OpenAI's latest ad format will put images of sponsored products and services on your screen. The ads, which OpenAI will begin testing in the US later this month, will "initially" appear when you generate images with ChatGPT, according to an announcement on Monday. The company first brought ads to ChatGPT in February. Until now, ChatGPT's ads only showed a company's name, logo, and a link to its product in a "sponsored" section beneath your chat. OpenAI's visual ad format will similarly remain separate from the image you generate and will "not influence the answers ChatGPT provides." Ads won't appear if you subscribe to ChatGPT's Plus, Pro, … Read the full story at The Verge.

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Breast cancer is the most commonly diagnosed cancer among American women — yet the gaps in care are wide. A majority of women over age 40 skip the recommended annual screening. Radiologists are reading more mammograms with fewer colleagues. And when a diagnosis arrives, the tests that inform treatment can take weeks to return results. […]

We celebrated our 16th birthday with 46 announcements across open source, post-quantum security, AI agents, and developer platform upgrades. Here’s a day-by-day roundup of everything we shipped.

Most AI coding demos stop at task managers, weather apps, or simple chatbots. For this project, we take on something more demanding: building an enterprise customer-support platform that can investigate complaints, retrieve relevant policies, recommend resolutions, and keep risky actions behind human approval. This gives us a practical way to test Claude Fable 5.1 as […] The post Building an Enterprise AI Customer Support Platform with Claude Fable 5.1 and Claude Code appeared first on Analytics Vidhya.

Who chooses what AI gets to do?

Boss of OpenAI calls for a regulatory light touch because of the ‘good stuff’ the technology can deliver Sam Altman says he believes the world should accept “bad things” happening with AI in exchange for the benefits of the technology. The chief executive of OpenAI cited hacks, scams and “other bad things that will happen” in an interview that sparked an instant backlash from critics of the major AI companies. His comments came after one of his company’s safety experts resigned, saying at the weekend that its “culture is broken”. Continue reading...

On 13 September, leading luminaries and up-and-coming talents in mathematics and computer science congregated at the annual Heidelberg Laureate Forum in Germany for a week of discussion, networking, and—naturally—wurst. Having attended several of these events in the past, the mathematicians’ chatter is normally concerned with which famed researchers are attending, or what interesting problems they have been working on. But instead, every snippet of conversation caught in passing or any debate accidentally overheard was about how AI companies such as OpenAI, Anthropic, and Google are steamrollering their way through mathematics. And there is good reason for these fervent discussions. Mathematics is the perfect testing ground for AI, involving step-by-step logical reasoning and answers that…

In this article, you will learn what an AI agent is and how to build one from scratch in plain Python using the Anthropic API,...

The pharmaceutical industry is producing more clinical evidence than ever before, but the ability to turn that evidence into timely strategic decisions is struggling to keep pace. PubMed added more than 1.5 million citations in fiscal year 2023, roughly 4,300 a day, according to the National Library of Medicine. On top of that literature, medical […]

The following article was originally published on the Agentic AI Foundation blog site and is being republished here with the author’s permission. A customer asks your company’s AI agent to update the shipping address on account 123. The agent relies on a support ticket with a typo and updates account 132 instead. The customer relationship […]

OpenAI introduces a new visual ad format in ChatGPT and expands measurement tools, attribution partnerships, and brand suitability for advertisers.

Norbert Wiener, godfather of cybernetics, once said, "The thought of every age is reflected in its technique." For the past century, our thought has been reflected in our computers, including by those in the AI industry. Google's Demis Hassabis calls the brain "a biological approximation to a Turing machine." Elon Musk puts it more bluntly, declaring that "people should just think of the brain as a biological computer." (Musk's brain often worries me.) But humans are more complex than a straightforward comparison to computers gives us credit for - and far more than most of the AI industry seems to appreciate. And as their products push e … Read the full story at The Verge.

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This is a chance for the PM to advance his progressive agenda and tackle urgent issues such as AI regulation and climate action Among the many crucial decisions Andy Burnham has to make over the next few weeks, one has gone almost completely unremarked: what Britain’s priorities will be when it assumes the presidency of the G20 next year. Burnham has said he wants to concentrate on domestic policy. But with the world in turmoil, chairing the group of the world’s largest economies will be one of his most important responsibilities. Michael Jacobs is professor of political economy at the University of Sheffield and a former energy and climate change adviser to Gordon Brown when he was prime minister Continue reading...

One transformer ran candidate generation and ranking in Yandex Music's A/B test without hand-engineered features, lifting likes 11.42%. The post Yandex Introduces Sona: A Single Generative Recommender That Replaces Entire Recommendation Cascade appeared first on MarkTechPost.

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Abuse material monitor says number of AI images assessed this year is already 40% higher than last year’s total AI-generated child sexual abuse material is proliferating online, with the amount of illegal material investigated this year already exceeding the total for 2025. Analysts at the Internet Watch Foundation have found more photorealistic child sexual abuse material in the first half of 2026 than for the whole of the prior year. The UK-based IWF, which monitors abuse material globally, said it had assessed 6,310 AI images that met the legal definition of child sexual abuse, 40% higher than last year’s total of more than 4,500. Continue reading...

Alibaba's Qwen went from an invite-only chatbot in April 2023 to a 2.4-trillion-parameter open-weight model in August 2026. This is the full story, release by release: every major model, its key feature, and how its license changed. Each claim links to its source. The post The Story of Qwen: Alibaba’s AI Models From 7B to 2.4T appeared first on MarkTechPost.

arXiv:2610.02459v1 Announce Type: new Abstract: Coding agents are extending their reach into the physical world by writing and executing robot control programs. One might expect the agents to use the existing mature software stack that engineers have developed over decades to access sensors and control motion. Yet prior work primarily engineers complex custom harnesses to orchestrate agents for robot use, particularly by prescribing specialized workflows and providing bespoke interfaces. This raises the question: "Is such additional harness engineering necessary?" We introduce OpenRUA, a zero-abstraction harness that bypasses bespoke abstraction layers by providing off-the-shelf coding agents with only terminal access to the robot's native software interface ROS 2. OpenRUA employs a minim…

arXiv:2610.02428v1 Announce Type: new Abstract: Autonomous mobile robots (AMRs) increasingly perform material transport in production logistics, where their operation is governed by job generation, dispatching and robot control. We present MoRoOp, a dataset of AMR operations recorded in a laboratory kit preparation and supply scenario over nine eight-hour shifts. During each shift, an AMR executed stochastically generated kit supply, empty-box refill and charging jobs. The dataset links job specifications, the operations constituting each job, dispatch events documenting operation state transitions and outcomes, and robot-state observations comprising position, orientation, velocity, per-wheel state of charge and diagnostics. It contains 1,382 jobs, 4,815 operations, 19,352 dispatch event…

arXiv:2610.02398v1 Announce Type: new Abstract: A robot demonstration records two things in the same frames: what happened to the objects, and how one particular arm made it happen. We condition on the first. A demonstration is compiled into an effect program: the 3D keypoint trajectories of the objects that moved, two points marking where each was held, and the configuration the scene ends in, with the demonstrator removed. PEWAM, a 71.5M-parameter world-action model, generates effect, robot execution, action and terminal state as four streams with independent flow-matching times, so clamping a program and sampling the execution turns inference into programming, re-solved closed loop from the live scene. On held-out LIBERO-Goal tasks, one demonstration's program completes 40 of 90 episod…

arXiv:2610.02368v1 Announce Type: new Abstract: Long-horizon compositional manipulation has become increasingly important for real-world robot deployment, where a single task involves multiple coordinated subtasks. Existing world-action models (WAMs) jointly predict short-horizon visual futures and actions, but typically lack explicit subtask-level reasoning. We propose Visual Goal-conditioned Action Reasoning (ViGAR), a hierarchical framework that factorizes manipulation into a visual subgoal planner and a subgoal executor. Given the current observation and global instruction, the subgoal planner predicts a visual subgoal for the next subtask. The subgoal executor then jointly generates future visual trajectories and actions conditioned on the predicted subgoal. Both components share a p…

arXiv:2610.02360v1 Announce Type: new Abstract: Vision-language-action (VLA) policies enable diverse robotic manipulation but can fail during execution without recognizing their own errors. Human observers provide complementary signals, as unexpected robot behavior can trigger rapid vocal, facial, or verbal reactions before failure is completed. We introduce SocialVLA, a local, policy-agnostic social perception gateway that converts spontaneous human reactions into runtime intervention signals for VLA manipulation. SocialVLA combines causal paralinguistic audio detection, visual reaction recognition, explicit stop phrases, and robot-relevance estimation. An asynchronous first-event fusion mechanism triggers a VLA hold from the earliest sufficiently confident signal, while a separate speec…

arXiv:2610.02341v1 Announce Type: new Abstract: Safe whole-body motion is essential for deploying humanoid robots in unstructured environments. Modern humanoid control commonly separates reference specification from execution, with a planner, teleoperator, or motion generator providing a reference that a reinforcement-learning policy tracks through dynamically feasible whole-body control. Runtime safety filters, such as control barrier functions (CBFs), offer a promising approach for enforcing newly introduced constraints via interventions on the tracker's outputs. We show, however, that treating the tracking policy and safety filter independently induces fundamental mismatches, as filtering alters both the executed actions and the induced state distribution. We study this policy-filter i…

arXiv:2610.02339v1 Announce Type: new Abstract: Robot demonstrations may contain useful behavior even when individual episodes are inefficient or unsuccessful. Trajectory stitching offers a way to compose these behaviors into improved training data, but identifying useful connections and verifying their feasibility is difficult in high-dimensional robot data, where many prior methods rely on low-dimensional state representations. We introduce NEEDLE, an offline dataset-augmentation algorithm that addresses these challenges by adding short, verified action bridges between recorded observations in high-dimensional robot demonstrations. First, NEEDLE identifies and creates connections that bypass suboptimal detours, broaden action coverage, and augment the original dataset with failed trajec…

arXiv:2610.02338v1 Announce Type: new Abstract: A growing body of work suggests that tactile sensing gives robot policies contact information that complements vision in dexterous manipulation. However, visuo-tactile robot data remains scarce: dexterous demonstrations require teleoperating robots, which limits dataset scale. Human demonstrations are far cheaper to collect and offer a path to scale this data, but only if human and robot hands carry tactile sensors with corresponding signals. This requires sensors that conform to different hand geometries, cover the full hand, and share a common layout across embodiments. We present SoTa, a low-cost capacitive tactile skin that provides full-hand coverage on humans and robots while preserving a shared layout of 202 taxels across correspondin…

arXiv:2610.02323v1 Announce Type: new Abstract: Flow-based Vision-Language-Action (VLA) policies generate action chunks by transporting samples from a task-agnostic isotropic Gaussian source. As this source is conditioned on neither recent execution nor predicted future evolution, (i) it discards the local continuity established by recently executed motion. (ii) Even when predictive world representations are introduced, they often only condition the transport dynamics rather than determine where generation starts, how far it may deviate, or along which action directions it may expand. Building on this observation, we introduce ProAct, a world-calibrated proposal-to-action framework that makes the generative source itself predictable. (i) To preserve motion continuity, a lightweight Propos…