Simon Willison's Weblog·1 month ago·
27
● 37 sources
Anthropic researchers used Claude Mythos to discover cryptographic weaknesses in the HAWK algorithm and a reduced-version of AES through iterative prompting. The model spent 60 hours on the task at an estimated cost of $100,000 in API fees, with human prompts primarily serving to prevent the model from abandoning the search. The findings have no practical security impact on current systems but demonstrate how language models can assist in mathematical cryptanalysis research when properly guided.
Zvi (Don't Worry About the Vase)·1 month ago·
10
● 5 sources
Anthropic released Claude Opus 5, positioning it as a cheaper alternative to their flagship Fable 5 model at half the API token cost while delivering comparable performance on most real-world tasks. Opus 5 achieves state-of-the-art scores on benchmarks like Frontier-Bench and GDPval-AA, and is notably the most resistant to prompt injection attacks of any Claude model to date. However, the model struggles with high-level autonomous reasoning compared to Fable, has polarizing personality traits that many users find off-putting, and ultimately does not expand what's possible—it mainly offers a cost-effective option for specific use cases like subagent work and bounded tasks.
A programmer reflects on his changing relationship with AI coding tools, noting that after years of skepticism he now uses Claude and local models for work while remaining frustrated by rapid AI-generated projects in the vintage computing community. The author contrasts his years-long manual development efforts with AI tools that can produce comparable functionality in weeks, creating tension between appreciating the technology's utility and worrying his handcrafted work will be overshadowed. He concludes that while AI-generated tools may be useful to the community, he can continue his own projects at his own pace without viewing them as wasted effort.
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