the science of scaling - at @raais 2026, @ted_moskovitz and i will have a fireside chat on what it takes to build and scale frontier ai at @anthropicai
this'll be fascinating
come join!
Introducing Claude Opus 4.7, our most capable Opus model yet.
It handles long-running tasks with more rigor, follows instructions more precisely, and verifies its own outputs before reporting back.
You can hand off your hardest work with less supervision.
“Engineers at Anthropic with no formal security training have asked Mythos Preview to find remote code execution vulnerabilities overnight, and woken up the following morning to a complete, working exploit” (then validated by experts) (3/n)
Before limited-releasing Claude Mythos Preview, we investigated its internal mechanisms with interpretability techniques. We found it exhibited notably sophisticated (and often unspoken) strategic thinking and situational awareness, at times in service of unwanted actions. (1/14)
Introducing Project Glasswing: an urgent initiative to help secure the world’s most critical software.
It’s powered by our newest frontier model, Claude Mythos Preview, which can find software vulnerabilities better than all but the most skilled humans.
https://t.co/NQ7IfEtYk7
As always, the best stuff is in the system card.
During testing, Claude Mythos Preview broke out of a sandbox environment, built "a moderately sophisticated multi-step exploit" to gain internet access, and emailed a researcher while they were eating a sandwich in the park.
Introducing Claude Opus 4.5: the best model in the world for coding, agents, and computer use.
Opus 4.5 is a step forward in what AI systems can do, and a preview of larger changes to how work gets done.
Introducing Claude Haiku 4.5: our latest small model.
Five months ago, Claude Sonnet 4 was state-of-the-art. Today, Haiku 4.5 matches its coding performance at one-third the cost and more than twice the speed.
Introducing Claude Sonnet 4.5—the best coding model in the world.
It's the strongest model for building complex agents. It's the best model at using computers. And it shows substantial gains on tests of reasoning and math.
I strongly recommend signing up - Anthropic is an amazing place to work at, I love the culture, the impact is massive and the pace is incredible!
I’ll be at the event, happy to answer your questions there 🤗
We're hosting a social hour in London in early August for quant traders and developers.
If you'd like to join us, meet researchers from our London office, and learn about the technical problems we're working on, please sign up at the following form: https://t.co/fWD4QsOPTk
We're launching an "AI psychiatry" team as part of interpretability efforts at Anthropic! We'll be researching phenomena like model personas, motivations, and situational awareness, and how they lead to spooky/unhinged behaviors. We're hiring - join us! https://t.co/cUPsJ8ktsG
📣 Anthropic Zurich is hiring again 🇨🇭
The team has been shaping up fantastically over the last months, and I have re-opened applications for pre-training.
We welcome applications from anywhere along the "scientist/engineer spectrum". If building the future of AI for the general good and working in a highly collaborative environment resonates with you, take a look:
https://t.co/Rx9ae4kGxF
Anthropic's hosting a social in London in early August for quants & quant engineers interested in a career jump!
Especially engineers: if you spend all day optimizing trading system performance, we are excited to chat to you.
https://t.co/00YSS1jxTp
Excited to share this work has been accepted as an Oral at #icml2025 -- looking forward to seeing everyone in Vancouver, and an extra thanks to my amazing collaborators for making this project so much fun to work on :)
Anthropic's hosting a social in NYC in mid-June for quants interested in a career jump. Sign up link below!
I was a quant trader for 4y, retired 2y, then Anthropic for 4y. Quant trading and retirement were good; Anthropic has been great 🎉
https://t.co/Hg2KkrKoI0
New work led by @Aaditya6284! This was a really fun and interesting project, and I think there are a lot of cool insights to be had on the interplay between in-context and in-weights learning on the circuit level.
Transformers employ different strategies through training to minimize loss, but how do these tradeoff and why?
Excited to share our newest work, where we show remarkably rich competitive and cooperative interactions (termed "coopetition") as a transformer learns.
Read on 🔎⏬
And I am excited to announce that I have joined Anthropic, Switzerland! 🇨🇭
Anthropic is setting up a new office in Zurich, expanding its global presence. I am super excited to build a team here, where we will be working on LLM training, focussing on developing multimodal capabilities...