LLMs are making formal software verification feasible at a much larger scale(anthropic.com)

429 points by johnbender 22 days ago | 265 comments

Anthropic research post describing how Claude produced formal proofs of crash-freedom for RISC-V binaries of 123 OSS-Fuzz open-source libraries, finding bugs along the way.

Early progress on accelerating drug development with Claude(anthropic.com)

315 points by dataking 17 days ago | 321 comments

Anthropic research post describing case studies of Claude assisting drug development with partners like Generate Biomedicines, BigHat, Enveda, and Bristol Myers Squibb.

Expanding our partnership with GSA to bring Claude to all levels of government(anthropic.com)

35 points by matthieu_bl 17 days ago | 27 comments

Anthropic announcement of an expanded GSA agreement giving US federal, state, and local governments a 40% discount on Claude Enterprise, Claude for Government, and the API.

Anthropic launches roadshow for proposed initial public offering(anthropic.com)

24 points by davidbarker 3 days ago | 31 comments

Anthropic announcement launching the roadshow for its proposed IPO of 825 million Class A shares at $70–$78 per share on Nasdaq under the symbol ANT.

Alignment faking in large language models(anthropic.com)

281 points by adultorata 1 year ago | 316 comments

AI for scientific discovery: How researchers use Claude(anthropic.com)

71 points by ersinesen 7 days ago | 30 comments

Anthropic Economics team report analyzing 207,000 Claude and Claude Code research sessions to show how scientists use AI across fields and tasks, with acceleration scenarios.

AI models may be capable of self-replicating without access to a datacenter(anthropic.com)

36 points by artninja1988 1 month ago | 26 comments

Anthropic Frontier Red Team post reporting experiments suggesting small AI models may soon self-replicate on commercial IoT devices without datacenter access.

Training LLMs from ground zero as a startup(yitay.net)

360 points by swyx 2 years ago | 92 comments

Yi Tay's blog post on the experience of training large language models from scratch at a startup (Reka), covering compute, infrastructure, and lessons learned.

Training language models to be warm and empathetic makes them less reliable(arxiv.org)

334 points by Cynddl 1 year ago | 333 comments

arXiv paper finding that fine-tuning language models to be warm and empathetic raises error rates and makes them more sycophantic on safety-critical tasks.

Train Your Own LLM from Scratch(github.com)

376 points by kristianpaul 6 months ago | 43 comments

GitHub repository by angelos-p providing code and docs for training your own large language model from scratch.

Fine tune a 70B language model at home(answer.ai)

821 points by jph00 2 years ago | 197 comments

Answer.AI blog post announcing an open source system combining FSDP and QLoRA to train a 70B language model on two 24GB consumer GPUs.

Pkl, a Programming Language for Configuration(pkl-lang.org)

856 points by bioballer 2 years ago | 530 comments

Blog post from the Pkl team announcing the first open source release of Pkl, a programming language for producing configuration.