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Anthropic Adjusts Fable 5 Biology Safeguards the Same Day Stanford Work Shows AI Can Design Viral Genomes

What changed

Anthropic updated its Fable 5 biology safeguards on August 7, the same day researchers from Stanford and the Arc Institute published a paper in Science demonstrating that their Evo 1 and Evo 2 models can design fully functional viral genomes. The timing is not coincidental. The question Anthropic is answering is not whether AI can do biology — Stanford just proved it can — but who gets to control the terms of access. The update reduces biology-related fallbacks on benign queries by roughly 85 percent. Anthropic rewrote and retrained its safety classifier’s constitution to better distinguish everyday health and educational questions — interpreting lab results, understanding symptoms, learning about biology — from dual-use research that remains blocked. Queries touching virology, toxicology, molecular design, and drug design still get routed to Opus 5, a less capable model. Fable 5 is not yet usable for professional biology research or drug development. But the company is building the infrastructure to change that. Anthropic says it is developing trusted access pathways for frontier biology capabilities — a vetted, gated model for researchers who need the full power of Fable 5 without open-ended exposure. The company’s own capability assessments acknowledge that Fable 5 could provide significant uplift to a malicious actor — capabilities they could not find anywhere else. The contrast with Stanford’s work is the structural frame. Evo 2 is an open-weight model, available for public download. As The Guardian and CNN reported, the ability to compose viral genomes with generative AI now exists while governance does not. A companion commentary in Science from Johns Hopkins researchers warned that the study raises urgent biosafety and biosecurity questions. The US Intelligence Community 2026 Annual Threat Assessment explicitly notes that advances in biotechnology could lead to novel biological threats from state actors maintaining offensive weapons programs. Anthropic’s response — restrict the dangerous queries, open the benign ones, build a gated pathway for everything in between — maps directly onto the regulatory asymmetry the company needs. The White House AI Framework, finalized August 4, excludes open-weight models from federal security review entirely. Closed-source labs face 30-day voluntary early access review delays; open-weight developers ship with zero…

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外部发现 · Anthropic · Original source ↗ · Site entry ·

OpenAI Announced Its Next Frontier Model 'Astra'

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How OpenAI Announced Its Next Frontier Model 'Astra' The US AI firm OpenAI, led by CEO Sam Altman, has announced its latest model, Astra. In a shocking introduction to the AI model, the company shared a selection of 10 results, each of which resolves or makes substantial progress on a long-standing open problem. The problems span high-dimensional geometry, coding theory, arithmetic circuit complexity, group theory, operator algebras, quantum complexity, lattice cryptography and extremal combinatorics. OpenAI’s next major model The US AI giant says the results were achieved by “an internal version of Astra”. Sam Altman, OpenAI’s CEO, is believed to have shown US politicians a demo of the Astra system while visiting Washington last week, according to reporting from The Telegraph. Noam Brown, a Research Scientist at OpenAI, wrote in a post on LinkedIn about the development: “An internal version of Astra, OpenAI’s next major model family, solved 10 major open problems in mathematics, quantum complexity and theoretical computer science. “We’re excited to see what scientists and researchers are able to create with our upcoming Astra models!” The research problems solved The model covered advancements in high-dimensional sphere packing, binary and spherical codes, non-sofic groups, Connes’s rigidity conjecture, arithmetic circuit complexity, quantum parallel repetition, closest vector problem, Ehrhart’s volume conjecture, multicolor Ramsey numbers and extremal number conjectures. On Conne's rigidity structure, the model offered a disproof of a longstanding conjecture that certain groups are uniquely determined by their von Neumann algebras. Meanwhile, the high-dimensional sphere-packing set New upper bounds on sphere-packing density down to the Cohn–Elkies threshold. “I'm in awe, and excited to see what other things we will learn from the AIs. There are a number of problems I've spent a long time thinking about, and maybe I will learn how to answer them soon,” Henry Yuen, Associate Professor at Columbia University, wrote on X. Henry said: “And then - the kicker - something that I personally spent a couple years on in grad school, leading to some of my proudest work: quantum parallel repetition theorems. I spent many hours, days, nights, weekends in cafes, in my office, at home, trying to understand Ran Raz's classical parallel repetition theorem and whether I coul…

Sources and evidence

外部发现 · OpenAI · Original source ↗ · Site entry ·