The world's first science intelligence engine capable of monitoring scientific progress in real time
sigargv/Laguna-M.1-GGUF · Hugging Face
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
Mixture of Experts Explained
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
Anatomy of a Frontier Lab Agent Intrusion: A Technical Timeline of the July 2026 Incident
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
The Scientific Contribution Graph: Automated Literature-based Technological Roadmapping at Scale
Sir Isaac Newton famously wrote, “If I have seen further, it is by standing on the shoulders of giants”. Scientific contributions are rarely developed in isolation, but build upon prior contributions, such as problem framings, experimental methods, and empirical findings. Understanding these prerequisite relationships is important for studying scientific progress, and for automated scientific discovery systems that must reason about which existing capabilities can be used to develop new ones (e.g. Lu et al., 2024; Jansen et al., 2025b; Baek et al., 2025).
World Monitor - Real-Time Global Intelligence Dashboard
Real-time global intelligence dashboard with live news, markets, military tracking, infrastructure monitoring, and geopolitical data. OSINT in one view.
Artificial Intelligence Glossary | Stanford HAI
Artificial Intelligence (AI) is rapidly growing, with new terms and concepts being introduced at a breakneck speed. You may have seen terms such as AGI, machine learning, or foundation models in media headlines, emerging legislation, or in your everyday life.
AI Index | Stanford HAI
The mission of the AI Index is to provide unbiased, rigorously vetted, and globally sourced data for policymakers, researchers, journalists, executives, and the general public to develop a deeper understanding of the complex field of AI. To achieve this, we track, collate, distill, and visualize dat
The Bazaar of Scientific Knowledge | shishyko!
What if we didn't collapse all the knowledge from the scientific process into one paper?
On-device intelligence for every product
We're building a frontier lab for on-device AI. Small, specialized models for audio, vision, and text, faster than the cloud and free.
DeepMind Institute
Bold, well-evidenced thinking on AGI from the lab that pioneered the field. Read the latest essays from the DeepMind Institute.
More Than a Tool
What We Learned from a Year of Conversations About AI
TERMINAL-BENCH-SCIENCE
A benchmark for evaluating AI agents on research workflows across scientific domains
Harness Engineering for Self-Improvement
The concept of recursive self-improvement (RSI) dates back to I. J. Good (1965), where he defined an “ultraintelligent machine” as a system that can surpass humans in all intellectual activities and design better machines to improve itself. Yudkowsky (2008) used the phrase “recursive self-improvement” for a specific feedback loop: an AI uses its current intelligence to improve the cognitive machinery that produces its intelligence. This feedback loop in modern AI may indicate the model rewriting its own weights directly, or more broadly the model improves the training pipeline and the deployment system, which in turn enables a better successor model with improved performance across economically valuable tasks. The speed of research development in AI has been shown to drastically accelerated in frontier labs (Anthropic; OpenAI).
How to burst the AI bubble: Strike at its roots
Sci-fi author/tech journalist Cory Doctorow on his new book, The Reverse Centaur's Guide to Life After AI.
Ecology is not yet ready for AI—and why that matters | PNAS
Ecology is not yet ready for AI—and why that matters
AI and the Republic of Science
AI promises to end scientific stagnation. But will it solve the right problem?
