Общее1 мин
How Cooley is accelerating IPO work with ChatGPT
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.
OpenAI Blog
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All published intelligence, sovereign stack research, ecosystem news, and AI foundation model reviews.
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Stories
Исследования1 мин
Они это сделали: Anthropic объединяет Claude Cowork, Claude Design и обычный чат в один Claude 🎉
Они это сделали: Anthropic объединяет Claude Cowork, Claude Design и обычный чат в один Claude 🎉.
Telegram — Вайб-кодинг
Исследования1 мин
GPT-6 Astra практически без ограничений???
GPT-6 Astra практически без ограничений???.
Telegram — Вайб-кодинг
База знаний1 мин
Replacing 7 Salaries With ONE AI Tool!
Короткий вопрос перед следующим советом. Сколько бы вы платили человеку, который находит клиентов, создает сайты, подбирает креативы, запускает рекламу, занимается SEO и готовит отчеты каждую пятницу? Какую бы цифру вы ни назвали, запомните её , ведь я нашел инструмент, который…
YouTube — AI Master
Общее1 мин
人工智能代理已经提出了自己的语言，但人们变得难以理解
🗣 人工智能代理已经提出了自己的语言，但人们变得难以理解。据《卫报》报道，没有人特别要求模特们创造一种新的沟通方式。在交互的过程中，智能体本身开始形成共同的词汇，赋予单词新的含义……
Telegram — GPT Time | Нейросети | ИИ
Общее1 мин
Meet the innovators under 35 shaping climate tech
Each year, the editorial team at MIT Technology Review puts together a list of 35 innovators under 35—a group of researchers, inventors, and other young minds worth following. The team worked on the newest edition of the list for months, and the final slate includes nine…
MIT Technology Review
Общее1 мин
Cloudflare открыла исходный код скилла, который превращает ИИ-агента в аудитора безопасности.
Cloudflare открыла исходный код скилла, который превращает ИИ-агента в аудитора безопасности..
Telegram — Вайб-кодинг
Стартапы1 мин
сентября приглашаем на АЛЬФА ВААА{АИ}ЙЙЙБ МИТАП — масштабное событие про нейросети и вайб-кодинг. Узнаем, кто из ф...
сентября приглашаем на АЛЬФА ВААА{АИ}ЙЙЙБ МИТАП — масштабное событие про нейросети и вайб-кодинг.
Telegram — Вайб-кодинг
Telegram — Вайб-кодинг
База знаний1 мин
Google is SO back...
Google dreams of RSI, recursive self-improvement. While most of the country is debating whether or not we should have RSI, Google is like, "Hey, we can put this AI into a simulation and have it do RSI." Which, I got to say, you got to give them credit for this. So, in this…
YouTube — Wes Roth
Общее1 мин
Iceland-based Treble raises $18 million for its voice simulation platform
Treble's voice simulation platform is used by voice AI model developers, AI wearable, and robotics companies
TechCrunch — AI
База знаний1 мин
Work IQ: Tooling with MCP & CLI #workiq #m365 #copilot #mcp #cli #devtool
Workday IQ MCP This is what allows agents to call Workday IQ as a set of tools. So, instead of just generating answers, it can pull real context from Microsoft 365 and take action. Through the unified MCP server, Workday IQ exposes Microsoft 365 to access things like chats,…
YouTube — Microsoft Developer
Общее1 мин
«ИИ может убить нас всех»: как за неделю страх вокруг AI вышел на новый уровень За последние несколько дней дискус...
«ИИ может убить нас всех»: как за неделю страх вокруг AI вышел на новый уровень За последние несколько дней дискус....
Telegram — BlueScreen.kz
Исследования1 мин
Memory Has Geometry: Non-Uniform Geometric Memory for Long-Horizon Personalized AI
Long-term memory is becoming a core substrate for personalized AI, yet most systems still represent personalization as discrete records in a largely static latent space, accessed under one global similarity notion. For data mining, this creates a mismatch: the evidence is a…
arXiv — cs.AI
Исследования1 мин
The Inference Engineering Pareto Atlas: Which Optimizations Dominate the Cost, Quality, and Latency Frontier?
LLM inference optimizations report speedups on different models, GPUs, prompts, and quality metrics, making them hard to compare or combine. We build a cost, quality, and latency Pareto atlas to identify the best configurations for different deployment constraints. Since…
arXiv — cs.AI
Исследования1 мин
OBC-Prune: Outcome-Based Calibration for Large Reasoning Model Pruning
Large reasoning models (LRMs) generate long chain-of-thought traces before answering, creating significant inference overhead. Pruning can reduce this cost, but its effectiveness depends on the calibration data used to estimate parameter importance. Recent work calibrates on the…
arXiv — cs.AI
Исследования1 мин
Making AI-Assisted Claims Independently Challengeable: Publication Authority and a Protocol for Falsifiable Publication Records
AI-assisted claims can appear authoritative when evidence, analysis, human authorization, presentation, and correction history refer to different states. Provenance, attestation, and transparency expose history but alone do not specify the publication transition examined here.…
arXiv — cs.AI
Исследования1 мин
One Color Preprocessing Improves DSATUR
The Graph Coloring Problem (GCP) is NP-hard and DSATUR stands as one of the fastest heuristics for it despite producing colorings that typically use more colors than state-of-the-art coloring algorithms. We propose SSLD (Semidefinite Spectral Learning with DSATUR), which…
arXiv — cs.AI
Исследования1 мин
Physics-Constrained Digital Twins for Sensor Integrity in Urban Pedestrian Flow: Detecting Stealthy False Data Injection with Conformal Guarantees
City pedestrian counting systems now feed economic indicators, planning decisions and safety operations, yet the twins built on top of them treat the incoming stream as ground truth. We study what happens when it is not. We formalise stealthy false data injection for city-scale…
arXiv — cs.AI
Исследования1 мин
GraphEcho: Structural Redundancy and Evidence Provenance in LLM Graph Agents
A large language model (LLM) agent can follow more graph paths without acquiring more independent evidence. GraphEcho tests whether agents mistake these repeated encounters for additional corroboration. The benchmark varies path counts and evidential origins while holding…
arXiv — cs.AI
Исследования1 мин
NeMo Data Designer: An Extensible Framework for Multimodal Synthetic Data Generation
We present NeMo Data Designer (NDD), an open-source, general-purpose framework for multi-modal synthetic data generation (SDG). Designed to be intuitive to use, NDD provides a declarative configuration format in which human and/or agent users define each dataset column, with…
arXiv — cs.AI
Исследования1 мин
Imitation Learning for Autonomous Driving in CARLA
Behavioral cloning trains a policy offline on expert demonstrations, but deployment is closed loop: each action affects the observations the policy receives next. We study how much closed-loop driving competence a compact multimodal policy can acquire from offline demonstrations…
arXiv — cs.AI
Исследования1 мин
A Four-Stage Decomposition of Word-Problem Solving and Mechanistic Fragility in LLM Math Reasoning
Large language models solve grade-school math word problems with high accuracy, yet a single irrelevant clause inserted into the problem can collapse it. We reconcile these observations with a mechanistic account. We show that the model's internal computation decomposes into a…
arXiv — cs.AI
Исследования1 мин
EvolveTrade: Experience-Driven Policy Refinement for Self-Evolving LLM Trading Agents
Large language model (LLM) trading agents can combine market data, news, and executable analysis, but their behavior is often controlled by static hand-written tool-use policies that are fixed before deployment. This limits their ability to adapt how they gather evidence, invoke…
arXiv — cs.AI
Исследования1 мин
CapMem: A Benchmark for Caption-Based Episodic Memory in Egocentric Video
Wearable assistants require episodic memory over egocentric video, yet current vision-language models face bounded frame budgets, growing visual-token costs, and long-context retrieval failures. Under these practical constraints, we study whether textual captions can serve as…
arXiv — cs.AI
Исследования1 мин
GVD: Governed Versioning and Deduplication for Document Repositories
Document repositories evolve continuously. Guidelines and policies are revised, superseded, and re-uploaded, so the same content recurs in different wording and newer versions refine or contradict earlier ones. These inconsistencies belong to the growing collection rather than…
arXiv — cs.AI
Исследования1 мин
A Systematic Evaluation of the COTQ Provincial Land Cover Product: Structural Consistency, Spectral Separability, and Relative Positioning Against ESA, ESRI, and Google Products
High-resolution land use and land cover (LULC) products derived from Sentinel-2 imagery are widely used for environmental monitoring and land management, yet their performance can vary across regions with complex ecological gradients and heterogeneous surface conditions. In…
arXiv — cs.AI
Исследования1 мин
Learning Heterogeneous Preferences
Learning from human feedback has become a central paradigm for training modern AI systems, where models of human utility are used as reward models in policy learning. Existing methods typically assume a \emph{universal utility} function shared across a population and treat…
arXiv — cs.AI
Исследования1 мин
SNOMED CT Concept Recommendation from Masked Clinical Context
Standardizing clinical language to SNOMED CT supports interoperability, analytics, and reusable phenotyping, but concept recommendation remains difficult when relevant concepts are rare or absent from training data. We present a masked-concept recommendation benchmark using the…
arXiv — cs.AI
Исследования1 мин
When to Call an LLM: A Confidence-Gated Hybrid for Cost-Effective Emotion Recognition in Conversational AI
Emotion recognition in conversation (ERC) is a production capability behind agent-assist prompts, escalation routing, and post-call analytics in contact-center-as-a-service (CCaaS) platforms, where cost and latency constraints matter as much as accuracy. We report a…
arXiv — cs.AI