Web News: Anthropic Released An AI It Doesn't Fully Trust

The hosts discuss the June 9th release of Anthropic's Claude Fable 5 and Claude Mythos 5 models, with one host having had several days of hands-on experience. He characterizes the new model as a meaningful step up from predecessors — particularly in code review and troubleshooting — but not a foundational leap comparable to earlier generational jumps like GPT-3 to GPT-4.

A central focus is the unprecedented safety approach Anthropic has taken. CEO Dario Amodei reportedly expressed hesitation about releasing the model due to its ability to find security exploits that had eluded both other AI models and professional security researchers for decades. Anthropic first released it under a program called 'Project Glasswing' to large companies including Google and Microsoft, as well as the U.S. government, giving them a month or two of exclusive access under NDA before public release.

The hosts examine the novel guardrail mechanism where certain sensitive queries — specifically around frontier cybersecurity and research biology — are automatically downgraded to the older Opus 4.8 model rather than being handled by Mythos 5. The hosts argue this creates a 'technical debt' problem: as newer and more capable models are released every few months, the staggering of models for safety routing will become increasingly complex and unmanageable, unlike earlier model-switching which was purely a UX or capability decision.

The conversation shifts to a new 30-day mandatory data retention policy, even for enterprise customers who previously could opt out. The hosts speculate this serves multiple purposes: monitoring for misuse and distillation attempts by competitors, gathering behavioral data to refine the model's safety mechanisms, and potentially informing product development. They note a tension since Anthropic is also releasing competing products (like a Figma-like design tool) built on the same models, making data retention concerning for businesses building on their API.

The distillation controversy receives significant discussion — the practice of using API calls to extract a model's capabilities into training data for new open-source models. The hosts acknowledge the irony of Anthropic objecting to this while having themselves scraped internet content (blogs, guides, videos) without explicit permission to train their models. They note Anthropic frames anti-distillation policies around national security and adversarial nations, which the hosts view as a way to sidestep the underlying contradiction.

The episode closes with broader concerns about the pace of AI development outstripping oversight capacity, drawing a parallel to the smartphone era's rapid evolution that eventually stabilized into annual incremental updates. The hosts predict AI model releases will similarly consolidate into annual cycles with simpler naming conventions, but express concern that the current pace — driven by software's lack of physical manufacturing constraints — is producing potentially dangerous progress without adequate governance structures.