, latency, and pricing.
Anthropic's mid-tier model matches Opus 4.6 on computer use, leads all models on office productivity tasks, and costs five times less than the flagship at $3/$15 per million tokens.
Cohere Command A Vision is a 112B multimodal model that leads on document and OCR benchmarks, beating GPT-4.1 across seven visual understanding tasks.
Mistral AI's unified MoE model - 119B total parameters, 6B active per token, 128 experts, 256K context, configurable reasoning, Apache 2.0 license.
OpenAI's CoT-Control benchmark shows frontier reasoning models score 0.1-15.4% at steering their own chain of thought - a result the company frames as good news for AI oversight.
Rankings of the fastest AI models and inference providers by tokens per second, time to first token, and end-to-end latency.
A practical guide to AI agents for business leaders covering ROI frameworks, vendor options, implementation costs, and real-world case studies.
Compare the best AI note-taking apps of 2026 including Notion AI, Google NotebookLM, Obsidian, and Mem with pricing, features, and recommendations.
A beginner-friendly explanation of AI embeddings - the technique that turns text into numbers so machines can understand meaning, power search, and enable RAG.
Compare the best AI data analysis tools of 2026 including Julius AI, ChatGPT Code Interpreter, and Claude analysis with pricing and features.
A step-by-step guide to building AI-powered automations using no-code platforms like Make, Zapier, n8n, and Dify - no programming required.
Rankings of the best small language models under 10 billion parameters, comparing Phi-4, Gemma 3, Qwen 3.5, and more across key benchmarks.
Rankings of the best embedding models by MTEB scores, comparing retrieval quality, dimensions, speed, and pricing for RAG and search.
Compare the best AI meeting assistants of 2026 including Otter, Fireflies, Granola, and tl;dv with pricing, features, and recommendations.
Rankings of the best AI models for multilingual tasks, covering 16 languages across the Artificial Analysis Multilingual Index and MGSM benchmarks.
New research shows reasoning models can't suppress their chain-of-thought, that they commit to answers internally long before their CoT reveals it, and that static benchmarks are inadequate for measuring real-world agent adaptability.
