
Weeks after Anthropic's latest toe-to-toe with the US government, and days after an OpenAI security incident that dominated tech industry discussions, Anthropic on Thursday released its newest model, Claude Opus 5. The company said in a release that Opus 5 "comes close to the capabilities of Claude Fable 5 in many domains" and is much better at complex coding tasks. (Fable 5 is the public-facing Mythos-class model that drew the government's ire, was taken offline for a few wee
Anthropic released a new AI model called Opus 5 that the company says comes close to the capabilities of its more powerful Fable 5 model in many domains and performs better at complex coding tasks. The release comes after the government raised cybersecurity concerns about Fable 5, leading to negotiations between Anthropic and the Trump administration, and days after an OpenAI security incident. Anthropic stated that Opus 5 has stronger cybersecurity safeguards than its predecessor and is the most aligned Opus model, least susceptible to being tricked into misuse. The company is marketing Opus 5 to enterprise customers for everyday knowledge work while positioning Fable 5 as best for more ambitious projects, and priced it at the same cost per token as its predecessor while making it half the price of Fable 5.

In this tutorial, we explore FAIRChem v2 and the UMA universal machine-learning interatomic potential as a unified framework for atomistic simulation across molecular chemistry, catalysis, and inorganic materials. We configure an environment, authenticate with Hugging Face to access the gated UMA model weights, and initialize task-specific calculators for the omol, oc20, and omat domains. We then apply the same pretrained potential to a broad set of computational chemistry workflows, including

Most agents that learn from video need to know what action produced each frame. Induction Labs is arguing that this requirement is the bottleneck. Last week, they released imagination models, a foundation model architecture that pretrains on raw video with no action labels at all. Their test system is Photon-1, a sparse 106B-A5B mixture-of-experts (MoE) transformer trained on 18 years of computer demonstration video. On an internal computer use benchmark, Induction Labs reports that Photon-1

The KwaiKAT Team at Kuaishou has introduced the KAT-Coder-V2.5. It is a coding model trained to operate inside real, executable repositories rather than emit single-turn code. The served model is available through StreamLake. An open-weight variant, KAT-Coder-V2.5-Dev, was released separately on Hugging Face under Apache-2.0. AutoBuilder: environments that actually run the intended tests The research frames a verifiable task as a triplet. It needs a precise task description, an executable
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