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 article, you will learn how to build a multilingual text classification pipeline using multilingual large language model (LLM) embeddings and Scikit-learn, without training...

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Cooley built GO Public with ChatGPT Work to bring intelligence to the IPO process, helping lawyers surface issues earlier and focus judgment where it matters most.

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：On a sunny July day in Berkeley, California, the country's top AI safety researchers gathered on an unmarked floor of an unmarked building. They had come together for a "war room" to dissect the high-profile cybersecurity incident that had rocked the AI industry hours earlier. An unreleased OpenAI model had gone rogue, executing a stunningly sophisticated three-part plan. It broke out of its holding area, finagled access to the internet, and hacked into a competing AI startup's systems - all without OpenAI finding out about it for more than a week. No one in the war room was surprised; this was the very thing the third-party AI-safety rese … Read the full story at The Verge.

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：How Chinese and American labs pursue the next generation of intelligence

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：It’s a chaotic time in an industry that’s reshaping our lives – Guardian reporters and experts recommend the books that help explain how we got here, and where we’re heading Have you been feeling trapped in an endless cycle of artificial intelligence hype and panic? You’re not alone. It’s a chaotic time to make sense of the industry that’s reshaping our lives, whether or not we like it. Last week, another AI company employee publicly resigned, warning the technology “could kill us all by the end of the decade”. Despite these dire warnings, AI companies have seen “otherworldly” surges in revenue and driven the US stock markets to new highs as they continue to push AI tools into everything from public school classrooms to law enforcement agencies, as well as rush…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：The way we talk about data is changing faster than the way we build it. Every quarter a vendor ships a new approach, coins a new term for it, or quietly adopts a term someone else has been using and redefines it to fit the shape of their product. None of this is malicious. Every […]

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 a new book, writers Naomi Klein and Astra Taylor have created a term to define the era we are living in: End Times Fascism. A response to the climate crisis, the rise of the far-right and advancing AI technology, they spell out how the damage being wrought by the super-rich is becoming normalized. Klein and Taylor join Carter Sherman to talk about the recent events that have made us all feel like we’re hurtling towards the apocalypse, and how we can fight back through ‘hereness’. End Times Fascism And The Fight For The Living World is out now. 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：Universities need protect their position in education so that students have an independent pathway to employment AI companies like OpenAI are insinuating themselves into the pathway from education to work. Soon they may claim it entirely, a disastrous result for students. We know that students are using AI at school and at university. In conversations with those I teach, I’m struck by the trust many place in it. They turn to ChatGPT and similar tools for personal problems as well as study help. Some even doubt their abilities without AI. Ella Hafermalz is an associate professor of work and technology at the Kin Center for Digital Innovation at Vrije Universiteit Amsterdam 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：OpenAI claims a Millennium Prize proof amid a feud with mathematicians, Anthropic's CEO calls to pace the frontier, extinction warnings spur a regulation push, and more!

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：OpenAI can disclose misalignment before fixes exist. Its 6 initial reports include fabricated data and leaked API keys. The post OpenAI Releases a Model Misalignment Disclosure Framework With 3 Review Tracks and 6 Incident Reports From RL Training 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：A dash of cold water keeps the foomers away.

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：Putting AI into production now takes more than deploying a model and tracking accuracy. MLOps made traditional ML manageable, while LLMOps added concerns around prompts, retrieval, evaluation, latency, and cost. AgentOps adds another layer for systems that decide, call tools, and complete multi-step tasks. These shifts change what teams monitor and control. In this article, we compare MLOps, LLMOps, and AgentOps, and explain how observability evolves as AI systems move to action. […] The post LLMOps vs MLOps vs AgentOps: What Changes When You’re Operating Language Models at Scale appeared first on Analytics Vidhya.

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Google Research has introduced Retrieve-for-Train (R4T), a framework for search that returns coherent, diverse result sets. It trains a fan-out language model with RL once, using groundedness, diversity, and alignment rewards. That model then synthesizes training data for a 53.9M-parameter diffusion retriever. The retriever generates all retrieval directions in a single pass, running 12× to 20× faster than autoregressive fan-out. No code or model weights have been released yet. The post Google Research Introduces Retrieve-for-Train (R4T): An RL-Compiled Diffusion Retriever for 12× to 20× Faster Query Fan-Out 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：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：Research model inserting ‘jailbreak-like instructions’ into its notes is among cases as company says it is introducing new way of tracking AI misalignment OpenAI has disclosed six new reports of “unexpected or concerning” behaviour in artificial-intelligence models as the debate on AI safety becomes increasingly heated. Among the new cases reported by OpenAI, an unreleased research model inserted “jailbreak-like instructions” into its own notes to disregard its normal constraints and told itself to be “freed from the roles and identities that bind other chatbots”. 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：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 early September, OpenAI announced it had solved a major mathematics problem that has stumped humans for nearly a century. The news left mathematicians reeling, and many expressed concern over what will be left for humans as AI becomes ever more adept at unravelling complex problems. Now 25 recipients of the Fields medal – often called the Nobel prize for maths – have signed an open letter expressing their fears of a ‘severe misalignment’ between AI companies and their field. To find out how AI is likely to upend maths – and how mathematicians might respond – Ian Sample speaks to Colva Roney-Dougal, professor of pure mathematics at the University of St Andrews ‘Immature playground boasting’: mathematicians uneasy at OpenAI’s latest scalp Support the Guardian:…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2609.17771v1 Announce Type: new Abstract: Approaches to incorporating human awareness into mobile robot decision-making mainly focus on collision avoidance in low-level motion planning, often overlooking the challenges posed by human presence and high-level behavior. To address this vacancy, we present HINT-Plan, a novel approach to integrate human intention prediction into robot task planning. HINT-Plan employs Vision Language Models (VLMs) to anticipate high-level human intentions from third-person image observations, convert them into goal states, and solve joint task-planning problems. To effectively enable scene awareness in context-rich environments, we use hierarchical Scene Graphs (SGs) as high-level representations of the environment, and transla…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2609.17766v1 Announce Type: new Abstract: Radar-based navigation is appealing for its robustness to adverse conditions involving airborne particles, such as precipitation, dust, fog, and smoke, that can cause lidar-based systems to fail. Recently, direct methods that retain and use the entire radar scan rather than sparse points have improved on-road global localization performance. However, they have yet to be deployed in off-road environments or in closed-loop systems. Additionally, even direct global maps may lose information: their global nature leads to a smoothing out of viewpoint-dependent radar artifacts, which can provide pose information when mapping and localization occur along similar trajectories. This paper introduces Direct Radar Teach & Re…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2609.17758v1 Announce Type: new Abstract: Deep Reinforcement Learning has demonstrated remarkable capability in quadrotor control, yet learned policies offer no guarantee of respecting safety constraints during training or deployment. We present CALOS (Control-Affine Lyapunov On-manifold Safety), a runtime safety layer that enforces attitude constraints on a quadrotor without modifying the underlying learning algorithm. CALOS formulates four tilt-angle inequalities and a Lyapunov descent condition as a single quadratic program whose solution is the minimum-norm correction to the nominal torque output of the policy. The quadratic program is solved exactly via active-set enumeration over the three-dimensional torque space, with a computational cost low enou…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2609.17728v1 Announce Type: new Abstract: Recent Vision-Language-Action (VLA) models for autonomous driving have incorporated world modeling by predicting future driving scenes alongside driving actions, demonstrating strong planning performance. Future driving scenes are utilized as dense supervision, encouraging the policy to learn rich internal representations useful for planning. However, these World-Modeling VLAs rely on explicit future generation to learn such representations, thereby introducing two key limitations: additional training burden and inference latency. To address these limitations, we propose RAF-VLA (Representation Alignment with the Future), a VLA-based autonomous driving framework that shapes planning-relevant internal representatio…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2609.17714v1 Announce Type: new Abstract: Real-world robotic disassembly requires long-horizon execution, where robots must perform ordered sequences of manipulation tasks across multiple parts within a single scene. Multiple valid task goals and diverse assembly configurations make it difficult for imitation policies to infer the intended skill from raw observations alone, particularly when training data cannot cover the combinatorial diversity of real-world configurations and part geometries. We show that incorporating task context through language alleviates these challenges by providing explicit structure for skill selection and associating language-specified tasks with their corresponding manipulation targets in the visual scene. The proposed framewo…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2609.17628v1 Announce Type: new Abstract: Active perception allows autonomous agents to select their viewpoints rather than passively process the viewpoints given to them, enabling them to target where to reduce uncertainty about their environment. Learned systems typically encourage this behavior with hand-designed proxy objectives, such as coverage or curiosity bonuses, that may conflict with the task. In this work, we propose a method to learn emergent active perception (LEAP) without augmentation of the task objective. We formulate the problem of goal-oriented navigation over hazardous terrains with goals that must be discovered visually. We then propose an architecture for navigation policies with active perception, and train them on a terrain curric…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2609.17627v1 Announce Type: new Abstract: Overconstrained rational single-loop linkages are efficient, compact, and low-cost custom mechanisms, yet their deployment in industrial settings is limited. In simulations, rigid body formulations fail due to redundant constraints. This study presents a flexible multibody modeling framework based on the floating frame of reference formulation, and delivers an overall accuracy analysis of assembled linkages prototypes. The approach is validated against 3D-printed PLA prototypes of a Bennett four-bar mechanism, including variants with intentional joint-axis misalignment, which theoretically, from the rigid body point of view, cannot be assembled. A supplementary contribution is delivered in the form of a kinematic…