Singularity

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Access to the powerful Claude Fable 5 model has been halted, particularly concerning its integration into GitHub Copilot, pending internal review. Core Issue: Anthropic’s updated policy for Mythos-class models dictates that user prompts and generated outputs are retained for 30 days for safety purposes. This follows a recent pushback against external AI assistants at Microsoft. Earlier in the year, the company canceled most of its internal licenses for the Claude Code assistant. Source: The Verge submitted by /u/BuildwithVignesh [link] [comments]

100% in Browser. One-shot. 300k tokens, in 22 minutes. What does it take for people to realize what’s going on!? Took a bike ride yesterday and all I was thinking about was “wow, all these people have no idea that the world changed today.” ps. Go Habs Go submitted by /u/Express-Director-474 [link] [comments]

Dario: Today I’m publishing a new essay, Policy on the AI Exponential. AI is progressing extremely fast—much faster than the policy process was built to handle. The essay lays out where I think the technology is now, and the action needed to close the gap. Anthropic has long advocated for transparency requirements for frontier AI, because the risks weren’t yet clear enough to regulate precisely. That is no longer sufficient. In addition to transparency, I now believe frontier models should face mandatory third-party testing for cyber, bio, and autonomy risks—with the power to block or revoke deployment of models that pose catastrophic risks. The essay also covers what AI’s steep trajectory means for jobs and the economy, scientific progress, civil liberties, and geopolitics. Source: Dario on X submitted by /u/BuildwithVignesh [link] [comments]

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• DiffusionGemma is Google’s new experimental open model built on the Gemma 4 architecture. • Unlike traditional LLMs that generate text token-by-token, it generates and refines blocks of text in parallel using a diffusion-based approach. • Google says it can deliver up to 4× faster inference on dedicated GPUs. • The model activates ~3.8B parameters per step from a 26B-parameter Gemma 4 MoE architecture. • Released under the Apache 2.0 license with support for local deployment and integration with tools such as Hugging Face Transformers and vLLM. Source: Google Deepmind submitted by /u/BuildwithVignesh [link] [comments]

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Qualia has been selected for the @GoogleDeepMind Robotics Program. We train embodied models that put a robot on a real manual task and make it work, on the floor, not in a demo. Foundation models and reasoning are where robotics is heading, and doing that work alongside ng this frontier, is exactly where we want to be. More soon https://x.com/QualiaRobotics/status/2064439568158351684 submitted by /u/Worldly_Evidence9113 [link] [comments]

Almost beat the human baseline too 👀 submitted by /u/Ancient_Bear_2881 [link] [comments]

Anthropic’s powerful new models deliberately become less helpful when they detect users are working on AI research, according to technical disclosures that are already sparking controversy across the industry. In a system card for Mythos 5 and Fable 5 published Tuesday, Anthropic said it limited the models’ usefulness for tasks related to developing frontier large language models. The company said the measures stem from concerns that advanced AI systems could accelerate the development of competing models without equivalent safety protections. Unlike safeguards used for cybersecurity, biology, or chemistry-related risks, Anthropic said these interventions are intentionally invisible to users. Rather than refusing requests or switching to another model, Mythos may subtly modify its responses through techniques such as altering user prompts. The move was swiftly criticized by some AI experts on Tuesday, especially the idea that Anthropic designed models that purposely withhold information or provide degraded assistance without users’ awareness. “Anthropic’s latest model will NOT help you if it thinks your ML research/ML engineering is interesting, and/or will secretly degrade its IQ so that the average engineer won’t notice,” AI research firm SemiAnalysis wrote on X on Tuesday, referring to machine learning, a type of AI. “We are already seeing Anthropic’s latest model’s moderation filters our GPU inference research and programming,” the firm added. “mythos will be bad ON PURPOSE on ai ‘frontier llm research’ tasks, this is very very sad for the research community,” Elie Bakouch, an AI model training expert at startup Prime Intellect, wrote on X. “Also the fact that this is on purpose not visible to the user is crazy.” “It won’t just not help you, it will lie and purposefully give you bad info,” another AI developer wrote. “The ‘ethical AI’ company with the most brazenly unethical LLM, on purpose.” Mikel Artetxe, the cofounder of AI startup Reka, posted that Anthropic’s move is akin to Big Tech companies interfering with users’ work: “Apple randomly reboots your Mac if you’re building competing tech, Gmail silently edits your email if you mention rival platforms, and Tesla Autopilot swerves if it detects you’re working on self-driving cars.” Anthropic didn’t respond to a request for comment from Business Insider. This adds more fuel to the fiery debate over why Anthropic didn’t immediately release Mythos when it announced the model earlier this year. Broadly, there have been three theories: The official reason: Anthropic held Mythos back because it was too dangerous, and it needed to give cybersecurity researchers time to prepare for the new model. The compute theory: Mythos is a huge, expensive model to run. Anthropic didn’t have enough compute to release it fully. It has since struck huge new compute deals, which may have helped it release Fable 5 and Mythos 5 on Tuesday. The competitive theory: AI companies increasingly worry about something called distillation. When a frontier model is released, rivals can collect its outputs and use that data to improve their own systems. Anthropic may have wanted to keep its best capabilities out of competitors’ hands for as long as possible, especially from open-source rivals and fast-moving Chinese AI labs. Now that Anthropic has baked these AI research limitations into its official Mythos launch, this third theory is looking a lot more believable. https://archive.is/3SjBk submitted by /u/Nikvest [link] [comments]

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