Anthropic: Fermat’s Last Theorem formalized in Lean
The proof comprises 13 million lines of Lean code and around 29,500 intermediate theorems.
Models, agents, applications: artificial intelligence put to work on real problems.
Here, artificial intelligence is judged on the evidence: what it does, for whom, at what cost. The section follows models and their measurable progress, agents doing real work, and above all deployments — a hospital screening more patients, a power grid better balanced, a public service answering faster. AI-as-spectacle, productless funding rounds and prophecy get no space.
We favour documented use cases with the numbers attached: how many examinations, what error rate, what savings. Non-Western players — Chinese, Indian, Emirati labs — are covered on the same footing as American ones, because much of the real deployment happens there. Every article cites its sources and separates the prototype from the service in production.
The proof comprises 13 million lines of Lean code and around 29,500 intermediate theorems.
Detection results will be sent directly to customers’ security teams, eliminating the need for manual review by Anthropic.
Fable 5.1 is available today through cloud platforms and Anthropic’s API.
Janelia neuroscientist Arco Bast built the Model Hardware Standard with Anthropic and Claude Code.
Anthropic’s update lets Claude carry project details from conversations into Cowork without a fresh briefing.
The US-only API offers models from OpenAI, Anthropic, DeepSeek and other providers.