Dominik Lukes
15.8K posts
@techczech
Exploring schemas and propositions about language models of all kinds on https://t.co/GU07uzb7Ud and on https://t.co/UfdxBd7jvK.
hallucinated references will land you a 1-year ban from arxiv now. wow
The latest 𝕏 algorithm has been published to GitHub github.com/xai-org/x-algo…
Codex is very good, but it is still a very "developer coded" interface for an everything app. And it continues the somewhat annoying AI perspective that non-coders are just not as competent and need stuff hidden from them, as opposed to requiring a different form of complexity.
Codex in the ChatGPT mobile app!
What happens when you post a real Monet and say it’s AI? The coolest art social experiment I’ve seen in a while. Thank you @SHL0MS
A lot of people have been wondering about Mythos, Glasswing, and the vulns we / our partners are fixing. Today, I’m excited for us to start sharing more. (For context, I lead Glasswing @AnthropicAI.) Two independent evaluations this week—from XBOW and the UK AISI—confirm what we've been seeing internally: Claude Mythos Preview is a step change in autonomous cybersecurity capabilities. We need to start preparing fast for a world of models with this level of capabilities. The UK AI Security Institute tested the model we shipped at the launch of Project Glasswing and found Mythos Preview is the first model to solve both of their end-to-end cyber ranges, including one (Cooling Tower) which no model had ever cleared. But attackers (and defenders) have sophistication & cost constraints – Mythos is also the only model that clears every one of their tasks estimated over 8 hours under their deliberately low 2.5M-token cap. XBOW tested it on their offensive security benchmarks, finding "token-for-token, unprecedented precision." It's the only model to succeed at subtle V8 sandbox work. Other Glasswing partners shared similar stories. In a few weeks of testing, Mythos Preview has helped them find many thousands of (estimated) high + critical severity vulnerabilities, sometimes double what they'd normally find in a year. I don't share this to boost Mythos. In fact, this is not about Mythos. It’s about preparing for the coming world of models being better, faster, cheaper, and more creative than some of the best human experts at dual use capabilities. Clearly, we need them supporting defenders as widely as can be done safely – and especially the least resourced ones. Within a year, Mythos will probably look quite dumb (relative to other new models). And others may release openly available or unguardrailed models of Mythos-level capabilities. We started Project Glasswing because capabilities like Mythos Preview's won't stay rare, or stay in careful hands. We are bringing it to defenders as fast as we responsibly can, while working to figure out, for example, the right safeguards and patching & disclosure processes. Also, to be clear, compute has never been a limiter in our rollout. Expect a fuller update on our Glasswing work in the coming days. XBOW report: xbow.com/blog/mythos-of… UK AISI report: aisi.gov.uk/blog/how-fast-…
The quantity of code that devs ship has roughly 10xed. But net developer productivity (value created by unit of time) is only up by a bit, if at all. Part of it is that the additional code is solving more incremental problems. A bigger part is that the new code is creating problems of its own.
The silent removal of Study Mode from ChatGPT is a big mistake (both Claude and Gemini still have theirs) We have enough evidence that using AI in assistant mode to study can hurt learning because it just gives you answers, making students think they learned when they have not. You can prompt the model to be a very good tutor, but most people don't know to do that. Study mode was an easy option that parents and teachers could suggest to mitigate negative effects, even if it wasn't perfect. OpenAI still has a page about it, and the link activates study mode but otherwise there seems to be no way to select it from a menu for most accounts. openai.com/index/chatgpt-… (Deleted this by accident, sorry, so reposted!)
