via LessWrong AI [3] — Below is the text of blog post that Dwarkesh Patel wrote on the Anthropic DoW dispute and related topics. He has also narrated it here. By now, I’m sure you’ve heard that the Department of War has declared Anthropic a supply chain risk, because Anthropic…

via Alignment Forum [999] — This work was conducted during the MATS 9.0 program under Neel Nanda and Senthooran Rajamanoharan.There's been a lot of buzz around Claude's 30K word constitution ("soul doc"), and unusual ways Anthropic is integrating it into training.If we can…

via LessWrong AI [6] — TL;DR: Comparing person-years of effort, I argue that AI Safety seems harder than for steam engines, but probably less hard than the Apollo program or . I discuss why I suspect superalignment might not be super-hard. My has come down over the last…

via The Verge AI [4] — Superhuman says it has disabled Grammarly's "expert review" AI feature that said its edit suggestions were "inspired by" real writers, including our editor-in-chief and other Verge staff members. "After careful consideration, we have decided to disable…

via The Verge AI [4] — Canva introduced a new feature that separates flat image files and AI-generated visuals into layered, fully editable designs. The Magic Layers tool is launching in public beta today in the US, UK, Canada, and Australia, allowing design components like…

via Substack Zvi [999] — Benchmarks have never been less useful for telling us which models are best.

via Alignment Forum [999] — I was inspired to revise my formulation of this thought experiment by Ihor Kendiukhov's post On The Independence Axiom.Kendiukhov quotes Scott Garrabrant:My take is that the concept of expected utility maximization is a mistake. [...] As far as I…

via LessWrong AI [4] — I was a few months into 21 years old when a hijacked plane crashed into the first World Trade Center tower. I was commuting in to work listening to the radio (as was the style at the times). I couldn’t figure out how the heck a plane could hit the tower.…

via Alignment Forum [999] — Writing up a probably-obvious point that I want to refer to later, with significant writing LLM writing help.TL;DR: 1) A common critique of AI safety evaluations is that they occur in unrealistic settings, such as excessive goal conflict, or are…

via ArXiv cs.AI [5] — Multi-modal large language models (MM-LLMs) have shown strong performance in medical image understanding and clinical reasoning. Recent medical agent systems extend them with tool use and multi-agent collaboration, enabling complex decision-making. However,…

via LessWrong AI [7] — Many Anthropic employees, especially, are sympathetic to AI safety and (will) have lots of money. This is something that is being talked about a lot (semi-)privately, but I haven't seen any public discussion of it. I find that striking. It seems like the…

via LessWrong AI [3] — TL;DR We release AuditBench, an alignment auditing benchmark. AuditBench consists of 56 language models with implanted hidden behaviors—such as sycophantic deference, opposition to AI regulation, or hidden loyalties—which they do not confess to when asked.…

via LessWrong AI [9] — After using the latest version of Claude Code and being surprised how capable it's become while still behaving friendly and corrigibly, I wanted to reflect on how this new observation should update my world model and my P(Doom).So I reached out to Dr.…

via Alignment Forum [999] — A central AI safety concern is that AIs will develop unintended preferences and undermine human control to achieve them. But some unintended preferences are cheap to satisfy, and failing to satisfy them needlessly turns a cooperative situation into an…

via The Verge AI [4] — Meta is acquiring Moltbook, a Reddit-like platform where AI agents can make and comment on posts, as first reported by Axios. In a statement to The Verge, Meta spokesperson Matthew Tye confirmed the Moltbook team will join Meta Superintelligence Labs as…

via LessWrong AI [7] — TL;DR:I think many of the marginal hires at larger organizations doing AI safety technical or policy work right now (including e.g. Apollo, Redwood, METR, RAND TASP, GovAI, Epoch, UKAISI, and Anthropic’s safety teams) would be capable of founding (or being…

via ArXiv cs.AI [5] — Inference-time alignment effectively steers large language models (LLMs) by generating multiple candidates from a reference model and selecting among them with an imperfect reward model. However, current strategies face a fundamental dilemma: ``optimistic''…

via ArXiv cs.AI [3] — The deployment of autonomous AI agents in derivatives markets has widened a practical gap between static model calibration and realized hedging outcomes. We introduce two reinforcement learning frameworks, a novel Replication Learning of Option Pricing…

via The Verge AI [4] — On Monday, Anthropic filed its lawsuit against the Department of Defense over being designated as a supply chain risk. Hours later, nearly 40 employees from OpenAI and Google - including Jeff Dean, Google's chief scientist and Gemini lead - filed an amicus…

via Substack Zvi [999] — It feels good to get back to some of the fun stuff.