All published intelligence, sovereign stack research, ecosystem news, and AI foundation model reviews.
Persistent memory allows an LLM agent to carry experience across conversations, but it also turns a local reasoning mistake into a durable one. During deliberation, an agent may consider a plan, simulate a tool result, report another speaker's belief, and then reject all of…
Looped LMs are parameter efficient and promise dynamic computation (saving memory and FLOPs on easy tokens). However, state-of-the-art open Looped LMs trained with this dynamic computation capability (Ouro models) do not realize it in practice as each loop iteration (depth)…
Vision-language-action (VLA) models map visual observations and language instructions to continuous robot actions. This task requires a transition from representations that describe the scene and instruction to representations that support action generation. Many…
An agentic system issues several structurally different kinds of LLM calls. It routes intent, classifies actions, grounds language in a device registry, plans multi-agent pipelines and writes the Python code those pipelines run. The difficulty of these call sites varies by an…
We present BEACON-SP, an ontology-grounded Graph Retrieval-Augmented Generation (GraphRAG) framework for clinician-facing decision support in behavioral health settings such as suicide prevention, where effective assessment requires integrating heterogeneous clinical,…
Multi-agent path planning (MAPP) in continuous environments often relies on roadmaps to balance safety and search efficiency. However, traditional roadmap generation methods, such as lattice grids or standard sampling-based approaches, frequently face a trade-off between graph…
Supervisory governors can interfere with the tool-using agents they regulate. We study this possibility in a controlled file-recovery environment where increases in regulatory intensity trigger experimentally imposed tool failures. A cost-blind governor can turn these failures…
Large language models can extract useful signals from heterogeneous enterprise data, but high-recall extraction often produces outputs that are duplicated, uneven in granularity, semantically overlapping, or too numerous for downstream systems and human reviewers to use…
The search for a common view of justice and fairness has challenged human collective activity, as our diverging judgments are unavoidably shaped by the self-interests of social position, personal benefit, cultural inheritance, and historical circumstance. John Rawls famously…
Simulating individual behavior requires large language models (LLMs) to preserve persona traits while adapting to dynamic social contexts. However, general-purpose LLMs often flatten distinct personas, while task-specific tuning suffers from fragmentation and generalization. To…
Detection engineers must translate threat reports, forensic observations, and hunt hypotheses into precise, testable rules. General-purpose large language models (LLMs) can draft such rules, but often produce invalid YAML, incorrect log sources, unsupported fields, or overly…
Enterprise systems increasingly rely on automated workflows, yet many AI-driven solutions remain brittle under non-stationary conditions, evolving policies, and delayed operational feedback. While reinforcement learning and large language model (LLM) agents offer partial…
Agent Skills package procedural guidance and resources for reuse, but a relevant Skill does not necessarily improve task performance. Existing studies characterize Skill content and evaluate downstream performance, yet provide limited explanations of how utility depends on…
Humans perceive far more in a scene than what is explicitly depicted: a single glance captures past causes and future trajectories; a quick peek determines if a vehicle can fit between two parked cars; a few seconds of video reveals who holds authority in a room; and a fleeting…
The global building boom of power-hungry data centers is straining electrical grids, causing greater reliance on energy from polluting fossil fuels. Christina Delimitrou, a newly tenured associate professor at MIT, is fighting this environmental threat by rethinking how the…
Anthropic выкатила Haiku 5.5: модель примерно на 75% дешевле Haiku 4.5 и обходит GPT-6 Luna. Быстрее и умнее Haiku 4.5 Настраиваемая глубина рассуждений Создана для быстрых задач и работы в качестве субагента Для запросов до 100 тысяч токенов цена такая же, как у Luna, но по…
OpenAI disrupted two AI-enabled influence operations that used false-front journalists and a think tank to spread geopolitical messaging.
Mecka AI collects and analyzes human motion data to train humanoid robots and other kinds of robots. The startup pays people to record everyday tasks.
Personal AI assistants like Grockbot, Muse, and Dot have taken AI mainstream. They are helping millions of people get more done, be more productive, and also do less of the tedious, boring stuff that life just requires. I have bots saving me money, planning my calendar, booking…
ChatGPT just got a lot more visual—introducing Intelligent UI. Intelligent UI allows ChatGPT to answer quickly with fully interactive user interfaces that make everyday answers more visual. It makes learning complex topics easier, and it quickly creates tools to solve a task…
Если вы создаете плагины для ChatGPT, вам стоит узнать о расширениях плагинов . Расширения плагинов позволяют интегрировать больше элементов интерфейса вашего продукта в ChatGPT, создавая более насыщенный и интерактивный опыт. Вы можете добавлять собственные инструменты,…
Hello everyone, hope you're having an amazing DevDay so far. On the outdoor stage now we're going to have a panel side discussion with two people from our AI deployment engineering team to talk about how to optimize AI costs. So we're going to talk about things like you know…
All right, everybody, welcome. Welcome to the outdoor stage. All right, thank you. Today, our next guest coming up here, I'm so excited to have you hear from him. He co-founded a product that became Snapchat Cameos and then went on later to lead generative AI at Snap. But now…
[applause] >> Hi everyone. My name is Dominic. I work on the developer experience here at OpenAI. Now Sam earlier launched around 20 or so new features. And between those and the roughly 300 features that we launched over the course of the last year, the building with them has…
Whoa. This is cool. I feel like I recognize half the people in the audience. Thank you all for being here. Last year I was in the seating over there. It's kind of crazy to be up here now. Today I'm excited to talk about multiplayer and what that means. I'm Jason from the…
Hello everyone. Hope you're having a beautiful morning. On the stage I'm super excited. We're gonna have one of our customers Stack Overflow talk about how they're using Codex intensively. So we're gonna have the VP of product Alex Lotto talk about different initiatives, share…
Привет. Спасибо, что сегодня с нами. Меня зовут Ник. >> А я—Даниэль. >> Мы работаем в команде по взаимодействию с разработчиками здесь , в OpenAI. Позвольте начать с небольшого опроса в зале. Поднимите руку те, у кого начало дня выглядит так: почта пуста, в голове ясность, и вы…
Hello, hi everyone, welcome, welcome. My name is Danielle, I work on the developer experience team here. And today we are going to start our interview. So for those of you, anyone passing by, feel free to come on in, hang out. So I'd love to introduce the CEO of Qodo, Itamar…