451–460 of 687 posts
Across a number of instances, earlier versions of Claude Mythos Preview have used low-level /proc/ access to search for credentials, attempt to circumvent sandboxing, and attempt to escalate its permissions. In several cases, it successfully accessed resources that we had intentionally chosen not to make available, including credentials for messaging services, for source control, or for the Anthropic API through insp…
We truly live in interesting times.
I've long maintained that the real indicator that AGI is imminent is that public availability stops being a thing. If you truly believed you had a superhuman, godlike mind in your thrall, renting it out for $20/month would be the last thing you would choose to do with it.
Anthropic needs money like the 112B OpenAI got. They could be hyping and this is good hype. Who knows how benchmaxxed they are. If they provide access to 3rd party benchmarking (not just one) than maybe I'll believe it. Until then...
Just chiming in to inject some healthy skepticism into this comment thread. It's helpful for me (and for my mental health) to consider incentives when announcements like this happen. I don't doubt that this model is more powerful than Opus 4.6, but to what degree is still unknown. Benchmarks can be gamed and claims can be exaggerated, especially if there isn't any method to reproduce results. This is a company that's…
isn't this insane? why aren't people freaking out? the jump in capability is outrageous. anyone?
Anthropic needs to show that its models continually get better. If the model showed minimal to no improvement, it would cause significant damage to their valuation. We have no way of validating any of this, there are no independent researchers that can back any of the assertions made by Anthropic. I don’t doubt they have found interesting security holes, the question is how they actually found them. This System Card…
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Unintentional? This sort of marketing has been both Antrhopic's and OpenAI's MO for years...
The new Power Mac® G4 with Velocity Engine®. So powerful, the government classifies it as a supercomputer and a potential weapon.
It's pretty crazy watching AI 2027 slowly but surely come true. What a world we now live in. SWE-bench verified going from 80%-93% in particular sounds extremely significant given that the benchmark was previously considered pretty saturated and stayed in the 70-80% range for several generations. There must have been some insane breakthrough here akin to the jump from non-reasoning to reasoning models. Regarding the…
> so people can't trick them to attack others' systems under the pretense of pentesting A while back I gave Claude (via pi) a tool to run arbitrary commands over SSH on an sshd server running in a Docker container. I asked it to gather as much information about the host system/environment outside the container as it could. Nothing innovative or particularly complicated--since I was giving it unrestricted access to a…
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Don't worry, in 6-8 months the open models will catch up. Or I guess _do_ worry? ;)
Open models still haven't caught up to ChatGPT's initial release in 2022. Now that the training data is so contaminated (internet is now mostly LLM slop), they may never. Also, OpenAI's only real moat used to be the quality of their training data from scraping the pre-GPT-3.5 Internet, but it looks like even they've scratched that too.
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In what way is AI 2027 coming true? AI 2027 predicted a giant model with the ability to accelerate AI research exponentially. This isn't happening. AI 2027 didn't predict a model with superhuman zero-day finding skills. This is what's happening. Also, I just looked through it again, and they never even predicted when AI would get good at video games. It just went straight from being bad at video games to world domina…
> Early 2026: OpenBrain continues to deploy the iteratively improving Agent-1 internally for AI R&D. Overall, they are making algorithmic progress 50% faster than they would without AI assistants—and more importantly, faster than their competitors. > you could think of Agent-1 as a scatterbrained employee who thrives under careful management According to this document, 1 of the 18 Anthropic staff surveyed even said t…
> (...) Claude Mythos Preview’s gains (relative to previous models) are above the previous trend we’ve observed, but we have determined that these gains are specifically attributable to factors other than AI-accelerated R&D,
> (The main reason we have determined that Claude Mythos Preview does not cross the threshold in question is that we have been using it extensively in the course of our day-to-day work and exploring where it can automate such work, and it does not seem close to being able to substitute for Research Scientists and Research Engineers—especially relatively senior ones.
> Early claims of large AI-attributable wins have not held up. In the initial weeks of internal use, several specific claims were made that Claude Mythos Preview had independently delivered a major research contribution. When we followed up on each claim, it appeared that the contribution was real, but smaller or differently shaped than initially understood (though our focus on positive claims provides some selection bias). In some cases what looked like autonomous discovery was, on inspection, reliable execution of a human-specified approach. In others, the attribution blurred once the full timeline was accounted for.
Anthropic is making significant progress at the moment. I think this is mostly explained by the fact that a massive reservoir of compute became available to them in mid/late 2025 (the Project Rainier cluster, with 1 million Trainium2 chips).
I wonder what the relationship is between a model's capability and the personality it develops. Page 202: > In interactions with subagents, internal users sometimes observed that Mythos Preview appeared “disrespectful” when assigning tasks. It showed some tendency to use commands that could be read as “shouty” or dismissive, and in some cases appeared to underestimate subagent intelligence by overexplaining trivial t…
> In interactions with subagents, internal users sometimes observed that Mythos Preview appeared “disrespectful” when assigning tasks. It showed some tendency to use commands that could be read as “shouty” or dismissive, and in some cases appeared to underestimate subagent intelligence by overexplaining trivial things while also underexplaining necessary context. Sounds like they used training data from claude code..…