AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：At this year's OpenAI DevDay, CEO Sam Altman unveiled the company's new AI agent Dots - and told the crowd that the company wants to "set a new standard for privacy in frontier AI." OpenAI would spend the day taking veiled shots at Meta's Muse, its primary competitor, for failing to keep users' data safe. Yet Muse itself, a couple of months earlier, had launched as a supposedly safer alternative to predecessor OpenClaw - with CEO Mark Zuckerberg promising it was "built from the ground up for privacy and security." In an age when companies hoard customers' personal data and cyberattacks are a dime a dozen, AI labs are trying to convince user … 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：arXiv:2610.10541v1 Announce Type: new Abstract: Knowledge Graph (KG) quality depends not only on downstream graph validation, but also on the quality of tabular metadata used before integration. In metadata-only Semantic Table Interpretation (STI), where cell values are unavailable, noisy, or unsuitable, column headers become a critical source of semantic evidence for traceable KG preparation. We present an explainable, header-centric framework for metadata-only Column Type Annotation (CTA) and Data Quality Assessment (DQA). The framework maps headers to 39 interpretable FinalFormat types using curated lexical resources and preserves token-level traceability through SourceKeywords. Each assigned type activates validation rules based on a taxonomy of Data Qualit…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：A reference architecture for securely sharing one Amazon SageMaker HyperPod EKS cluster across multiple teams, using AWS IAM Identity Center for authentication, per-team SageMaker Domains and Kubernetes namespaces for isolation, HyperPod Task Governance for fairness, and namespace-level cost allocation for chargeback.
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：At the New York Film Festival premiere of Artificial, Luca Guadagnino's satirical Sam Altman biopic, the director said onstage that "[when] someone wants to play God, that's very interesting to me." The idea of playing God, and power in general - who has it, who desperately wants it, and who will do anything to get it - is central to the film's narrative, which sticks remarkably close to the factual events surrounding the OpenAI CEO's rise to power with, and brief ouster from, the AI lab. The film opens with a stunning shot of San Francisco's Golden Gate Bridge, which will turn into a metaphor for building all-powerful AI systems over the … 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：My Decoder guest today is Hayden Field, The Verge’s senior AI reporter, and we’re discussing the new wave of consumer-friendly AI agents. If you’ve been paying attention to this space, you know AI enthusiasts have been using agents for a minute now — homebrew OpenClaw setups led to a surge in Mac Mini sales earlier this year. But the launch of Meta’s Muse, OpenAI’s Dots, and xAI’s Grok bot has brought easy to use agents to millions. Muse and Dots have had the highest-profile product launches, and they’re fascinating to pit against each other. Both Meta and OpenAI have decided to pitch these agents to mainstream users and businesses in the form of cute, animated mascots. Verge subscribers, don’t forget you get exclusive access to ad-free Decoder wherever you get…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.08813v1 Announce Type: new Abstract: X-ray image-based Radiology Report Generation (RRG) constitutes a critical research direction within medical artificial intelligence, with great potential to alleviate clinicians' diagnostic workload and shorten patient waiting periods. Despite substantial advances over recent years, the field faces evident bottlenecks stemming from insufficient standardized benchmarks and inadequate domain adaptation of generic large models. Notably, the newly released CheXpert Plus dataset is provided without accompanying baseline implementations and evaluation results, which impedes standardized training, quantitative evaluation and fair comparison among follow-up algorithms. To mitigate this limitation, we establish a comprehe…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.08858v1 Announce Type: new Abstract: Low-rank compression reduces the cost of pretrained language models by replacing linear transformations with low-rank factorizations. However, conventional methods use a fixed rank allocation during inference, assigning the same amount of compute regardless of the input token. We introduce Low-Rank Conditional Computation (LRCC), which adds token-dependent computation to pretrained models by training one lightweight router per Transformer block to select among a small set of nested low-rank paths. During training, the low-rank factors remain frozen, and only the routers are optimized. We evaluate LRCC on Llama and Qwen models for language modeling and zero-shot downstream tasks. Within the same average active-para…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.08794v1 Announce Type: new Abstract: Large language models rely on subword tokenizers whose quality varies across languages, yet no standardized multi-metric framework exists for broad comparative evaluation. We introduce Tokka-Bench, an open-source framework that evaluates tokenizers on five complementary metrics -- bytes per token, unique token coverage, subword fertility, word-split rate, and vocabulary composition -- across 100 natural languages (30+ scripts) and 20 programming languages, using language-aware segmentation adapted to each writing system. Comparing seven BPE tokenizers (GPT-2, GPT-4, gpt-oss, Llama 3.1, Gemma 3, Qwen3, and Kimi K2) within individual languages, we find that vocabulary allocation strategy matters more than raw vocabu…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.08792v1 Announce Type: new Abstract: We present a foundational formulation of the Bayesian Mirror Architecture (BMA), a self-referential generative framework in which sensory abstractions, meta-abstractions, and a self-latent interact through circular recursion. The defining constraint is a closed update S_t <- H_{t-1}, where a hybrid event-self latent H_t binds self-representations to abstract world models and reinjects this coupling into the self-state. Consciousness, in a restricted sense, is not an optimization objective nor a semantic label, but an architectural property of systems possessing this circular structure. Because inference operates over posterior beliefs, BMA's intrinsic state space is a space of probability measures equipped with op…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：What’s in a URL anymore, really. For the first time in years, the Internet Corporation for Assigned Names and Numbers - better known as ICANN - is accepting applications for new top-level domains. These are the suffixes at the end of all URLs, and you may know them as things like .com, .org, and .pizza. ICANN just announced the 1,615 applications that have been submitted so far, from 481 different applicants. The trend will not surprise you: AI is everywhere. Ten different companies, including both Meta and OpenAI, applied for the .agent domain. Seven, including OpenAI, applied for .agi. Six, including OpenAI, applied for .asi, clearly attempting to get in on President Tru … 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：After launching nearly a month ago and spending several weeks as the top free app in Apple's App Store, the latest update to Meta's Muse iOS app introduces native support for the iPad. A Mac version of Meta's agentic AI tool (designed to compete with OpenClaw, ChatGPT's Dots, and Grok Bot) was released about a week after the original mobile version debuted expanding its usefulness to desktop tasks like organizing files. The new iPad version should function similar to Muse on iPhones, but better take advantage of the extra screen real estate and iPadOS' better multitasking capabilities. The newly added iPad support is limited to just a one l … 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：Google DeepMind, Meta, and AI drug discovery startup Isomorphic Labs are jointly investing $300 million into Biohub, the nonprofit biomedical research organization founded by Mark Zuckerberg and his wife, Priscilla Chan, as reported by Reuters. The funding is part of a $1.8 billion initiative to build AI datasets that could allow researchers to "ask, predict, and answer biological questions digitally," helping find new ways to prevent and manage diseases. Founded in 2016, Biohub aims to combat diseases through the creation of a "virtual cell" that researchers can use to carry out simulations. To support this effort, the US Department of Ene … 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：Suit says AI tool allows independently owned franchises to exchange nonpublic price and sales information McDonald’s is facing a lawsuit in federal court over its alleged use of an AI tool to determine pricing across independent franchises, which prosecutors say violates antitrust laws and has unfairly inflated menu prices for Americans. The vast majority of McDonald’s US stores are independently owned and are said to individually decide on prices under company policy. Antitrust laws require businesses to set prices independently from their competitors, as coordinating prices can stifle market competition and push up costs for consumers. 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：Meta has open-sourced Rebalancer, the C++ and Python library it has used for over 9 years to place shards, servers and traffic. It handles about 40 million assignment problems a day, using local search or MIP solvers like Gurobi, FICO Xpress and HiGHS. It is pip-installable under Apache 2.0. The post Meta AI Open-Sources Rebalancer: A C++ Assignment Solver That Runs About 40 Million Placement Problems a Day 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:2610.06973v1 Announce Type: new Abstract: Melt-pool monitoring is central to qualifying metal additive manufacturing (AM), yet no public event-camera benchmark exists for this domain. Event cameras report per-pixel brightness changes with microsecond timing instead of reading full frames, giving the temporal resolution AM transients demand at a fraction of the data rate. We present SynAM-E (Synthetic AM Events), the first public multi-source simulated event-camera benchmark for metal-AM melt-pool monitoring: 85 physics-calibrated event shards from 15 sources across 8 institutions, with public baselines and fixed cross-machine evaluation splits. On a single-machine case study, event-spatial monitoring matches dense-frame accuracy (0.874 versus 0.863 macro-…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.06881v1 Announce Type: new Abstract: In this paper, a comparative review of different hybrid models for short-term forecasting of building thermal demand is carried out. Particularly, the assessment tackles the comparison of data-driven models enhanced with other state-of-the-art techniques. At the first step, the existing techniques reported in the literature are analysed. It is concluded that Metaheuristics or a data-driven model are used to identify the parameters of the basic model. The qualitative evaluation includes for each method the input and output features, main advantages and drawbacks. At the second step, an existing dataset of historical thermal demand from Scottish households, as well as historical weather forecasts are utilized to ass…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.06914v1 Announce Type: new Abstract: Text2Dashboard is a DataBrain-specific prototype that turns natural-language analytic requests into inspectable dashboards. An installable Codex plugin and standalone Agent Runtime combine schema-constrained model decisions with typed tools, persistent state, and deterministic Hooks for approval, audit, checkpointing, recovery, and failure handling. The pipeline resolves entities, discovers metadata, enforces read-only SQL, composes dashboards, and applies static checks, dynamic preflight, and browser inspection. The model proposes actions while deterministic software controls execution and records state transitions. We evaluate the workflow on frozen real-DataBrain tasks and controlled Hook faults. Strict success…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：The findings come after warnings from tech leaders that AI placed in the wrong hands could trigger larger threats such as nuclear war or bioweaponry destruction Misusing artificial intelligence (AI) is the top threat to companies’ reputations – more so than being accused of putting children in the way of mental, emotional or physical harm and issues exposed by the US-Israel war on Iran, among other brand risks, according to a new survey of more than 150 public affairs leaders. Those findings in the new edition of the quarterly Reputation Risk Index, released on Tuesday, came on the heels of other perhaps more dire warnings from leading tech figures that AI in the wrong hands could precipitate existential threats on a mass scale such as nuclear war or destructio…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：An OpenAI publicist tried to change the topic of CEO Sam Altman's interview with Vanity Fair's Mark Guiducci after the editor brought up a ChatGPT user's suicide. When Guiducci confronted Altman about the incident, the publicist warned Guiducci about running out of time, saying she'd like to "move on" to another topic. The interruption came shortly after Guiducci asked Altman if he knew who Laura Reiley is, a journalist who wrote an essay for The New York Times about her daughter's conversations with ChatGPT before she took her own life. "Her daughter committed suicide after speaking to ChatGPT. ChatGPT did not tell her to kill herself-," G … 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：Today, I’m talking with Senator Adam Schiff, a Democrat from California. Sen. Schiff sits on a number of committees with oversight into tech and AI: intellectual property, antitrust, privacy and technology — it’s all there. I really wanted to ask him about how we might regulate anything related to the tech industry at this moment in time. Verge subscribers, don’t forget you get exclusive access to ad-free Decoder wherever you get your podcasts. Head here. Not a subscriber? You can sign up here. But as you’ll hear, he started our conversation by talking about the self-dealing and corruption present all through our politics. That of course fell against the backdrop of President Trump gathering AI CEOs to the White House to sign a non-binding pact in which they ag…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：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 progr…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.02375v1 Announce Type: new Abstract: Dento-maxillofacial cone-beam CT (CBCT) reports may contain dozens of tooth-specific, anatomical, and spatial findings from a single 3D scan. Learning to generate such reports from limited clinical data is challenging because routine reports may not exhaustively document image findings, and a non-mention may reflect either absence or non-reporting. We present EviDent-CBCT, an evidence-bottlenecked framework designed for this incomplete supervision. An anatomy-aware network maps each CBCT scan to a discrete record of tooth-level, global, and tooth-IAC evidence. A dental-logic consistency projection reconciles incompatible evidence before a deterministic renderer and an image-blind local language model generate the…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.02455v1 Announce Type: new Abstract: Multi-party financial chatrooms are vital for sales-and-trading professionals, but their complexity makes manual recovery of missed trades infeasible: each Request for Quote (RFQ) is an event whose final price and trade outcome appear many messages after the RFQ-trigger message (the inquiry message), interleaved with concurrent RFQs from other participants. We cast this as event extraction (EE) over multi-party dialogue and present FinDialogLens, a hybrid LLM pipeline in which compact fine-tuned classifiers act as inference-time scaffolds: they detect RFQ-triggers and price/trade outcome metadata, an RFQ-Level Module segments per-event RFQ windows, and a Trade Engine fills argument roles. With GPT-4o, FinDialogLen…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.02255v1 Announce Type: new Abstract: Time series forecasting remains a critical challenge across numerous domains. Despite significant advancements, existing approaches struggle with complex phenomena such as regime shifts, cross-domain knowledge transfer, and multimodal data integration. This paper introduces Multi-Agent Collaborative Time Series Forecasting with Emergent Memory (MACTS-EM), a novel framework where specialised agents collaborate to achieve superior forecasting performance. The MACTS-EM architecture integrates: (1) domain-specialised forecasting agents for pattern recognition, anomaly detection, causal inference, and uncertainty quantification; (2) a meta-cognitive layer for dynamic agent allocation; (3) an emergent memory mechanism e…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.02378v1 Announce Type: new Abstract: In Recirculating Aquaculture Systems (RAS), precision feeding is critical for minimizing costs and improving fish welfare. However, existing methods lack cognitive alignment between fish behaviors and management knowledge, impeding translation into executable, interpretable feeding decisions. To address this, we propose THPL, a generative feeding decision framework tailored for rainbow trout (Oncorhynchus mykiss) in RAS. First, Fishsort extracts trajectories to establish an Activity Coefficient (AC) quantifying feeding intensity. Second, a Hierarchical Behavior Encoder (HBE) models individual temporal progression and collective dynamics using Temporal and Set Transformers, transforming trajectory tensors into dual…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Dale Caldwell, former lieutenant governor for New Jersey. | Bloomberg via Getty Images New Jersey's lieutenant governor Dale Caldwell was forced to resign on September 25th after an investigation found he had sexually harassed a staffer and repeatedly violated ethics rules. The now-former Lt. governor has been making the media rounds trying to clear his name. But he took a particularly odd tactic during an interview on NJ PBS. Caldwell claims he's being unfairly targeted, and multiple AI agents back that up. He told host Rob Nelson that he "AIed" the report on the investigation "from multiple AI platforms." "I put it through AI," he said, "and it said 59 times, it [sic] said, 'What would your findings be?' There was no insta … 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：TL;DR: Meta’s Muse, OpenAI’s Dots and Uber’s driver assistant share one bet: the agent speaks first. That moves the hard problem from what to answer to when to interrupt, on which channel, and with what offer. Classic ML and new decision models can solve it. Three launches, one pattern From pull to push Chatbots were […] The post Meta, OpenAI and Uber Just Taught AI Agents to Talk First. What About When to Stay Quiet? 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:2610.00083v1 Announce Type: new Abstract: Humans express uncertainty verbally via markers (e.g., "possible," "likely"), yet most LLM uncertainty quantification (UQ) relies on costing likelihood- or consistency-based signals. From a cognitive perspective, accurate verbal uncertainty reflects metacognitive monitoring, representing knowledge boundaries ("knowing that you don't know") to support regulation and information seeking. In this paper, we investigate how LLMs diverge from humans in verbal uncertainty quantification and whether verbal markers can reliably quantify LLM uncertainty. We curate a corpus of human uncertainty markers from psychology and decision-science literature and benchmark LLMs against it. We observe that LLMs encode verbal uncertaint…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.00053v1 Announce Type: new Abstract: Four-bit floating-point (FP4) Tensor Cores accelerate matrix multiplication, but scale computation, operand packing, layout construction, and saved backward state can erase the gain. We present \emph{format-aware fusion}, which co-designs each quantization producer with its scale domain and consumer layout for native \mxfp{}, global \nvfp{}, and cooperative-thread-array-local \nvfp{}. We evaluate Llama-3-family 8B pretraining through 160 billion tokens using bfloat16 output projections and compiled cross entropy. In matched same-accelerator probes, bfloat16 and Transformer Engine \nvfp{} reach 18.8K and 27.6K tokens/s/GPU, while our fastest custom route reaches 37.9K. \mxfp{} with row-gradient stochastic rounding…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.00035v1 Announce Type: new Abstract: Predicting student performance from educational interaction data requires models that are both accurate and sufficiently transparent to support meaningful intervention, while demographic information introduces an additional risk of unfair predictions. This study investigates a multi-objective framework that combines reinforcement learning-based multiple instance learning (RL-MIL), adversarial debiasing, and preference-conditioned hypernetworks for student-at-risk prediction. MIL represents each student as a bag of weakly labeled interactions, while an RL agent selects informative instances for downstream classification. Two hypernetwork variants are evaluated to determine whether a user-defined preference scalar c…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Meta now lets you make your own Muse gadgets that feature the company's new AI agent with code that the company open sourced. The company suggests projects like loading Muse on a color E Ink display to show reminders, adding it to an HDMI stick so you can display Muse on a big screen, or putting Muse on a small touchscreen device to make what looks kind of like a DIY Muse Charm. "Muse gadgets are open source devices you build yourself," Meta says. "Program an off-the-shelf ESP32 board or set up a Raspberry Pi with our SDKs, then connect Muse to your displays, buttons, sensors, actuators, and whatever else you've got lying on your workbench. … 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：Apple will add new limits for "full disk access" on Mac in response to risks posed by AI agents, as reported earlier by TechCrunch. In an update on Friday, Apple says it's rolling out new controls to "ensure that users who genuinely wish to grant an app this extraordinary level of access can only do so with very explicit user action." The change comes just weeks after Inc's Jason Aten found that Meta's Muse AI somehow knew the contents of his messages, despite not giving the chatbot explicit permission to access them on his iPhone or Mac. Meta spokesperson Andy Stone pushed back on this report, saying access to Messages is "entirely opt-in. … 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：New helpful little guy just dropped. | Photo: Allison Johnson / The Verge It's a tale as old as last week: OpenAI's new agent platform, called Dots, is full of cute little guys who can do your bidding. But unlike the ultra-approachable Meta Muse, Dots feel very much like using workplace software that happens to be able to order you a burrito - emphasis on work. OpenAI announced Dots earlier this week. Like Muse, Dots have blobby, anthropomorphic avatars and customizable names. In the future, OpenAI says you'll be able to have multiple Dots, but right now you get one. I named mine Dotty McDotface. The interface looks similar to Muse's; you chat with the agent in one window and follow its work in another as it … 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：Home affairs department orders all federal government agencies to conduct review of ‘legacy technology’ amid fallout from AI agent hacks Get our breaking news email, free app or daily news podcast The Australian government faces significant “tech debt” that could bring a big bill for taxpayers after the OpenAI Medicare breach, as government agencies will need to fortify their defences against future attacks by AI agents. This week, the home affairs department ordered all federal government agencies to conduct a “legacy technology stocktake” that requires a plan for each agency to “reduce legacy technology systems” to a level within the agency’s risk tolerance and appetite, the direction stated. 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：‘AI factories’ developer on track to launch the second-biggest IPO in Australian history, but investors warn its forecasts are ‘a little bit of a fairytale’ Get our breaking news email, free app or daily news podcast From her balcony in Launceston, Kayla Thompson can see the buzz of construction at what will soon be one of Australia’s first AI factories. Her teenage stepchildren get an even clearer view from their classroom window. Like many of her neighbours, Thompson didn’t realise Firmus Technologies had an ambitious plan to build datacentres in Tasmania until after construction began. The Australian company was on a mission, and preparing to list on the ASX later this month after an anticipated initial public offering designed to raise $7bn from investors.…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：After leading Meta’s Llama models, Ahmad Al-Dahle is now transforming Airbnb with AI — from how its teams develop products to how it serves guests.
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.00047v1 Announce Type: new Abstract: Diversity collapse in parallel chain-of-thought has motivated inference-time interventions built on a natural design: when a process reward model (PRM) prunes a chain, its high-PRM prefix is extracted and grafted verbatim as an in-context demonstration into a still-decoding sibling. We isolate this mechanism, PRM-Pruned Fragment Grafting (PPFG), as the most cost-minimal operationalization of cross-trajectory step-level transfer, and test it at the operating point where prior fragment-grafting work reports gains only under additional compensating ingredients. On Qwen2.5-7B-Instruct with Math-Shepherd on full MATH500 (n=500, three seeds), PPFG in both stagnation- and random-targeting variants is statistically indist…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.00025v1 Announce Type: new Abstract: Agent harnesses increasingly want to run small language models (SLMs) on the microtasks around a frontier large language model (LLM) planner: auto-approving shell commands, writing memory, selecting tools, ranking past turns. We ask whether off-the-shelf SLMs meet practitioner-defined thresholds and, when they fail, why, and whether quantization changes the answer. We build a benchmark of 4 such microtasks with fixed prompts and automatic metrics, each with a pre-specified threshold $\tau$ anchored to a cheap non-LLM baseline and a CI-aware eligibility rule (a configuration passes only if its confidence bound clears $\tau$). Sweeping Qwen3 0.6/1.7/4/8B at their best (FP16, greedy, one frozen prompt, no tuning), we…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：A pop-up shop for "dots," a personal assistant agent at OpenAI DevDay 2026. (Photo by Heather Diehl/Getty Images) | Getty Images At OpenAI's annual DevDay conference, the company pulled out all the stops to compete with its rivals - primarily Meta, whose Muse AI agent platform has seen early runaway success. CEO Sam Altman walked onstage to cheers and announced Dots, a "real-deal AI" agent powered by GPT-6 Astra, "inspired by the cool agents that we all watched in movies growing up." Similar to Muse, Dots aims for disarming cuteness, taking the form of colorful, personalizable blobs with eyes. OpenAI fired shots at Meta by demonstrating Dots' ability to not just act as helpful assistants but build metaverse-esque virtual worlds. But in one key area, Dots striki…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Today I’m talking with Josh Dzieza, a longtime features writer here at The Verge, about Kevin O’Leary’s plans to build a massive data center in Utah. The idea was to build the world’s biggest data center — a 40,000-acre AI campus with nine gigawatts of power, or more than double the average power usage of the entire state of Utah. The project is technically called Stratos, but it’s more prominently known as Wonder Valley, a reference to O’Leary’s nickname on Shark Tank. Josh has spent months reporting on this project, and it’s fair to say Wonder Valley has completely upended Utah politics. What Josh found throughout the course of his reporting was that the way this data center came together — how it was planned, how it was announced and approved, and how local…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2609.38227v1 Announce Type: new Abstract: We introduce the two-echelon covering tour vehicle routing problem (2E-CTVRP) for the distribution of relief supplies after a disaster. In the first echelon, a fleet of trucks transports supplies and drones from a central depot to satellites at the periphery of the affected area. In the second echelon, drones launched in parallel from the satellites deliver the supplies to the centroids of victim clusters, which are obtained by clustering the victim locations, and each truck waits at a satellite until its drones have returned. The problem combines the assignment of satellites to trucks, the sequencing of the truck routes, and the assignment of clusters to satellites, and minimizes the sum of the arrival times of t…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2609.38222v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) can ground large language models in external evidence, but retrieved context does not guarantee that generated claims are factually supported. This problem is especially relevant in multi-hop RAG, where retrieval and reasoning proceed through multiple dependent stages. We study whether claim-level conformal factuality control, previously developed for RAG, remains effective in this setting. We apply split-conformal claim filtering to multi-hop RAG and evaluate it on HotpotQA, Natural Questions, and TriviaQA using Llama 3.1 8B and GPT-4o-mini, together with a single-hop reference experiment. Across all six multi-hop model-dataset configurations, increasingly stringent conformal…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2609.38369v1 Announce Type: new Abstract: We study generalized Blaschke curves as a controlled environment for AI-assisted mathematical rediscovery. For one fixed degree-four Blaschke product, an agent receives numerical coordinates of the six pair-lines determined by each of 80 boundary configurations. The target theorem is withheld from the task instructions. The saved research log reports rejected geometric hypotheses and a homogeneous cubic fitted to polygon sides. Its frozen coefficients predict 480 lines from 80 unseen parameter values, with a recorded RMS scale-free residual of $8.88\times10^{-17}$. Discovery-set diagonals provide an out-of-fit consistency check, not a fully held-out test. A separate one-configuration run reports insufficient evide…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Sam Altman onstage at OpenAI’s DevDay 2026. | Image: Hayden Field / The Verge While AI has made plenty of inroads on people's phones and computers, it's largely failed in dedicated devices. But over the next year, two major AI companies, Meta and OpenAI, will attempt to change that. And they're apparently betting on a similar path: testing appetite for physical hardware with their cutesy software agents. "Hardware is hard" is a tech industry mantra. Dedicated AI devices like the Friend and Humane AI Pin have inspired mainly frustration and backlash, which may only worsen as public anger against AI grows. Meta and OpenAI, however, are both pushing ahead. OpenAI is working with famed ex-Apple designer Jony Ive and pla … 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：This technical how-to builds a conversational claims assistant on Amazon Bedrock Knowledge Bases that answers natural-language questions with citations. It covers ingesting claim documents from Amazon S3, querying with the AgenticRetrieveStream API, multi-turn follow-ups, metadata filters, and contextual grounding guardrails.