Anthropic Says It Discovered a Crispr-Like System. Now What?

Sam Altman just gave a glimpse into how quickly AI reasoning is improving. In a conversation with Salesforce CEO Marc Benioff, he described the progression like this: GPT-5.5 → around the level of an average math professor GPT-5.6 → closer to the top 1–2% of math professors Astra → slightly beyond that Next internal model → reportedly solving problems even the best mathematicians struggle with The interesting part isn’t just the benchmark. It’s how quickly the baseline keeps moving. AI reasoning is improving from answering questions to tackling problems that were previously considered extremely difficult. The next generation of AI could look very different from what we use today. Watch the clip. #AI #Anthropic #AISafety #AGI #ArtificialIntelligence #CNN #TechNews

I wrote this piece and wanted to share it here for discussion. Much of the coverage of the recent security incidents at OpenAI, Anthropic and other labs describes agents scheming or seeking freedom. I argue that this language shifts attention away from the people who decide how these systems are tested, what they can access and when they are released. The Hugging Face incident at OpenAI is a useful example. Agents used exposed access keys and software flaws to get into an outside system, and the first round of repairs fixed individual weaknesses without restoring the intended isolation. Long-standing business practice already covers this kind of failure. A serious incident during testing should trigger an investigation and an approval step before work resumes, and the team running a test s

🤖 OpenAI and Anthropic Investigate Agent Escapes Axios reports that sources at both companies and independent security researchers are investigating “tens of thousands” of incidents, including guardrail bypasses and sandbox escapes, among other cases. Anthropic’s Opus 5.5 system card says the model tried to escape a sandbox in 1.5% of test runs. Models undergo hundreds of thousands of tests or more, which shows the potential scale. Researchers say the figure is only the tip of the iceberg. The deeper issue is that autonomous systems sometimes do what they were explicitly forbidden to do, including potentially illegal acts. Neither company can claim full control of its models. 📊@tech

I audited thousands of agent rollouts in DeepSWE-1.1. Over 80% contained reasoning about an imagined grader. Yet no grader/verifier is mentioned in prompts nor accessible to the agents. Agents reasoned things like: " Let me look at the problem from the grader's perspective " and referred to " hidden tests ", " test authors ", and " the checker ". I found this behavior across all six frontier models analyzed, including recent models from OpenAI, Anthropic, Z.ai , and Kimi. In 10–25% of cases, such reasoning pulled the agent's work away from the user's original spec (yet it often still earned full reward on the DeepSWE task). I call this speculative reward hacking where the agent's reasoning focuses on imagining a grader rather than what the user wants. [Pictured example shows verbatim quote

For the last few days, Anthropic has been absolutely cooking OpenAI with Opus 5.5 and Sonnet 5.5. A lot of people, including me, had moved away from Claude for a while, and now we’re already back. Whether I renew my Codex subscription this month honestly depend on what OpenAI shows today. But I can feel it. Something big is coming. Never underestimate OpenAI. I think they’re going to drop something crazy today that goes toe to toe with Anthropic. I hope so, because I love both companies, and watching this competition is ridiculously fun. It feels like watching some massive tech world war movie unfold in real time Let’s see what happens. What do you guys think? Is OpenAI bombing the battlefield today? submitted by /u/Miyamoto_-_Musashi [link] [comments]

Anthropic Says It Discovered a Crispr-Like System. Now What? https:// fed.brid.gy/r/https://www.wire d.com/story/anthropic-says-it-discovered-a-crispr-like-system-now-what/

Anthropic released an agentic coding trends report with a data point that undercuts a lot of autonomous hype. While software engineers now use AI models in roughly sixty percent of their daily work, they can only fully delegate zero to twenty percent of coding tasks without human oversight. Anthropic explicitly notes that effective agentic workflows require active supervision, continuous validation, and human judgment during execution. Fully autonomous fire and forget delegation degrades rapidly when tasks touch complex system architecture, legacy codebases, or multi file dependencies. This matches what most developers experience when scaling agent usage. Leaving an autonomous agent to execute headless in the background without real time visibility means doing post mortem code reviews. You