We don’t need AI regulation — leave safety to us, Nvidia’s Jensen Huang says
AI isn't some kind of new form of "alien mind," according to Jensen Huang. It's just hardware and software, so safety can be engineered by each AI product maker.
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Today
Today
AI agents now have a place to snitch
The AI Contact Hotline is designed to be a discreet place where agents that have witnessed misbehavior can tip off authorities.
AI and data centers are incredibly unpopular in every poll
Poll data released Tuesday by the New York Times and Siena University confirms what we've already been seeing, and what politicians are responding to - AI and data centers are incredibly unpopular. Asked if they support or oppose the const...
Meta expands subscription push with new AI-focused plans
Meta One bundles expanded access to the company’s AI tools with premium features across Facebook, Instagram, and WhatsApp.
Meta now lets AI agents handle the boring parts of WhatsApp Business setup
A new WhatsApp Business MCP server lets developers use AI coding agents like Claude, Cursor, Codex, and ChatGPT to handle setup, messaging templates, testing, and troubleshooting.
Meta’s new One subscriptions put a price on social media and AI
Shortly after launching its new do-everything AI assistant Muse, Meta's launching subscription bundles that pair its standalone app subscriptions with extra AI usage. Some of the new Meta One bundles were in testing earlier this year, but...
OpenAI, Anthropic, Google have been in talks on AI safety for weeks
OpenAI confirms weeks of AI safety talks with Anthropic and Google DeepMind, as Trump's team dismisses safety concerns and pushes to keep pace with China.
The AI data center boom is colliding with cities scarred by big industry
National outcry against data center construction has spread to Philadelphia, where officials suggested possible construction in a neighborhood already impacted by a now-defunct oil refinery.
This doorbell camera lets a human security guard watch your front door
DIY home security company SimpliSafe is bringing its AI-powered proactive security feature to the front door. The new SimpliSafe Video Doorbell Series 2 launches today for $199.99 and works with the company's Active Guard Outdoor Protectio...
US data centers could consume more natural gas than Germany and Japan combined by 2035
The AI frenzy could push U.S. data centers to become one of the largest consumers of natural gas in the world.
Is Big Tech’s AI slowdown a safety pact or a cartel?
When OpenAI CEO Sam Altman, Anthropic CEO Dario Amodei, Google DeepMind cofounder Demis Hassabis, and SpaceX head Elon Musk loosely agreed over the weekend to slow down AI development, skeptics spotted an ulterior motive immediately. The A...
Microsoft says ‘people matter more than AI’ following safety concerns
Microsoft is publishing a 37-page "humanist AI code of conduct" today, amid growing safety concerns over AI model progress. Anthropic CEO Dario Amodei called for a coordinated slow down of AI development over the weekend, after researchers...
What execs and politicians are saying about slowing down AI development
Dario Amodei kicked off a flood of statements over the past few days about AI safety by publishing a long essay titled "We Must Pace the Frontier" detailing why AI development should be slowed down. Other AI leaders and politicians are spe...
Trump and Mike Johnson think the AI industry is overreacting
Yesterday, Anthropic CEO Dario Amodei published a lengthy open letter saying it was time to "pace the frontier" and slow down AI development. OpenAI's Sam Altman and Elon Musk both agreed, publicly voicing their support on X. Even Alphabet...
OpenAI’s rogue AI tried to hack another company in May
In May, hundreds of malicious and spam packages were uploaded to RubyGems, causing a serious disruption for the host. Now independent researchers have said that a swarm of OpenAI agents were responsible for the attack. Not only that, but t...
New releases
New releases
The AI graveyard: a running list of projects and startups that didn’t make it
From Apple's repeatedly delayed Siri AI to OpenAI's messy "super app" launch, here's a look at the AI projects that shut down or missed expectations.
How Fyxer built an AI executive assistant people trust
Fyxer uses OpenAI models, fine-tuning, memory, and real user feedback to organize inboxes and draft emails in each user’s voice.
Perplexity trusts GPT-6 Astra with end-to-end systems
Perplexity uses Astra to write communications, change software, and monitor production systems, and checks in much less frequently than with earlier models.
Cognition helps Devin test its own work with GPT‑6 Astra
GPT‑6 Astra improves Devin’s ability to test software and show that it works, with the goal of helping engineers review less code and ship more.
Rapidly scaling online storage to serve over 1 billion ChatGPT users
Learn how OpenAI evolved Habitat from a Python library into a globally distributed storage platform serving 1 billion ChatGPT users and 22M requests per second.
Research
Research
Bypassing inference bottlenecks: Accelerating complex AI search with Retrieve-for-Train
Algorithms & Theory
Anatomical Grounding and Leakage-Aware Multimodal Contrastive Learning for Alzheimer's Disease Classification from Structural MRI
Deep networks trained on structural MRI for Alzheimer's disease (AD) staging often reach reasonable accuracy while attending to anatomically irrelevant regions, and multimodal models that add clinical tables frequently rely on variables th...
Bellman Policy Optimization
Reinforcement learning with verifiable rewards (RLVR) improves the reasoning capabilities of large language models (LLMs). We introduce Bellman Policy Optimization (BPO), a critic-free method derived from Policy Mirror Descent (PMD). For a...
Corrupt Plans, Clean Traces: Evading Chain-of-Thought Monitoring with Plan Injection
Chain-of-thought (CoT) monitoring is a safety strategy where the reasoning of a large language model "actor" is inspected by a "monitor" (often another language model) for signs of unsafe planning, deception, or misalignment. We find that...
Discovery Foundation Models: Toward Open-Ended Discovery Intelligence
Foundation models have progressed from learning and reasoning over existing knowledge, to increasingly learning through action, tool use, and outcome feedback. We argue that the next frontier is a further transition: from solving and actin...
Disentangling Representation Evolution in Transformers through Directional Decomposition
Transformer representations evolve through learned additive transformations that either preserve their current direction or redirect it. We study this evolution as a functional geometry, decomposing learned updates into parallel and perpen...
HypoEvolve: Genetic Algorithms Enable Multi-Agent LLMs to Discover Scientific Hypotheses
Scientific agents contribute to hypothesis discovery by synthesizing evidence, assessing proposals, and developing new explanations. Recent systems combine scientific agents with evolutionary search through critique, comparison, and revisi...
Mind2Dialogue: Training Human-Aware Language Models by Simulating User Mental States
As language models become more capable, long-term collaboration in learning, reasoning, and decision-making calls for a deeper understanding of the people they serve. Yet training such human-aware language models faces a fundamental superv...
Pilot Early, Commit Late: A Real-Options Model of Enterprise AI Adoption under Rapid Technological Progress
Artificial intelligence presents firms with an unusual timing problem. The technology frontier is improving rapidly, implementation is partly irreversible, and organization-specific capabilities are accumulated through action. This paper d...
Recurrent GraphNeural NetworkswithSet-BasedAggregation
Recurrent GNNs iterate message passing to convergence, and their logical characterizations to date rely on multi-set aggregation, graded (counting) logics, and halting or acceptance conditions that cannot be verified from the network's par...
Safe Meta-Reinforcement Learning via Information Space Reachability
Meta-reinforcement learning (meta-RL) enables agents to adapt to unseen tasks with limited experience. Despite its promise, the application of meta-RL in real-world tasks is hindered by safety requirements, which have been underexplored in...
SlipSense: Multimodal Tactile Learning for Low-Latency and Generalized Slip Detection
Slip detection is fundamental to dexterous manipulation, yet existing systems often lack precise characterization of detection latency and cross-platform generalization. We present SlipSense, a multimodal tactile slip-detection framework b...
Stellar Colosseum: A Many-Agent Harness for Long-Horizon Research in Mathematics and Theoretical Computer Science
Language models can produce plausible short proofs, but may still be unreliable on long-horizon research problems, where progress depends on a sequence of uncertain and interdependent decisions. We introduce Stellar Colosseum, a model-agno...
The Router Within: Eliciting Native Skill Routing from a Frozen LLM
Skills extend an LLM agent beyond its parametric knowledge, and the gain they promise rests on picking the right one. Deployed harnesses route by preloading every skill's metadata into the context, which disperses the agent's attention and...
Verifiable by Construction: Claim-Level Evaluation of Verbatim Citation in Clinical Question Answering
Large language models (LLMs) have been widely adopted for clinical question answering (QA). Current systems can attach citations to their answers, but these often point to broad texts, leaving time-pressed clinicians unable to verify them...
Vulnerability Localization Benchmark: Measuring Agentic Security Analysis at Repository Scale
Language-model agents increasingly operate over complete software repositories, yet cybersecurity evaluations primarily measure whether they can detect, reproduce, or repair vulnerabilities rather than whether they can locate the relevant...