AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Trump and Republicans want companies to regulate themselves. It’s a dereliction of duty that will make AI less safe It is hard to get Sam Altman, Elon Musk and Dario Amodei to agree on much. But over the weekend, all three AI company CEOs called for AI development to slow down in the face of growing, alarming risks. Their employees are sounding the siren too, with one researcher publicly quitting and accusing OpenAI and Anthropic of “gambling with our lives”. The combination of dire warnings from insiders and growing real-world evidence of rogue AIs should, in a sane world, lead to government action. Instead, Donald Trump and the Republican leadership have their heads in the sand. Continue reading...

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Discussion | Link

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Artificial intelligence is not replacing the player, coach or analyst, but it is certainly allowing them to do more Daniel Kokotajlo, a former researcher at OpenAI, warned last week that it was possible we would end up “creating a new species that ends up ruling the world”. Once the initial shock wore off, and I’d considered what this could mean for my young children and the future of the planet, another thought popped into my head: will this new species be able to swing an old cricket ball or navigate a seaming green top? It sounds frivolous. It is frivolous. But the question is not quite as ridiculous as it first appears. Continue reading...

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：The stark reality is this: we don’t know how to maintain control of these systems. But there are actions we can take With Jacob Coxon’s resignation from Anthropic, we have reached the AI risk tipping point. Millions of people are finally coming to understand what experts have known for years: AI companies have been gambling with all of our lives, and the odds are not good. In response, the Anthropic CEO, Dario Amodei, has introduced a proposal for “pacing the frontier”, endorsed by Sam Altman and Elon Musk. Can we breathe a sigh of relief? Are we about to step back from the edge of extinction? Amodei envisions a slowdown of one to two years, resulting in “profound progress” on technical safety measures. But that’s not what humanity needs right now. What we need…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：New OpenAI Economic Research shows how workers use AI beyond traditional roles and which new activities become recurring parts of their work.

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Discussion | Link

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Discussion | Link

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Discussion | Link

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Discussion | Link

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：In this episode of Guardian Australia’s weekly US politics podcast, co-hosts Jonathan Yerushalmy and Reged Ahmad look at whether there is any appetite across the political spectrum to put guardrails on artificial intelligence as around the world existential fears mount that the technology is developing too quickly. They also explain what the latest supreme court ruling on the Trump administration’s mail-in ballot restrictions means for the midterms. And they look at what happened when the US president waded into the Irish reunification debate Read more: Trump facing AI backlash in Congress as push for guardrails intensifies John Crace: AI on course to kill us all within 10 years? Donald Trump says: ‘Hold my Coke’ Continue reading...

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Prior Labs released TabPFN-3.5, a tabular foundation model pretrained only on synthetic data that beats Otto's winning solution. The post Prior Labs Releases TabPFN-3.5: A Tabular Foundation Model That Beats the Winning Otto Kaggle Solution With Default Settings appeared first on MarkTechPost.

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Is AI going rogue the worst that could happen? Maybe not … Sign up here to get an email whenever First Dog cartoons are published Get all your needs met at the First Dog shop if what you need is First Dog merchandise and prints Continue reading...

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Discussion | Link

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：In today’s newsletter: It is hard to tell fact from fiction when it comes to AI. What is really going on – and what should the government do about it? Good morning. As a general rule, it pays to be suspicious of any gigantic company that claims it’s developing a tool capable of destroying humanity. But in recent days, a number of warnings from the AI industry have suggested that even tech insiders are starting to worry about what they have unleashed. In a lofty essay published on Saturday, Dario Amodei, the founder of Anthropic (the company behind Claude), argued that tech companies need to “slow” the pace at which they’re developing the newest and most sophisticated AI models. Lucy Letby | Three babies might have survived if hospital had acted upon concerns ov…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Premier David Crisafulli has described the deal as a ‘major win’ that will deliver more jobs for the state AI giant Anthropic, the developer behind large language model Claude, has done a deal to lease its first Australian datacentre in western Queensland. Premier David Crisafulli announced the decision in parliament on Wednesday. Continue reading...

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Air pollution is a serious public health risk, contributing to an estimated 30,000 deaths in the U.K. alone last year. Data-driven insights can help — but computing air quality with traditional chemistry-based models is expensive, which limits how detailed they can be and how regularly they can be run. David Topping, a professor in the […]

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Nums AI has released Causilo, a pretrained tabular foundation model for classification and regression with a scikit-learn interface. It posts the top TabArena Elo among single models, ahead of Google's TabFM and LG's EXAONE Tabular. The code is Apache-2.0, while weights are licensed for non-commercial research. The post Nums AI Releases Causilo: A Tabular Foundation Model That Tops TabArena Among Single Models appeared first on MarkTechPost.

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2609.16346v1 Announce Type: new Abstract: This paper presents Auto-HSI, a method for generating personalized human-swarm interaction (HSI) interfaces on demand. The objective is to enable untrained operators to use natural language descriptions and gesture demonstrations to explain how they want the robots to collectively behave in response to their gestures. Based on these inputs, the code should automatically be generated for personalized state machines that will control the robots as desired, in response to the desired gesture inputs. In the developed Auto-HSI prototype, the generated code produces a personalized interface for centralized control using one- and two-handed gestures, enabling a user to teleoperate the robots' motion, formation shape, and…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2609.16331v1 Announce Type: new Abstract: We present ManiSkillFormer, a neuro-symbolic framework for demonstration-free and compositional robotic manipulation. Instead of learning end-to-end visuomotor policies, ManiSkillFormer introduces task-conditioned geometric contracts that explicitly structure the interface between perception and action. Each manipulation skill declares the semantic geometric primitives required for execution, such as object keypoints and surface normals. Building on human-defined skill structures, LLM agents generate these contracts and corresponding motion templates for different objects and task contexts. These contracts guide the perception module to ground task-relevant 3D primitives from observations, which are then used to i…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2609.16319v1 Announce Type: new Abstract: Dexterous grasping is usually conducted for specific tasks, leading to heterogeneous constraints such as specific approach directions, desired contact regions, specified wrist trajectories, and functional hand poses. Our previous work, GraspXL, achieves scalable grasping motion synthesis for diverse objects and hand morphologies, while lacking controllability for synthesis under such various task-driven constraints. In this paper, we propose ConGraspXL, which extends GraspXL with controllable constraint-conditioned grasp motion synthesis that accommodates diverse task-driven constraints and their combinations. We introduce a hierarchical constraint formulation, enable flexible constraint composition with a masked…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2609.16256v1 Announce Type: new Abstract: Continuum robots enable smooth shape morphing and safe interaction in confined environments. However, most existing systems are task-specific and depend on external sensing infrastructure, limiting their adaptability and real-world deployment. This paper presents a self-contained modular continuum robotic platform that combines mechanical reconfigurability with onboard pose estimation. The robot is constructed from interchangeable continuum joints with analytically precomputed stiffness, allowing rapid assembly and direct programming of the robot shape. Proprioceptive sensing is achieved using magnetic sensors and a modular learning-based framework, where a single model is trained per joint and reused across confi…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2609.16186v1 Announce Type: new Abstract: Autonomous soft-tissue cancer surgery has been limited to interventions on organ surfaces, because current systems cannot perceive and adapt to anatomy once it deforms or is cut. We introduce the first vision-guided autonomous system capable of performing complete tumor resections for partial nephrectomy. Our system integrates conditional occupancy networks, trained entirely in a physics-based simulation, that infer full 3-D anatomy (tumor, margin tissue, and kidney) from single-view partial point clouds. These occupancy networks maintain intraoperative tracking even as tissue is cut and deformed, enabling adaptive planning and execution. The surgical platform combines a depth camera for capturing surface point cl…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2609.16089v1 Announce Type: new Abstract: Structured spatial data require quantum encodings that preserve geometric relations, expose measurable observables, and remain implementable on finite-depth hardware. This work introduces a quantum representation and circuit architecture for rigid-body transformations and specializes it to Denavit--Hartenberg kinematics of serial open-chain manipulators. Each translational contribution is factorized into a classical metric magnitude and a signed unit direction encoded by a single-qubit Bloch vector, while parameterized rotations reproduce the ordered propagation of frame directions. A selector register prepares probabilities proportional to the contribution magnitudes, and the reduced state of a designated readout…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2609.16075v1 Announce Type: new Abstract: Flexible robotic production requires joint decisions on process progression, material routing, resource assignment, temporary cooperation, and simultaneous execution, since each decision can affect the feasibility of the others. The challenge is greater under decentralized control, where each robot acts from bounded local information while system progress depends on collective decisions, shared resources, material state, and workspace compatibility. These properties closely match cooperative multi-agent decision making under partial observability and resource contention. This paper introduces AssemblyGrid v1, a reproducible benchmark for repeated multi-robot production that combines explicit process progression, d…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2609.16074v1 Announce Type: new Abstract: Robots operating in open environments act under partial observability, physical constraints, and dynamic task contexts. Beyond mapping observations and language instructions to actions, they must anticipate how candidate actions may affect future states and task-relevant outcomes. Recent advances in world models, video generation, and Vision-Language-Action (VLA) policies have motivated the development of World-Action Models (WAMs), which couple future world prediction with executable action generation. This survey provides a robotics-oriented review of WAMs. We clarify their scope relative to conventional world models, model-based reinforcement learning, action-conditioned video generation, and reactive VLA polic…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2609.16041v1 Announce Type: new Abstract: Visual torque feedback supports underwater bilateral teleoperation, but the benefit of mixed reality (MR) over conventional monitor presentation remains unclear. We present MR-GLi, an MR interface that spatially registers a reaction torque indicator and wrist-camera image to the robot gripper. Twenty participants performed lift and pick-and-place tasks with rigid and compliant objects in a counterbalanced within-subject comparison with a 2D monitor, using identical visual-feedback content and four-channel bilateral control. MR-GLi provided gripper-linked access to visual feedback while maintaining a similar level of torque-regulation performance to the 2D monitor. Subjective evaluation further indicated reduced pe…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2609.16040v1 Announce Type: new Abstract: Bilateral control-based imitation learning captures both position and force information, making it well suited to contact-rich manipulation. However, existing approaches provide limited means for an operator to specify how a learned task should be executed at inference time, such as slowly or quickly, gently or firmly. We propose Bi-MoDe, a modifier-conditioned decoding framework that injects a constrained latent into every layer of the Transformer action decoder via adaLN-Zero, allowing behavioral directives to directly influence action-chunk generation. We evaluate the method on a real-world whiteboard wiping task with combinations of temporal and physical modifiers. Bi-MoDe improves physical directive following…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2609.16464v1 Announce Type: new Abstract: The clinical management of autism spectrum disorder (ASD) faces a bottleneck in early screening, mainly because trained specialists are scarce and conventional assessment tools are subjective. Here, we introduce ASDchat, a multimodal large language model designed for evidence-based ASD screening, which takes video, audio, and dialogue as input. ASDchat adopts a dual-branch architecture, where the decision branch generates screening probabilities and the evidence branch generates traceable, timestamped behavioral evidence aligned with standardized clinical criteria (ADOS-2). The model was trained and evaluated on a dataset of 1,035 participants from 27 sites in China, which covered typically developing (TD) childre…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2609.16448v1 Announce Type: new Abstract: Breast histopathology analysis increasingly relies on distributed learning because direct data pooling across institutions is often restricted by privacy, governance, and communication constraints. This study compares server-based Federated Averaging (FedAvg), fully decentralized gossip learning, and Hybrid Gossip-FedAvg for invasive ductal carcinoma (IDC) patch classification. Experiments used 277,524 color image patches with patient-disjoint training, validation, and test partitions and a workload-balanced, Dirichlet-guided allocation across six nodes. Ring, random degree-3, and fully connected gossip topologies were evaluated together with sensitivity analyses for statistical heterogeneity, mixing coefficient,…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2609.16409v1 Announce Type: new Abstract: Chain-of-thought reasoning has revolutionized natural language processing by enabling large language models (LLMs) to decompose problems into intermediate steps before answering. Yet confining reasoning to the textual domain presents limitations for tasks requiring direct manipulation of visual representations. Recent efforts augment multimodal LLMs with external visual expert tools such as depth estimation or object detection modules, but these remain fundamentally limited by their reliance on narrow, rigid operations that cannot flexibly generate or transform visual content. We propose ReImaGin, which leverages image generation models as a flexible visual reasoning mechanism for multimodal LLMs: unlike fixed-fun…