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AI 资讯 Reddit r/artificial

Anthropic just released Claude Fable 5 a Mythos-class model for general use, with safety classifiers that fall back to Opus 4.8 on ~5% of sessions

Anthropic dropped two models today: Claude Fable 5 (general availability) and Claude Mythos 5 (restricted to cyberdefense partners). The short version: Fable 5 is their most capable model ever released publicly, and they’re being unusually transparent about how they’re handling the risks. What’s actually impressive: -Stripe compressed months of engineering into days with it. In a 50-million-line Ruby codebase, Fable 5 did a codebase-wide migration in a day that would have taken a full team 2+ months by hand.  -On vision tasks, it beat Pokémon FireRed using only raw game screenshots with no maps or navigation aids. Previous Claude models needed complex helper harnesses to even play it.  -Mythos 5 autonomously conducted novel genomics research over a week, assembling single-cell data for millions of cells across 138 animal species. Its trained model outperformed a recent paper published in Science despite being 100x smaller.  -On Cognition’s FrontierCode eval (production-quality coding), Fable 5 scores highest among frontier models, even at medium effort.  The safety approach is interesting: Rather than just refusing dangerous requests, Fable 5 uses classifiers that silently fall back to Opus 4.8 on queries related to cybersecurity, biology/chemistry, and distillation. Users are informed when this happens, and it triggers in less than 5% of sessions on average.  They ran a bug bounty that produced zero universal jailbreaks in 1,000+ hours of testing. UK AISI made some progress toward one in a short initial window, but no full break.  Pricing: $10/M input tokens, $50/M output tokens less than half the price of Mythos Preview.  Caveat on Pro/Max/Team plans: Free access lasts through June 22, then requires usage credits. They say they’ll restore it as a standard plan feature when capacity allows.  The biology capabilities are wild Mythos-class models outperforming dedicated protein language models on AAV design tasks without being trained for it is a real signal

/u/Direct-Attention8597 2026-06-10 03:47 9 原文
开发者 HackerNews

Ask HN: Favorite text heavy blogs the are a joy to read

After ten years I’m working on a redesign of my personal tech blog. I want to look at some other blogs with good modern design. Of course searching for ‘well designed blogs’ or ‘webdesign 2026’ brings up endless marketing listicles. Even after wading through the crap, the advice is focused on advertising and product centric sites, not prose heavy sites with good typography. So my question to you is: What are some of your favorite text heavy blogs that are a joy to read? I don’t mean the content

joshmarinacci 2026-06-10 03:35 5 原文
AI 资讯 Reddit r/MachineLearning

AI Epistemic Risks: Emerging Mechanisms & Evidence [R]

How will AI affect our ability to think and judge for ourselves? Our new paper co-authored by 30 experts explores epistemic risks —the threats AI poses to our collective capacity to form beliefs accurately, reason well, and maintain a healthy information environment. We look at how AI can lead to harm through these mechanisms: Persuasion & Manipulation: AI systems are highly persuasive, opening the door for political/economic manipulation, incitement and radicalization, and other misuse, as well as unintentional harms like AI sycophancy and mental health risks. Cognitive Offloading: We may be delegating our thinking to AI at a deeper level than prior technologies, risking long-term degradation of individual and societal cognitive resilience. Feedback Loops: Human-AI and AI-AI interactions are narrowing the epistemic space humans and AIs draw from. This already drives homogenization, and may potentially lead to fragmentation and “lock-in” (a self-referential state that is difficult to reverse). While we believe AI could be an unprecedented lever for improving how humanity processes knowledge, we shouldn’t assume this will happen by default. We outline promising directions to change this trajectory across how AI systems are built, human-AI interaction design, institutional and individual adaptation, and information market incentives. Epistemic risks are self-perpetuating. As they can undermine the individual cognitive and social foundations needed to recognize, prioritize, and govern other threats—including the risks from AI itself—the time to act is now, before our capacity to respond is itself lost. Authors: Mick Yang, Stephen Casper, Jonathan Stray, Jasmine Li, Cameron Jones, Anna Gausen, Natasha Jaques, Brian Christian, Bálint Gyevnár, Hannah Rose Kirk, Zhonghao He, Dan Zhao, Siao Si Looi, Joshua Levy, Kobi Hackenburg, Elizabeth Seger, Matt Kowal, Michelle Malonza, Luke Hewitt, Hause Lin, Maarten Sap, Dylan Hadfield-Menell, Thomas H. Costello, Reihaneh Rabbany, Je

/u/KellinPelrine 2026-06-10 03:18 8 原文
AI 资讯 Reddit r/webdev

Need ideas !!!

I’m building a website that will eventually become a collection of useful browser-based tools, similar to iLovePDF but covering many different categories. The goal is simple: No downloads No accounts Fast and mobile-friendly Free to use I’m researching what people actually need before building more tools. What’s a small utility, calculator, converter, formatter, generator, or productivity tool you use regularly but wish had a better version? Examples: Land measurement calculators PDF tools Text formatting tools Developer utilities SEO tools Study tools I’d love to hear your ideas and pain points. submitted by /u/Nikpa_2163 [link] [留言]

/u/Nikpa_2163 2026-06-10 03:01 7 原文
科技前沿 The Verge AI

Nintendo is playing things too safe

Tuesday's Nintendo Direct showcase felt like an important moment for the company. With the Switch 2 heading into its second holiday season, one in which the hardware will be even more expensive thanks to a price hike, it was a chance for Nintendo to really sell new audiences on its latest console - but that's […]

Andrew Webster 2026-06-10 03:01 15 原文