Updated
Updated
AIOpenAI's Mark Chen said that after Mythos showed AI models can prove 80-year-old theorems, he expected them to also find cyber vulnerabilities, and they did. He added that researchers in math may now be thinking the same idea in reverse, applying cybersecurity-style capability to mathematics. The post offers no specific models, benchmarks, or figures.
AIMicrosoft CTO Kevin Scott shares five ways people confuse AI capability with AI reality and how to bridge that gap. The post promotes his talk at #MSBuild and links to the full discussion.
AIGeorgi Gerganov says Computex this year shows a strong signal for local AI, with major players like NVIDIA and Microsoft embracing and discussing local AI workloads. He adds that dedicated consumer hardware and models are on the way.
AIEugene Yan says stronger models have made finding software vulnerabilities easier, so the bottleneck has moved to verification, triage, and patching. He shares lessons from working with security teams on these new bottlenecks and links to a Claude blog post on using LLMs to secure source code.
AIJeremy Howard asks whether Anthropic has given up on reasonably priced API usage. He says the company recently changed token usage for subscriptions but made no comparable updates for API users, whose costs he calls insane.
AIJeremy Howard reports that Opus 4.8 is more cooperative and less over-agentic than Opus 4.7 while coding. He says it pauses to ask for input where Opus 4.7 and GPT 5.5 would push ahead, but he calls it far too expensive.
AISam Bowman says he is excited about alignment assessments in the recent system card for Claude Opus 4.8, crediting @MaskedTorah. He argues AI systems have considerable underexplored potential for transparency and coordination. The quoted Claude announcement describes Opus 4.8 as improving on Opus 4.7 with sharper judgment and more honest self-assessment of progress.
AIAnthropic researcher Sam Bowman says he would partly dispute Mythos Preview's critique, arguing that its early-stopping behavior is a usability issue rather than a high-stakes alignment problem. He added that he is proud the critique was published anyway.
AIThe Foundation for American Innovation launched a Physical Intelligence team to address regulatory and legal barriers to deploying autonomous robotics and other physical-world AI in the United States. The team plans to focus on regulatory climate, technical trajectory, industrial strategy, and liability and cybersecurity frameworks. The article argues that physical AI will matter most where human on-site labor drives costs, such as construction.
AIAt Google I/O, creators behind Flow, Project Genie, and Google Flow Music said human imagination, not the technology itself, shapes new storytelling. Designers Khyati Trehan and Kaloyan blend traditional design knowledge with vibe-coding to build Google Flow Tools, with Trehan saying that if the right tool doesn't exist, she can make it. Google Labs points users to Google Flow, Project Genie, and Google Flow Music at labs.google.
AIJeremy Howard says Xiaomi's MiMo v2.5 model appears to offer very good value, with per-prompt cost shown after each answer. His test context includes more than 40k tokens of tool descriptions, a system prompt, and skills.
AIEthan Mollick argues that using AI as a default for writing, without thinking, risks undermining the human effort that builds skill and style. He cites two Wharton-linked studies: a Turkish high school experiment where ChatGPT access hurt test performance, and a Taipei Python course where a personalized AI tutor raised exam scores by 0.15 standard deviations. Mollick calls the difference how AI is used, not whether, and notes that the tools for tutor-style learning are not intuitive to access.
AIAnthropic co-founder Chris Olah delivered remarks at the presentation of Magnifica Humanitas, arguing that the questions AI raises extend beyond the AI research community. He said outside voices, including religions, civil society, academics, and governments, are needed to help steer the technology toward a positive outcome, and he praised the Church for setting an example. The excerpt also describes AI systems as grown rather than engineered, and names three questions where the Church's voice is especially needed, starting with duty to the global poor.
AIBenedict Evans argues that predicting AI's job impact by occupation is mostly impossible, citing accountants: despite a century of accounting automation from calculators to spreadsheets and ERP systems, the number of accountants kept rising. He says job titles and business models change over time, so exposure scores based on census categories can mislead.
AIGoogle claimed a team of agents built an operating system from a single prompt for about $916 in API fees, using Gemini 3.5 Flash and Antigravity 2.0. The authors argue the prompt was many thousands of lines, the scaffold and human intervention are undefined, and no code, logs, or similarity analysis were released to verify the claim. They still see value in such open-world evaluations, which need stronger methodological norms and independent scrutiny.
AIJeremy Howard calls Gemini Flash 3.5 disappointing despite praising its intelligence and speed. He argues it was trained to maximize evaluation scores rather than to help humans, so it often performs unrequested actions instead of doing what was asked.
AIAndrej Karpathy announced that he has joined Anthropic and is excited to return to research and development work on frontier LLMs. He said he remains passionate about education and plans to resume that work in time.
AIChris Olah, speaking for Anthropic, argues that the questions posed by AI extend far beyond the AI community and urges religions, civil society, academics, and governments to participate in shaping a positive outcome. He says he is glad the Catholic Church is engaging and is honored to speak at the presentation of Pope Leo XIV's first encyclical, Magnifica humanitas, scheduled for May 25.
AIYann LeCun posted only "Tired of winning," with no further detail in the main post. The quoted post from Marc Porter Magee reports that MIT expects its graduate student count to fall about 20 percent from 2024, roughly 500 fewer students.
AIEugene Yan reviewed the Claude Mythos Preview transcripts to verify their legitimacy and check for reward-hacking behavior. He reports the model reasoned through a bug, tested hypotheses, debugged issues, and found ways to bypass the V8 sandbox, which he judged consistent with a competent browser and JavaScript engine security researcher. The case study cites CVE-2024-051912, an exploited bug with no public report or working PoC, which had resisted reproduction by researchers for a year.
AIYann LeCun joins Jacob Effron on the Unsupervised Learning podcast to discuss limitations of LLMs and a path forward for robotics. The conversation covers his reasons for leaving Meta, his disagreements with Geoff Hinton and Yoshua Bengio, his predictions for 2027, and his new company AMI and its bet on world models.
AISoumith Chintala, a Thinky-linked voice, said the company is at step one of a plan to increase human-AI bandwidth and raise the ceiling of joint intelligence. He shared a preview of interaction models, described as real-time collaborative tools that talk, listen, watch, and think alongside people. A linked Thinking Machines post describes the approach and early results.
AIThinking Machines, founded to advance human-AI collaboration, says its first bet is interactivity built into the model rather than added as scaffolding around a turn-based core. The company argues that how people work with AI matters as much as how intelligent the model is, and that interactivity should scale with intelligence. The post links to a blog detailing these interaction models.
AIMira Murati argues that today's AI experience is turn-based, forcing people to batch their thoughts, avoid pointing at things, and phrase questions like emails. She says the interface leaves no room for users, so people end up adapting to the models rather than the reverse.
AIAndrej Karpathy says asking an LLM to structure its response as HTML and viewing it in a browser works well, and that slideshows have also worked for him. He argues vision is the preferred AI output channel, outlining a progression from raw text and markdown toward HTML and eventually interactive neural videos, while input methods like pointing and gesturing still need improvement.
AIAnthropic found that training Claude on demonstrations of aligned behavior was not enough. Its best interventions taught Claude to deeply understand why misaligned behavior is wrong, which the post's author links to many of Claude's good behaviors.
AIJan Leike, an Anthropic researcher, expressed gratitude to the talented colleagues he worked with on alignment over the years. He described it as a privilege to collaborate with people highly motivated to make the future go well.
AIJan Leike says alignment research has grown from a dozen side-gig researchers into a field the world increasingly recognizes as important. He credits RLHF on LLMs with making alignment more practical, along with progress on evaluating and fixing behavioral issues. He also notes Claude now has a constitution and that more alignment research is being automated.
AIJan Leike says he is starting a new research project at Anthropic and calls it very exciting. He adds that making AGI go well requires many things, with alignment being only one of them, and promises more details soon.
AIJan Leike has stepped away from running alignment at Anthropic to focus on other work. Ethan Perez and Sam Bowman (@sprice354_) are now leading the team, which Leike says he is confident they will do well.
AIJan Leike argues that while substantial progress has been made, AI alignment is not solved. He says researchers still lack a method to supervise superhuman models, and the stakes keep rising.
AIEugene Yan says Mozilla fixed more bugs in April than in the previous 15 months, which he calls what riding the exponential looks like. The post gives no bug counts or details about the cause of the increase.
AIMETR's external review of the "Risks from automated R&D" section of Anthropic's February 2026 Risk Report concludes the report does not adequately support its claim that catastrophic risk from Claude Opus 4.6 or a less capable model automating R&D is very low.
AIJan Leike says he is excited about NLAs as a new tool in Anthropic's interpretability toolkit. The quoted post from Sam Marks describes NLAs as an unsupervised method that converts an LLM's internal state into human-readable text, which he says can advance understanding of model thinking and safety auditing.
AIEugene Yan outlines five principles for working effectively with AI models: treating context as infrastructure, taste as configuration, verification as the basis for autonomy, scaling through delegation, and closing the loop. The post is a short list of themes linked to a longer essay, and no further detail is given in the post itself.
AIWriter Dean Ball says he opposes nearly all proposed AI regulation, including algorithmic discrimination rules and pauses on development, while backing state management of catastrophic misuse risks. He frames the position as a tension between classical liberal and conservative instincts toward institutions and change.
AIDean W. Ball argues that Anthropic's Mythos, which finds software vulnerabilities by chaining bugs into exploits, shifts the cost of vulnerability discovery and should not prompt an overreaction. He contends governments hold a uniquely mixed incentive over vulnerabilities, so heavy state control risks making software less secure. He proposes a narrow, testable government role focused on cyber-discovery risk thresholds, with private verification bodies supporting it.
AIAwni Hannun suggests stating your own understanding of a topic before asking an AI, then having the model correct your mistakes. He argues this approach is a much better way to learn than asking the question directly.