Artificial intelligence
Models, labs, research and products shaping how AI is built, deployed and governed.
AI control
AlphaFold
AMD
Anthropic
ARC-AGI
CAISI / CAISSI: the US government's AI testing centre at NIST
Claude Mythos
Constitutional AI
DeepSeek-R1
ECMWF AIFS (Artificial Intelligence Forecasting System)
Figure AI
Frontier safety frameworks (responsible scaling policies)
Gemini Robotics
Genesis Mission (US AI-for-science initiative)
GNoME (Graph Networks for Materials Exploration)
Google DeepMind
Intel
NVIDIA Isaac GR00T
Isomorphic Labs
METR
Model Context Protocol (MCP)
NVIDIA
Open X-Embodiment
OpenAI
OpenAI o1
Physical Intelligence
RFdiffusion
Reinforcement learning from human feedback (RLHF)
Samsung Electronics
Scalable oversight
Self-driving labs (autonomous laboratories)
Sparse autoencoders (interpretability)
SWE-bench
Tesla Optimus
Test-time compute
TSMC (Taiwan Semiconductor Manufacturing Company)
UK AI Security Institute (AISI)
Unitree Robotics
Waymo
WeatherNext (GraphCast, GenCast)
AI for science tracker: milestones and what to watch
AI safety tracker: alignment, interpretability and evals in 2026
Frontier AI tracker: reasoning models and agents
Robotics and embodied AI tracker: milestones to watch
US export controls on advanced AI chips
How fast are AI agents really improving?
Why AI chip supply is so concentrated
Do AI-designed drugs work? What the clinical evidence shows
Has AI discovered new materials? The debate over GNoME and A-Lab
Can AI safety keep pace with AI capabilities?
Should games use AI-generated voices? The AI voice NPC debate
Are humanoid robots ready for real work? The 2026 debate
Do reasoning models really reason? The debate over their limits
AI for science in 2026: a crash course
AI safety and alignment in 2026: a crash course
Frontier AI in 2026: a crash course
How AI agents work
How frontier AI capabilities are measured
How AI designs new proteins, drugs and materials
How AI predicts protein structures
How AI safety testing works: evals, red teams and thresholds
How AI weather models work
How large language models work
How mechanistic interpretability works: looking inside AI
How reasoning models work
How robots learn: demonstrations, trial and error, and data
Robotics and embodied AI in 2026: a crash course
Sim-to-real: training robots in simulation for the real world
Vision-language-action models: how robot foundation models work
Voice gaming explained: voice control, voice chat and AI voices
What is AI alignment? Making AI do what we intend