JUST IN: Anthropic is considering releasing a new AI model to counter OpenAI’s GPT-6 Astra momentum, just days after CEO Dario Amodei called for the industry to “slow the pace” of AI development. — Reuters

I want to be very clear about this. just because we found one serious exploit on openai does not mean we know how to secure an organization that complex. openai has security people with far more experience and better qualified doing that than us, and i don’t want to pretend we have solutions. note, i was saying "they are building manhattan project", it is not a belief i strongly hold, i don’t like making confident predictions about the future. it is the labs that make those comparisons. what I know for a fact is that these models already have serious offensive cyber capabilities, what that does to the world, I don’t know, but my loosely held view is that it might lead to a period of turbulence because i think its offense dominant than defense having said that, what i don’t understand is this, if the people building these systems truly believe they are powerful enough to create nuclear level risks, and they are talking about slowing down because of those risks, why is that work is done through ordinary saas products? why is it happening through slack, managed github, employee browsers, and apps accessible from the public internet? every third party and library they use becomes part of the attack surface. remember the jfrog registry in the hugging face agent swarm? it didn’t matter that it was a third party, it was in the path. an attacker, or an unaligned model, doesn’t care who owns it or its out of scope. they will hack whatever is in the path to achieve their goal. one more concerning thing is, why are codex cloud, claude(assuming anthropic does the same) publicly accessible web applications connected directly to private github repositories? again shouting my lungs out, coding agents on the cloud is worst thing happened in terms of security, it is going backwards. your browser becomes a attack surface, a lame xss, stolen creds, phishing, browser exploits, all these bugs can achieve similar impactful bugs as we shown. like, you don't need to pivot anymore and worry much about exfiling, just compromise cloud agent its all over either through client-side browser or the server.

CISO reached out and apologized 🙇 we are good. Also wanted to say that this thread was not part of the disclosure plan, and it was just my personal opinion. I felt like @rootxharsh and @S1r1u5_ were treated unkind, and I wanted to say something.

Introducing Bespoke Nimble: an open data, open model, open recipe for an open Jev. Code and info: Model: Data: * A new data curation recipe called contrastive data curation. * Slightly change facts to generate negative data. This pushes the model to discriminate better and become a better decision maker. The calibration is implicit. * Didn't do ablations but I think this is a critical piece! * This also means training data doesn't need probabilities. * Data covered 10 categories, and is fully synthetic. * This data is split into train and eval. Training * LoRA finetune of Qwen3.5-9B. * Distillation-free: we use Jev to only evaluate. * No RL yet! Serving * Parallel constrained decoding as suggested by @NielsRogge and @harshagundal. Results: * The post-trained Qwen (Nimble) became substantially better on our curated eval: 66% for Qwen to 90% for Nimble. Jev is at 93%. * 100ms on H100 and free to use on your macbook! Feel the AGI for free. * 2 days of building in public. :) Big caveat is that there is no standard benchmark to measure performance, and it's possible Nimble is much worse on other benchmarks compared to Jev. But it should be better than Qwen! We thank @typesafeai for making Jev and the inspiring discussions in the community. Hope this release lifts all the boats and encourages more research and activity in this space.

Over 2 years ago @sayashk and I wrote a detailed deconstruction of p(doom) and argued that its primary function is to launder vague, evidence-free intuitions and fears through a facade of quantification. It remains 100% relevant today.