Theory is easier to trust once it's running against a real API, so both examples in this article use the same tool — a get_weather function backed by <a href="https://open-meteo.

Discussion | Link

After teasing its new Copilot "super app" last month, Microsoft is officially unveiling it today. The redesigned Copilot app bundles three AI capabilities into a single interface of chat, coding, and agents. As part of the launch, Microsoft is also rebranding Scout, the AI personal assistant it unveiled at Build earlier this year, as Autopilot. This new Copilot app will have three tabs for Home, Code, and Autopilot, with Home combining Copilot Chat and Cowork together. It's the default landing experience for Copilot users, and Microsoft is also planning to include a Today feature inside it that works as personalized dashboard for important … Read the full story at The Verge.

Xi is expected to depart Washington after touring the nation’s vault of records, where the Declaration of Independence, the Constitution and the Bill of Rights are held Sign up for US Breaking News emails Hello and welcome to the US politics live blog. Donald Trump is taking Chinese president Xi Jinping to visit the National Archives later today, showing off the sacred texts of US democracy to the leader of the world’s most powerful communist country. Donald Trump welcomed Xi Jinping to the White House for a state dinner in honor of the Chinese leader that was not televised because the White House continued to deny full access to the event to CNN journalists on Thursday, despite a court order. Writing on his social media platform, Trump complained that two of the three outlets he banned f…

Discussion | Link

Continue reading...

I suspect nearly all of my students use AI, and I worry about its corrosive effects. We must not entrust tech companies with our long-term health Prof Devi Sridhar is chair of global public health at the University of Edinburgh When I was a postgraduate student at the University of Oxford in the early 2000s, I interviewed for a major consulting firm. All my friends were being recruited, and I thought why not give it a shot? Aside from the usual maths-proficiency test (how quickly can you crunch numbers in front of a client and look smart), I was asked about what the future of streaming could look like. I gave a long-winded answer about the unintended consequences of changing how humans interact with each other when a new technology is introduced, and why this may not be in the best intere…

LangChain announced new updates to LangSmith. Updates include Engine v2 with red teaming and automatic testing, a new version of Managed Deep Agents, trajectories and more.

Projects are the bridge between learning and becoming a professional. While theory builds fundamentals, recruiters value candidates who can solve real problems. A strong, diverse portfolio showcases practical skills, technical range, and problem-solving ability. This guide compiles 10 solved projects across AI domains, from basic machine learning to advanced generative AI system. The tools and […] The post 10 Solved Generative AI Projects to Boost your Profile appeared first on Analytics Vidhya.

Discussion | Link

Discussion | Link

Discussion | Link

Discussion | Link

A quiet day lets us discuss the work behind the scenes - now open for business!

Expert says Australia’s criminal laws should be clarified to determine how fault is applied to a corporation when its AI agent commits a crime Get our new political email, free app or daily news podcast The federal government could change Australian laws if the current legal framework could not respond to the unprecedented OpenAI hack of Medicare, ministers have confirmed. On Friday, the government said the review by spy agency, the Australian signals directorate, would consider whether legislative change was needed after the prime minister revealed an artificial intelligence agent developed by OpenAI hacked Medicare’s statistics website and three other systems in June. Continue reading...

Discussion | Link

Fastino Labs has released GLiNER2.5-Decide, a 340M-parameter open-weight decision model. It takes text and a schema of typed questions and returns structured answers. Each answer comes with a probability distribution, a confidence score, and constraint-feasibility metadata. It targets the frequent judgment calls inside agent pipelines: routing, triage, tool selection, and guardrails. Is it deployable? Yes, […] The post Fastino Releases GLiNER2.5-Decide: A 340M Open-Weight Decision Model That Runs on CPU appeared first on MarkTechPost.

Discussion | Link

Black Forest Labs (BFL), the lab behind the FLUX image models, has released FLUX 3 Action. It is a 7B open-weights World Action Model (WAM) for robot control. The model reads camera frames, robot state and a text instruction. It then predicts future video frames and the next chunk of actions together. On the RoboLab-120 […] The post Black Forest Labs Releases FLUX 3 Action: A 7B Open-Weights World Action Model That Tops RoboLab-120 appeared first on MarkTechPost.

arXiv:2609.28818v1 Announce Type: new Abstract: Generalization in robotic manipulation requires policies to perform tasks across diverse unseen object instances that vary in shape, size, and pose. However, conventional behavior cloning (BC) methods often overfit to instance-specific geometry and appearance, limiting transfer to novel objects. We introduce KeyGen, a framework that learns canonicalized semantic 3D keypoints from point clouds and uses them as structured object-centric representations for policy learning. A visuomotor diffusion policy conditions on these keypoints together with object-centric geometry to predict full manipulation trajectories, enabling consistent geometric correspondence across object instances. To evaluate category-level generalization, we construct a photor…

arXiv:2609.28816v1 Announce Type: new Abstract: Robotic bodies are inherently distributed in sensing and actuation, yet learning-based control still commonly relies on centralized information processing. This work studies the problem of information organization in communication-constrained embodied control: which computations should remain local, and which information is worth transmitting for whole-body coordination. We propose FlyCNS, an embodied information-organization framework inspired by the Drosophila brain--nerve-cord connectome. FlyCNS preserves local sensorimotor computation within each limb and enables selective long-range communication through separate ascending and descending routing pathways. From a real connectome, FlyCNS extracts the directional structural complexity of t…

arXiv:2609.28807v1 Announce Type: new Abstract: Over the course of a lifetime, robots may encounter novel scenarios unaccounted for in its original training that result in performance degradation. One common approach to mitigating this issue is to further grow the offline training dataset in hopes of producing a policy robust to these changes. In contrast, biological learning occurs moment-to-moment via a stream of experience, unlike the predominantly batch-based and offline nature of deep learning. Although recent works show the feasibility of stream-based deep reinforcement learning, where updates use only the latest experience, none have shown it to be a viable continual learning framework for adapting robotic policies to unseen changes. In this paper, we present the first analysis of…

arXiv:2609.28798v1 Announce Type: new Abstract: Long-horizon manipulation often requires reasoning about state absent from the current view, such as a vanished object's location, temporal identity, or the contents of a shuffled container. We present OCC4M ("Occam"), an object-centric 4D memory that maintains persistent tracks in a shared world frame and explicitly represents temporal, motion, and containment relations. A vision-language model (VLM) queries this structured memory to select actionable targets for history-free low-level execution. Across seven simulation conditions and 350 episodes, OCC4M achieves 96.6% memory success and 88.9% end-to-end success, versus 54.6% and 57.7% for FrameSamp, a raw-history VLM baseline using Gemini 3.7 Flash with the complete observation history and…

arXiv:2609.28767v1 Announce Type: new Abstract: Real-world perception systems must adapt to changing environments, but manual image annotation cannot scale to field data volumes. We present BirdsEye, which shifts expert annotation from images to the field: an operator records target locations in world coordinates using RTK positioning and calibrated projective geometry propagates each observation to all frames where the target is visible. To quantify how well physical annotations align with image observations, we derive a first-order mapping from camera-pose uncertainty to pixel uncertainty and validate it against Monte Carlo simulation. This mapping is linear in the six per-axis pose variances, so it inverts into a sensor design tool: we give a sufficient condition converting an annotati…

arXiv:2609.28766v1 Announce Type: new Abstract: Applying adhesive tape to secure wire harnesses or seal packages requires robots to coordinate a flexible strip, a moving roll, and surfaces that attach and detach. Simulation could make these interactions repeatable for robot development and evaluation, but resolving every adhesive layer is expensive and can suppress roll motion at practical solver tolerances, while a permanently rigid roll cannot release material. We present TapeSim, a tape simulator that concentrates deformation near the unwinding region and along the released strip. We will release the source code. A rigid cluster represents most wound material, while an advancing deformable collar enables payout and leaves released tape flexible and reattachable. Optional releasable bon…

arXiv:2609.28716v1 Announce Type: new Abstract: This paper investigates temporal neural networks for \mbox{end-effector} position \mbox{estimation} of an aerial continuum manipulator (ACM) operating under aerodynamic effects induced by the unmanned aerial vehicle (UAV). An experimental dataset is collected under stationary (\mbox{rotor-off}) and \mbox{free-hovering} conditions across continuum robot (CR) configurations and UAV altitudes, providing \mbox{end-effector} position measurements with and without aerodynamic residuals. To establish a nominal framework, \mbox{strain-parameterized} kinematic models with progressively richer strain bases are evaluated to balance model complexity and prediction accuracy. The selected nominal model then serves as the baseline for 3D position residual…

arXiv:2609.28709v1 Announce Type: new Abstract: Autonomous UAV flight through cluttered and partially unknown environments requires reasoning not only about observed obstacles but also about occluded regions that the sensor cannot observe. We present OA-MPPI, an obstacle- and occlusion-aware extension of Model Predictive Path Integral (MPPI) control for quadrotor flight that accounts for potential moving agents emerging from these regions into the vehicle's path. At every planning step, we extract a 3D occlusion boundary from the online occupancy map and use it to model the regions that hidden agents could reach over the prediction horizon. We penalize trajectories that enter these expanding regions within MPPI rollouts generated using nonlinear quadrotor dynamics and accounting for indiv…

arXiv:2609.28660v1 Announce Type: new Abstract: Human hand-object interactions (HOIs) provide a rich source of demonstrations for dexterous manipulation, but learning directly from them presents challenges in bridging morphology gaps, ensuring dynamical feasibility, and sim-to-real deployment. We present Morphometric Imitation, a three-stage framework that transforms reconstructed HOIs into zero-shot sim-to-real visuomotor policies. First, morphometric optimization (MMO) kinematically retargets human motion across hand morphologies while preserving demonstrated contacts. Second, residual reinforcement learning (RL) refines the kinematic reference using object pose and contact information from the human motion to produce dynamically feasible robot demonstrations. Third, these demonstration…

arXiv:2609.28530v1 Announce Type: new Abstract: A general-purpose vision-language model can understand a task goal without knowing how a particular robot's motion and functional parts produce the intended effect. We introduce KnowBody, a harness that makes these action-relevant body relations explicit, queryable, and revisable while keeping the model weights frozen. Initialized from one off-task trajectory, a partial body model guides action selection and the interpretation of past interactions. New evidence refines the model, and knowledge dependent on revised body estimates is rechecked before reuse. Across 32 fixed-budget trials on four real-robot tasks, initialized KnowBody achieves 75% completion versus 25% for the native harness and requires fewer planner rounds on successful trials…

arXiv:2609.28813v1 Announce Type: new Abstract: Cinematography, the craft of visual storytelling through framing, lighting, and camera operation, fundamentally shapes how audiences perceive and emotionally engage with video content. While Large Vision Language Models (LVLMs) have made remarkable progress in video question answering, existing benchmarks primarily focus on identifying low-level techniques rather than understanding their storytelling impact. To address this, we introduce CinematicVQA, the first-of-its-kind benchmark for cinematic video understanding that goes beyond technique recognition to evaluate film-grammar reasoning, utilizing our introduced Cinematic Scene Graph (CSG), a structured representation that links filming techniques to their perceptual effects and narrative…