AI 行业资讯，
紧跟前沿
每日自动聚合海内外 AI 资讯源与 arXiv 前沿研究，点击标题跳转原文。
OpenAI acquires Odessia, travel startup created by Sonder founder
OpenAI has not yet said what its plans are for the future of travel. But Sonder founder Francis Davidson is a well-known figure in the travel industry.
OpenAI, Anthropic face new oversight as New York’s AI safety law takes effect
New York is preparing to enforce its sweeping AI safety law, requiring major developers like OpenAI and Anthropic to register, disclose safety practices, and report critical incidents or face fines.
All 7 Anthropic founders will each cash out about $250M in IPO
Each of the seven co-founders plans to sell exactly the same number of shares in the IPO, which would bring each of them about $250 million in cash at the midpoint of the price range while leaving the group in control of the company.
Oura to acquire AI-native primary care startup Counsel Health for $625M
The deal comes a few weeks after Oura postponed its up to $2.2 billion IPO indefinitely, citing “uncertainty in the IPO market.”
PSI is trying to make a business out of AI-driven scientific discovery
PSI used an unreleased Anthropic model to answer a fundamental question about quantum computing that scientists have pursued for nearly two decades.
OpenAI rolls out new business profiles, making ChatGPT just a little bit more like Google
OpenAI is looking to make ChatGPT a more robust consumer discovery engine, and a host of new features seek to empower businesses to help it do that.
Anthropic launches Claude Meetings to turn workplace discussions into plans and tasks
As participants talk, Claude can draft the plan being discussed, map out a timeline on a whiteboard, answer questions in the meeting chat, and access connected work apps to retrieve information, such as last year's figures.
Nvidia CEO Jensen Huang’s affair with alleged Chinese spy: a timeline
The affair could have ramifications for national security as the U.S. and China race to develop the most advanced AI infrastructure.
Google broadens its AI hardware portfolio with two new specialized chips
Google's new tensor processing units (TPUs) broaden its chip portfolio to more use cases: confidential model training and more memory capacity.
Meta’s AI agent Muse lands on Apple Watch and Android Wear OS
Users can now interact with Meta’s AI assistant through voice calls, text messages, or dictation on their Apple Watch.
双11冲刺进行时！抖音商城服饰趋势品牌有哪些
双11进入最后冲刺，秋冬服饰需求仍在持续释放。11月10日，抖音商城双11服饰趋势品牌发布，女装、男装、童装童鞋、内衣配饰、鞋靴运动、箱包装备六大细分榜单同期出炉，呈现出泛时尚消费领域的热门风向。 01 趋势女装 秋冬换季叠加降温节点，冬装成为女装消费的主力。 趋势女装榜上，AP、MSBEAST/野兽小姐、RENATHING位列前三。 “既要暖暖的，也要美美的”，正成为女性冬装消费新主张。皮草日常化与版型剪裁的设计升级，直接带动了高客单女装品类的爆发。 02 趋势男装 男装的消费偏好，正从“能穿”向风格与场景迁移。 趋势男装榜上，MBNL-F/秦磊、悍石
Adobe brings AI agents and new creative tools to Photoshop, Premiere, and Firefly
Adobe is taking on Figma with a new prototype builder tool in Firefly.
Anthropic sets IPO price range of $70 to $78 per share to reach an implied valuation of $1.404 trillion
The company could end up being worth a hefty $1.404 trillion if its shares list at the top of the price range, on a fully diluted basis.
After challenging Google’s Android with Cyanogen, its co-founder takes aim at Windows for AI era
Kora is set to launch as a free-to-use alternative to Windows, targeting users who rely heavily on AI models and agents.
Spotify’s AI DJ gets new voices, personalities, and an option for less chatter
Spotify Premium users can now customize their AI DJ with new voices with different personalities, or turn off the commentary between songs.
Ring, known for its doorbell cameras, launches a home security drone and an enterprise security robot
Amazon-owned Ring is pushing into robotics with the launch of a home security drone and a rolling robot designed to patrol and protect businesses.
Cyberattacks threaten to make open source AI a little less open, Hugging Face exec warns
Hugging Face executive Irene Solaiman warns that growing cyberattacks on open AI platforms could force tighter security restrictions, threatening the accessibility that makes open source communities valuable to developers worldwide.
阿里巴巴：已正式申请平头哥独立上市
11月10日晚，阿里巴巴集团发布公告：已向香港联交所交表，申请旗下子公司平头哥独立上市。上市完成后，平头哥仍将是阿里巴巴子公司。 公告显示，2026年9月11日，平头哥已向香港联交所递交上市申请，拟通过H股在香港联交所主板独立上市。据悉，IPO具体规模尚未最终确定。 截至2026年4月，平头哥真武系列AI芯片累计出货量达56万片。平头哥上市安排，将有助于市场更清晰定价阿里巴巴核心业务价值，并展现平头哥自身作为中国领先全栈数据中心芯片提供商的商业价值，吸引半导体和AI算力赛道专业投资者，也将进一步支撑平头哥加大研发和人才投入，提升国产优质算力供给。
吉利星愿上市两年，刷新全球最快百万销量速度纪录
11月6日，吉利银河全球用户音乐嘉年华暨吉利星愿百万达成宠粉权益发布会，在杭州举行。上市24个月，吉利星愿累计销量突破100万辆，不到一分钟售出一辆，成为全球最快达成百万销量的新能源汽车，以现象级爆款姿态改写了全球纯电小车市场的竞争格局。 面向百万用户的信赖与期待，吉利星愿发布STAR限定系列新版型——STAR Ace与STAR Chill，限时权益价8.88万元；同时“百万达成宠粉权益”也在大会上发布，用户登录吉利银河App参与抽奖，就有机会获得爷爷不泡茶奶茶券、吉利星愿百万销量纪念徽章、吉利星愿车载生态实用精品、卡皮巴拉治愈IP周边等好礼。吉利星愿以
灵光接入什么值得买，AI助理开始帮用户“盯好价”
从商品推荐到价格追踪，个人AI助理进一步深入日常消费场景。 11月10日消息，蚂蚁集团旗下个人AI助理灵光接入消费内容平台「什么值得买」，将商品信息、消费决策支持等服务进一步纳入灵光。 此次接入是灵光持续扩展开放服务生态的又一动作。此前，灵光已陆续接入支付宝、钉钉、飞书、米家、微信读书、哈啰打车等40个连接器服务，能力覆盖工作、出行、家庭管理和日常生活等多个场景。 「什么值得买」长期积累了商品信息、消费内容和优惠信息等资源。对于灵光而言，接入专业消费信息服务，有助于提升AI在具体消费场景中的信息获取和服务能力；对于什么值得买而言，个人AI助理也提供了一个
从芯片到千比特整机，超导量子计算还有一场硬仗
近亿元融资刚刚落袋
从“一脑多机”到“一脑多手”，蚂蚁灵波开源LingBot-Touch触觉基础模型
11月10日，蚂蚁灵波科技开源触觉基础模型LingBot-Touch
Agent自演进驶入“双轨时代”！openJiuwen首发TTSE经验学习框架
让每一次任务，都成为下一次进步的起点
成立四个月，融资过亿美金：TensorWorld物原科技要跑通“物理真实”路线
TensorWorld物原科技在一个月内已拿到过亿美元融资
达卯科技与浦东环保能源战略合作，黎明智算中心算电协同平台启动
加速东部城市型智算中心向E-AIDC演进
Token卷到触觉了！机器人终于有了通用手感
蚂蚁灵波开源LingBot-Touch
四维图新创想大会 | 以数据与算力为基，SEEWAY.AI驶向新一站
11月6日，四维图新在上海举办2026 EVOLUTION创想大会。CEO 程鹏全面解读穿越 “极点” 的破局方向，以数据与算力为基，答行业焦点之问，并正式公布向移动智能体领域拓展的战略布局。 数据之战，先拿好合规这张入场券 "过去十年，中国新能源赢在电池；未来十年，中国汽车要赢在数据。"程鹏的判断直指行业下一个核心战场——数据已成为汽车智能化的"第二战场"，而用好数据的前提，是合规。 监管的门槛正在快速抬高。2026年9月，GB 48319与GB 48320两项时空数据安全新强标正式发布，将于2027年10月实施，四维图新作为参编单位参与起草。叠加6部
Fable 5.2首批实测来了！网友：Opus突然不香了
作曲、拍片、3D建模一条龙全包圆
Otter AI can now follow conversations across 30+ languages
Otter AI just added support for 27 languages and revealed an upcoming feature that can follow along if speakers switch between languages.
Fable 5.2 “撞车”蚂蚁灵波触觉模型，CEO 朱兴：两类模型协同将加速具身产业成熟
11 月 10 日，Claude Fable 5.2 发布同日，蚂蚁灵波科技开源触觉基础模型 LingBot-Touch。一款面向数字世界的通用大模型，一款面向物理操作闭环的具身基础模型，同一天走进公众视野。 这两条技术路线的关系，正是当下具身智能行业讨论的焦点。在蚂蚁灵波看来，通用大模型与具身基础模型更接近 1+1＞2 的协同关系：前者增强对任务和环境的理解与推理，后者补齐物理感知与闭环操作能力，两者齐头并进，才能共同加速具身产业成熟。 此次开源的 LingBot-Touch 基于近 5000 小时真实触觉数据预训练，覆盖磁触觉、视触觉和压阻式三类主流
从众筹爆款到现货开售，妙动科技Beni机器人开创影像新视角
2026 年 11 月 10 日，消费级机器人公司妙动科技宣布，旗下全球首款多地形跟拍机器人 Beni 正式开启现货发售：标准套装售价 4999 元、探索套装售价 5799 元，国内用户可通过京东商城购买，即买即发货。 一个月前，Beni 刚以筹资超 500 万美元、全球 7926 名支持者的成绩，创下Kickstarter 平台消费级机器人众筹金额历史第一的纪录。今天，它已从“众筹爆款”进入“现货开售”的阶段。对成立不到两年的妙动科技而言，此次Beni开售不止是面向全球用户推出首款产品，更意味着将前沿机器人技术与专业影像工程融合，探索出具身智能在消费级
Forcing a Letter Suppresses Refusal: Mechanistic Evidence from WMDP
arXiv:2611.08639v1 Announce Type: new Abstract: Safety benchmarks for large language models (LLMs) commonly use multiple-choice question (MCQ) format. However, prior studies documented that MCQ format reduces refusal rates, which may significantly affect the safety behavior of th
FinEvolveKG: Controlled and Attributable Prompt Evolution for Financial Knowledge Graph Construction
arXiv:2611.08643v1 Announce Type: new Abstract: Financial institutions construct knowledge graphs (KGs) from shared SEC 10-Ks to serve risk analysis, portfolio management, and investment research, whose analytical needs differ. Extraction must adapt without fragmenting shared gro
Compression of Emotion in Language Model Representations
arXiv:2611.08683v1 Announce Type: new Abstract: Large language models (LLMs) have been evaluated on their ability to identify emotions expressed in text and produce fluent emotional language. However, output predictions alone do not reveal how fine-grained emotion distinctions ar
Contextuality and Contradictions: Exploring Real-World Identifications of AI-Generated Writing
arXiv:2611.08704v1 Announce Type: new Abstract: As AI-generated content spreads into nearly every domain of human interaction, practices and discourses of AI detection, both formal and informal, have become an everyday part of how people interact with text and with each other. In
RL-ATTACK: A Generalized Black-Box Adversarial Attack on Language Models via Reinforcement Learning
arXiv:2611.08711v1 Announce Type: new Abstract: Large language models (LLMs) exhibit vulnerabilities to adversarial perturbations that can induce unintended responses. These vulnerabilities can be identified via intentional attacks and subsequently used to improve model safety. I
Structuring Survey Histories for LLM Digital Twins: A Controlled Study of Background, Decision Procedure, and Evaluation Profiles
arXiv:2611.08730v1 Announce Type: new Abstract: LLM-based digital twins aim to predict how individuals would respond in new settings from representations of their prior responses. Existing evidence that compression of survey histories need not reduce predictive accuracy suggests
Semantic Conditional Similarity (SCS): A Formal Mathematical Framework
arXiv:2611.08778v1 Announce Type: new Abstract: Semantic Textual Similarity (STS) operates on document pairs, returning a single scalar per comparison. In a multi-document setting where several sources may have contributed to one or more targets, pairwise STS cannot disentangle e
Guardrail Erosion in Domain Fine-Tuned Large Language Models: A Paired Audit of Knowledge-Centric Abstention in Biomedical LLMs
arXiv:2611.08780v1 Announce Type: new Abstract: The number of domain fine-tuned models, particularly in the biomedical domain, is rapidly expanding. Fine-tuning promises high-performing models at a fraction of the cost of training a base model, but it can also produce unintended
Richness Is Not Evenness: Ordered Renyi Crossings under Self-Training
arXiv:2611.08892v1 Announce Type: new Abstract: Recursive self-training of language models, a setting studied in model collapse, can reduce vocabulary while making frequent words, mostly function words, less dominant. We fine-tune English GPT-2 on its own output for nine generati
From Procedures to Permissions: Learning Precise Subagent Authorization from Agent Skills
arXiv:2611.08905v1 Announce Type: new Abstract: As language agents tackle increasingly complex tasks, they increasingly rely on multiple agents to coordinate specialized work, requiring decisions not only about what each subagent should do but also which tools and workspace resou
On the Incompleteness of do-calculus for Universal Identifiability
arXiv:2611.08916v1 Announce Type: new Abstract: We study the problem of causal effect identification from an arbitrary set of observational and/or interventional distributions, which we call Universal Identifiability (uID). The uID problem generalizes existing classical identifia
Using an LLM to Tackle Difficult Cases in NER for Nepali Tweets
arXiv:2611.08967v1 Announce Type: new Abstract: Named entity recognition (NER) is challenging for social media data in a low-resource language. LLMs often lag behind pretrained language models (PLMs) in NER performance, but they show promise in handling cases that PLMs struggle w
Beyond Truncation? Entailment-Licensed Elision and the Limits of Semantic Preservation in LLM Decoding
arXiv:2611.08975v1 Announce Type: new Abstract: Instruction-tuned large language models (LLMs) answer at greater length than a request needs. We ask whether a training-free controller inside the decoding loop can remove that surplus while preserving content, judged against the si
Language, Not Code Abstraction: Natural-language Training Shapes Brain-aligned Geometry
arXiv:2611.09027v1 Announce Type: new Abstract: Code-trained language models produce positive brain scores, which raises the question of whether abstract structure learned from programming languages can substitute for natural-language training. We trained 25 GPT-2-small models on
Failure Profiling and Reachable Trajectory Selection for Reasoning Distillation
arXiv:2611.09042v1 Announce Type: new Abstract: Training smaller language models on reasoning solutions generated by a larger teacher model is the prevailing approach for transferring mathematical reasoning capabilities. However, the student tends to overfit the output distributi
Does Reasoning Improve Psychological Depth in Large Language Models?
arXiv:2611.09061v1 Announce Type: new Abstract: Benchmark gains from reasoning-enhanced large language models encourage the assumption that these models should broadly perform better on complex generative tasks, but this remains underexplored in open-ended, creative domains shape
The Invisible Gap: Romanized Indic Generation Fails Where Automatic Metrics Succeed
arXiv:2611.09085v1 Announce Type: new Abstract: Hundreds of millions of Indians communicate with digital systems in romanized Latin characters -- typing "aap kaise hain" rather than native script -- yet romanized Indic generation is absent from NLP benchmarks and evaluation frame
MARS: Training Multilingual Search Agents for Retriever-Free Evidence Acquisition
arXiv:2611.09090v1 Announce Type: new Abstract: Existing multilingual retrieval-augmented generation relies heavily on learned retrievers and similarity-based ranking from multilingual collections, which are vulnerable to cross-lingual retrieval errors and indexing overhead. In t
AlienBench: A Benchmark of Structural Novelty in Language Model Outputs
arXiv:2611.09094v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for creative tasks such as writing, design, and idea generation. For these uses, it matters whether a model's ideas depart from familiar examples or stay close to them. Novelty is o
PhoPunct: A Large-Scale Benchmark of Transformer Architectures for Vietnamese Punctuation Restoration
arXiv:2611.09107v1 Announce Type: new Abstract: Vietnamese punctuation restoration is often evaluated on relatively small benchmarks, limiting conclusions about how architectural choices scale with data volume. We present a controlled benchmark on News and Novels corpora containi
Calibrated concept profiles: making the reading of a model's neurons a measurement
arXiv:2611.09196v1 Announce Type: new Abstract: Interpretability has largely moved from reading a model's neurons directly to reading a second model trained on the first: a probe, a sparse autoencoder, a crosscoder. The move answered real faults -- mixed meanings, thresholds with
Representational drift in a code model: behaviour settles, which neurons carry it does not
arXiv:2611.09204v1 Announce Type: new Abstract: In neuroscience, representational drift is a change in which neurons carry a representation while behaviour stays the same; we measure its analogue in OpenCoder-1.5B during pretraining, for 169 Python constructs over two trillion to
Khmer PFGen-Bench: Building a Judge-Free Benchmark for Open-Ended Generation in a Low-Resource Language
arXiv:2611.09222v1 Announce Type: new Abstract: Benchmarks for open-ended generation often rely on large language model (LLM) judges, whose reliability in low-resource languages is uncertain. We introduce Khmer PFGen-Bench, to our knowledge the first judge-free benchmark for mult
KLEAR: Knowledge-Matched LLM Evaluation in Korean across Application Requirements via Controlled Benchmark Transformation
arXiv:2611.09223v1 Announce Type: new Abstract: Existing Korean benchmarks for Large Language Models (LLMs) evaluate performance across diverse knowledge domains, but their accuracy scores cannot distinguish whether incorrect responses arise from a lack of required knowledge or a
DUET: Dual-Sparse Inference for Block Diffusion Language Models
arXiv:2611.09239v1 Announce Type: new Abstract: Diffusion language models (DLMs) enable parallel token generation through iterative denoising, yet their inference remains costly due to repeated attention over a growing historical prefix and repeated processing of the entire curre
Multilingual Artificial Datasets for AI-Driven Cardiology: the CliTe and ParaCliTe corpora
arXiv:2611.09296v1 Announce Type: new Abstract: Background and Aims. Comparable, multilingual, validated cardiology corpora are critical to advance trustworthy natural language processing (NLP) models for cardiology but such resources are scarce due to privacy concerns. This stud
Asymmetric Correspondence Learning for Lexical and Style Embeddings: Interpreting Latent Space via Acoustic Features
arXiv:2611.09313v1 Announce Type: new Abstract: Self-supervised speech embeddings jointly encode lexical, speaker, and prosodic information, complicating feature isolation. We introduce Asymmetric Correspondence Learning (ACL), distilling HuBERT features into separate Acoustic Wo
Syn2DRE: Synergistic Dual Teacher-Student Framework for Document-level Relation Extraction
arXiv:2611.09342v1 Announce Type: new Abstract: Document-level Relation Extraction (DocRE) aims to identify relations between entities across a document but typically relies on costly large-scale annotations. While pseudo-labelling enables the use of low-quality data, existing me
A Spiking Neural Model of the Mental Lexicon: Representations, Similarity Structure, and Associative Retrieval in Perception and Production
arXiv:2611.09402v1 Announce Type: new Abstract: A neural account of lexical access requires an explicit distinction between the structure of lexical representations, the associations linking representational levels, and the activity generated during retrieval. This paper specifie
内容来自各源站公开 RSS · 每日自动更新