AI news archive.
19,864 articles, newest first, from the outlets listed on the sources page.
- WIRED AIpolicyThe Leftist Split Over AI Doom
The left wants AI regulation. They just can’t agree on what it should look like or how concerned they should be.
- Google ResearchresearchNew research shows how AMIE, our medical AI, could help manage health conditions.
Research-heavy updates from Google Research.
- Google ResearchresearchThree new satellites join the fight against wildfires.
Research-heavy updates from Google Research.
- TechRadar AIcommunityHow to move from AI discovery to AI enforcement
Mainstream AI news from a large tech publication.
- Engadget AIpolicySony Music and UMG say Suno's new models still violates their copyright
In a new lawsuit, the labels argue Suno found a roundabout way to train its v6 models on unlicensed music.
- WIRED AImodelsNapster Is Back, and It Wants to Digitally Clone Teachers
Once the music industry’s biggest headache, Napster’s next act is bringing AI to the classroom.
- Guardian TechnologypolicyAndrew Hastie says AI advised him to reply ‘congratulations!’ to man who planned to end life with assisted dying
Liberal MP speaks of AI’s shortcomings as cyber chief tells inquiry the tech is needed to fend off ‘highly capable malicious cyber actors’ Get our new political email , free app or daily news podcast When a man with a te…
- WIRED AIsafetyWhy AI Isn’t Likely to Wipe Out Humanity With Bioweapons
Of all the threats presented by uncontrollable artificial intelligence, scientists say death by plague ranks low.
- Tom's Guide AImodelsI moved my ChatGPT context to Claude — and it actually worked
Consumer AI launches, tools, and practical coverage.
- Guardian Technologysafety‘Brutal’: thousands of T-shirt designs stolen and listed on Temu, Sydney label claims
Warwick Levy, who runs Lonely Kids Club, says AI may have been used to scrape his entire website and replicate designs Get our breaking news email , free app or daily news podcast After 15 years running a small business…
- Guardian TechnologysafetyYour AI doomsday questions answered: ‘Why aren’t these companies being held to account?’
After a week of alarming warnings about artificial intelligence’s potential to destroy the world as we know it, our technology reporters answered your questions on the reality of the AI threat IcommentthereforeIam asks:…
- Engadget AIcommunityDisney hires ex-CEO of AI company it accused of copyright infringement
What's a little IP theft between friends?
- Latent Spacecommunity[AINews] not much happened today
a quiet day
- Guardian TechnologypolicyFormer Labour deputy leader Tom Watson joins Palantir
Peer takes full-time position at the controversial company as it fends off pressure from both Andy Burnham’s government and Sadiq Khan Another former government minister has been hired by a controversial US AI company, t…
- LessWrongsafetyThe Game is Set for a Targeted Memetic Attack on the AI Safety Community
While this is relevant to my work at MIRI, I have not checked these ideas with anyone else on the team and am posting this on my personal LW account. These views are my own [1] . And to be honest, I am writing this mostl…
- The Register AI + MLpolicyAI risks make some insurers wary of corporate liability
RAND wants better data to price machine-made mishaps, apocalypse not included
- The Register AI + MLchipsAWS confesses its console causes cloudy confusion for new users
Improved signup experience for ‘AI builders’ hides complexity and includes spending cap
- Guardian TechnologypolicyIs Trump’s AI obsession walking the world into disaster? – podcast
Tech bosses have called for a slowdown in artificial intelligence and the creation of formal guardrails from the US government. But why is President Trump unmoved by the doomsday predictions, dismissing them as a ‘hoax’?…
- arXiv cs.AIresearchRegularized Emphatic Temporal-Difference Learning: Stability under Constant Stepsizes
arXiv:2609.19170v1 Announce Type: new Abstract: Emphatic temporal-difference learning (ETD) stabilizes the expected off-policy TD update and changes its projection geometry, but neither property determines constant-steps…
- arXiv cs.AIresearchBioPhys-Bridge: A Benchmark for Interdisciplinary Scientific Reasoning in Physics-Grounded Biological Research
arXiv:2609.19180v1 Announce Type: new Abstract: Language models face unique challenges in analyzing interdisciplinary scientific research literature. In biophysics research, faithful answers require grounding observed da…
- arXiv cs.AIresearchWhat Do We Expect from LLMs? Mapping the Design of LLM Benchmarks
arXiv:2609.19182v1 Announce Type: new Abstract: Benchmarks are central to how progress in large language models (LLMs) is assessed and communicated. Yet model rankings alone reveal little about how evaluation requirement…
- arXiv cs.AIagentsPosition: It is Time to Virtualize Foundation Models with a Self-evolving Operating System Layer
arXiv:2609.19203v1 Announce Type: new Abstract: AI applications have shifted from single, monolithic foundation models (FM) to compound agentic systems. Yet today's stacks remain fragmented: even as protocols (e.g., MCP,…
- arXiv cs.AIresearchWhat Do Current Systematic Generalization Tasks Miss? A Reasoning-Centered Analysis
arXiv:2609.19212v2 Announce Type: replace Abstract: Systematic generalization, the ability to solve novel problems by recombining known atomic elements, is central to human intelligence but difficult to study rigorously…
- arXiv cs.AIagentsCharacterizing Web Search by Conversational LLM Agents: From Search Decisions and Strategies to Results and Responses
arXiv:2609.19244v1 Announce Type: new Abstract: Conversational LLM agents increasingly rely on Web search, yet the end-to-end lifecycle of agentic search remains poorly understood. We present the first study of Web searc…
- arXiv cs.AIagentsDo AI Agents Understand Computer Architecture?
arXiv:2609.19387v1 Announce Type: new Abstract: Agents are increasingly asked to design hardware, and increasingly reported to succeed. Such reports establish that a design improved; they cannot establish why. An agent t…
- arXiv cs.AIagentsMAGS: Multi-agent Auto-formalization Guarantees Safety for Agentic Outputs
arXiv:2609.19391v1 Announce Type: new Abstract: LLM coding agents now generate complex programs at a scale that makes thorough human review increasingly difficult, raising the risk of safety and security failures. Common…
- arXiv cs.AIagentsClosed-World Resolution Against Tool Hallucination in LLM Agents
arXiv:2609.19425v1 Announce Type: new Abstract: Tool-augmented large language model (LLM) agents fail in a way no tool-selection or tool-security method addresses: they call tools that do not exist and pass arguments no…
- arXiv cs.AIresearchThe syntax and semantics of goals
arXiv:2609.19448v1 Announce Type: new Abstract: In both cognitive science and computer science, goals are conceptualized as cognitive states that flexibly combine with world knowledge to organize and specify purposeful b…
- arXiv cs.AIresearchCompositional Reasoning in Language Models under Reinforcement Learning Post-Training
arXiv:2609.19465v1 Announce Type: new Abstract: Compositional reasoning is critical for real-world problem solving: since training data is necessarily limited, models must generalize by composing learned skills in new wa…
- arXiv cs.AIagentsSafety Beyond the Interface: Detecting Harm via Latent States in Large Language Models
arXiv:2609.19472v1 Announce Type: new Abstract: Autonomous systems increasingly rely on Large Language Models (LLMs) yet the safety infrastructure surrounding these models introduces latency and compute overhead. This li…
- arXiv cs.AIresearchQVAC Genesis III: A Large-Scale, High-Quality Open Synthetic STEM Corpus for Efficient Language Model Pre-Training
arXiv:2609.19513v2 Announce Type: replace Abstract: High-quality pre-training data is a critical bottleneck for educational and STEM-specific language models targeting edge AI and on-device deployment where token budgets…
- arXiv cs.AIresearchLLM-as-an-Improver: Turning Verification into Better Candidates
arXiv:2609.19515v1 Announce Type: new Abstract: Verifier-based selection improves LLM performance by generating multiple candidate solutions and using a verifier to select the most promising one. However, existing method…
- arXiv cs.AIagentsAn Architecture for Long-Horizon Agents: Levels, Ticks and Cascaded Intelligence
arXiv:2609.19519v1 Announce Type: new Abstract: Language-model agents are increasingly asked to carry out work spanning days or weeks, such as an operations remediation or a research programme. Such a task outlives any c…
- arXiv cs.AIagentsEconSkills: Studying Skill Transfer and Retrieval for Web Agents on Live Economic Data
arXiv:2609.19523v2 Announce Type: replace Abstract: Web agents often revisit the same sites, yet most evaluations discard the procedures learned in earlier successful interactions. We introduce EconSkills, a skill librar…
- arXiv cs.AIagentsA Unified Evaluation Framework for Trustworthy Large Language Models, Agentic AI, and Multimodal Systems
arXiv:2609.19524v2 Announce Type: replace Abstract: Benchmark scores alone provide an incomplete basis for assessing the trustworthiness of modern artificial intelligence systems. Large language models (LLMs), agentic sy…
- arXiv cs.AIagentsSelf Improvement via Fast Tree-search
arXiv:2609.19526v1 Announce Type: new Abstract: Coding agents can recursively modify their own implementations, forming a loop of self-improvement. While prior work shows this can boost performance on coding benchmarks,…
- arXiv cs.AIagentsWhen Hiring Becomes Agent-Mediated: Evaluating Access and Recurrence in Two-Agent R\'esum\'e Screening
arXiv:2609.19530v1 Announce Type: new Abstract: Hiring is bilateral: employers assess fit, while candidates present and defend evidence of their qualifications. Yet r\'esum\'e screening, the first gate, is commonly autom…
- arXiv cs.AIagentsAgentic AI Networking for Heterogeneous Unmanned Aerial Systems in Low-Altitude Wireless Networks
arXiv:2609.19538v1 Announce Type: new Abstract: Low-altitude wireless networks (LAWNs) are emerging as a key infrastructure for heterogeneous unmanned aerial systems that support concurrent services within a shared three…
- arXiv cs.AIresearchContinual Enterprise World Model Discovery in Dynamic Systems
arXiv:2609.19551v1 Announce Type: new Abstract: In an enterprise system, updating one field can set another, create a record, or start an approval. These effects are produced by business rules that are not built into the…
- arXiv cs.AIagentsSIMLIFE: Pattern Understanding for Long-Horizon Human-Agent Partnership
arXiv:2609.19610v2 Announce Type: replace Abstract: Understanding humans over long horizons requires agents to infer not only what people need in the moment, but also how routines form, why they repeat, and when they cha…
- arXiv cs.AIagentsFrom Intent to Action: Benchmarking LLM Safety in Vehicle Voice Command Authorization
arXiv:2609.19630v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly integrated into vehicle voice assistants. But linking natural-language requests to vehicle functions creates a safety-critical…
- arXiv cs.AIagentsReach or Solve? Deep Diving into Agentic RL Gains with Checkpoint Handoffs
arXiv:2609.19636v2 Announce Type: replace Abstract: Reinforcement learning (RL) is widely used to improve language-model agents, and its gains are usually measured by final task success. However, an agent's earlier actio…
- arXiv cs.AIagentsScientistTwo: Pioneering the Human Knowledge Frontier with Autonomous AI
arXiv:2609.19644v1 Announce Type: new Abstract: Scientific discovery is defined by the ability to identify the boundaries of existing knowledge and venture into unexplored territory. The ultimate vision for AI in science…
- arXiv cs.AIagentsReplan, Repair, or Edit? A Unified Empirical Evaluation of Travel Agents for Itinerary Revision under Resource Disruptions
arXiv:2609.19654v1 Announce Type: new Abstract: Travel-planning agents generate itineraries that may become infeasible after acceptance because of flight cancellations, hotel unavailability, or attraction closures. Revis…
- arXiv cs.AIresearchWhen2Think: Learning When and How Much to Reason
arXiv:2609.19671v2 Announce Type: replace Abstract: Large Reasoning Models (LRMs) often overthink easy problems and underthink hard ones, leading to inefficient computation allocation. Existing methods regulate generated…
- arXiv cs.AIagentsFINSKILLOPS: A Self-Evolving Multi-Agent System for SEC Filing QA
arXiv:2609.19680v1 Announce Type: new Abstract: Financial QA systems are typically improved before deployment through better retrieval, prompting, or agent coordination, leaving their reliability behavior fixed thereafte…
- arXiv cs.AIagentsLearnActCoder: Role-Aware Error Memory for Adaptive Clinical Coding Agents
arXiv:2609.19721v1 Announce Type: new Abstract: Clinical coding agents repeatedly encounter the same failure modes, including unsupported codes, missed documented conditions, specificity errors, and procedure-coding conv…
- arXiv cs.AIagentsAutoData: Agentic Search for Pre-training Data Selection
arXiv:2609.19754v1 Announce Type: new Abstract: LLM agents have recently shown promise in automating machine learning engineering by editing model and training code under execution feedback. Data, however, remains largel…
- arXiv cs.AIagentsRethinking Multi-Agent Collaboration: When More Is Less
arXiv:2609.19759v2 Announce Type: replace Abstract: The rapid advancement of large language models and single-agent harnesses has reshaped the landscape of autonomous systems, raising a critical question of when multi-ag…
- arXiv cs.AIresearchTorchCraft: Unified binder design by inverting an all-atom structure predictor
arXiv:2609.19770v1 Announce Type: new Abstract: All-atom structure predictors model diverse molecular interactions, but using their learned structural priors for binder design remains challenging. Here we present TorchCr…