A SemiAnalysis podcast said Anthropic placed unusually strict classifiers on Fable, the public version of its flagship Mythos model, as regulatory pressure shaped how the company released the system. According to the discussion, users attempting certain actions are immediately downgraded to the Opus model, and that downgrade cannot be reversed within the conversation. SemiAnalysis founder Dylan Patel said the restrictions were so severe that even internal staff could not use the model for routine work. The podcast also said Mythos had completed training in February but was not released under the Fable name until May. In the same discussion, Jordan said his understanding was that Mythos 2 had also finished training but had not been launched, while internal teams were still iterating. The speakers argued that Anthropic, which had long called for regulation, is now seeing that regulatory framework slow the pace of its own public model releases. They drew a parallel with OpenAI, saying its next-generation public release is also being delayed even as internal training continues, potentially widening the gap between internal and public model capabilities.
ChainCatcher reported, citing a SemiAnalysis podcast, that Anthropic has placed very strict classifiers on Fable, the public version of its flagship Mythos model, under regulatory pressure. In the discussion, users who attempt certain actions are said to be immediately downgraded to the Opus model, and that switch cannot be undone within the same conversation.
SemiAnalysis founder Dylan Patel said on the podcast that the classifier restrictions were "too harsh," adding that even internal employees were unable to complete routine tasks with the model.
Mythos was trained months before its public release
The podcast said Mythos had completed training as early as February, but Anthropic did not release it under the Fable name until May.
Jordan said during the discussion that, to his understanding, Mythos 2 had also finished training but had not been released. He added that the internal research team was still believed to be iterating on the model.
Discussion points to regulation affecting release timing
Analysts in the podcast discussion said Anthropic had spent a long time calling for regulation, but that the arrival of those rules was now constraining the pace of its own public releases.
The speakers drew a similar comparison with OpenAI. They said OpenAI is also delaying the public release of its next-generation model while internal training continues, and the capability gap between internal systems and public-facing models may keep widening.
This article was originally published by Bit.Fan. For more cryptocurrency news and market insights, visit www.bit.fan. Disclaimer:
The market information, project data, and third-party content displayed on this platform are for industry information sharing only and do not constitute any form of investment advice or return commitment.
Cryptocurrency trading carries high risks. Users should fully assess their risk tolerance and make independent decisions. All profits, losses, and legal responsibilities are borne by the users themselves.
