All published intelligence, sovereign stack research, ecosystem news, and AI foundation model reviews.
🧠 Meta* выпустила Muse Spark Open – самую мощную open-weight модель из США Модель ориентирована на кодинг, агентские задачи, сложную разработку и длинные цепочки рассуждений. Главные характеристики: • 816 млрд параметров, из них 42 млрд активных; • контекстное окно на 1 млн…
Nvidia 拥有一个拥有 26 亿参数的开放世界模型。它可以将图像、文本提示和相机运动轨迹转换为可控的虚拟世界。所有这些都在单个 GPU 上运行。- 代码可在 GitHub 上获取。- 研究论文已在 arXiv 上发布。- 适用于……
🎙 OpenAI 已更新语音 - GPT-Live-1.1 已发布。新版本有更多的声音、改进的口音以及更少的接听时的“检查...”等停顿。 GPT-Live-1.1 已经在 ChatGPT、Codex 和dots 上运行。还添加了以下语言的新声音： • 法语； • 德语； • 印地语； •…
🖥 腾讯发布 Hy Memory 2.0：开放模型、框架和 MemHub，为 AI 智能体提供长期记忆。Hunyuan 在一个版本中同时发布了三项内容：Hy-Memory-30B-A3B 模型、SDK 框架和 MemHub 应用。据腾讯称，这是四大开放解决方案中的第一名……
В Казахстане впервые провели две робот-ассистированные операции на легких.
🟢 Новый глава Apple рассказал TIME о будущем iPhone, искусственном интеллекте и конкуренции с OpenAI Генеральный директор Apple Джон Тернус, сменивший Тима Кука в сентябре, дал первое большое интервью TIME и появился на обложке выпуска Best Inventions 2026. Собрали главное. 🗣️…
Ведущий инженер Anthropic, написал руководство о том, как действительно ставить более амбициозные задачи перед ИИ, и поделился готовым промптом. Феликс Ризеберг, работающий над Claude в Anthropic, отмечает, что все советуют быть "амбициознее" при использовании ИИ, но никто не…
🔍 Anthropic впервые допустила независимых экспертов к внутренним системам для проверки безопасности ИИ Разработчик Claude предоставил шести исследователям некоммерческой организации METR доступ к своим внутренним инструментам практически на уровне сотрудников компании. Эксперты…
15 октября в Qazaq AI Research University (QAIRU) прошёл форум, посвящённый Дню работников высшего образования. Участники обсудили цифровую трансформацию вузов, применение искусственного интеллекта в обучении и науке, а также подготовку специалистов для цифровой экономики,…
Benchmark 的合作伙伴承认，风险投资不支持竞争对手公司的传统规则正在受到人工智能快速发展的考验。随着公司迅速...，投资组合公司之间的利益冲突变得越来越普遍。
arXiv:2610.20951v1 Announce Type: new Abstract: Decision models answer typed questions about an input with one probability per option, computed in a single forward pass without generating text. Like the fast System 1 of dual-process theory, they answer at once, but their depth…
arXiv:2610.20782v1 Announce Type: new Abstract: The closed world asks AI for specialized competence and lets it manufacture the iid data its theory assumes: a fixed criterion licenses collecting examples until the task is covered. The open world asks for versatility --- taking…
arXiv:2610.20676v1 Announce Type: new Abstract: Correctness feedback suppresses the very evidence that specification-completeness auditing is designed to uncover: programs that satisfy a written contract but violate intended behavior. We demonstrate this objective reversal on 12…
arXiv:2610.20681v1 Announce Type: new Abstract: Formal inequality proving requires mathematical reasoning and exact computation, often connected through intermediate lemmas and goal reformulations. We introduce IneqAgent, an agentic framework combining LLM reasoning with…
arXiv:2610.20786v1 Announce Type: new Abstract: Multi-modal agents have made significant progress in interacting with open worlds. However, their ability to self-evolve remains limited. Supervised fine-tuning enables imitation but not active experience organization, while…
arXiv:2610.20836v1 Announce Type: new Abstract: Evaluator-guided reasoning presents a local control problem at every step: trust the current answer, return a fallback, or spend more inference. We formulate this choice as a compute-aware three-action controller, scoring terminal…
arXiv:2610.20867v1 Announce Type: new Abstract: We present a general declarative framework for anticipatory reasoning about interactive motion in complex dynamic environments. Our focus is on (explainable) anticipatory space-time mental model formation at a semantic level to…
arXiv:2610.20926v1 Announce Type: new Abstract: Agent skills turn procedural knowledge into reusable artifacts, allowing LLM agents to accumulate and refine expertise through experience. Building on this, skill evolution iteratively improves skills using execution feedback.…
arXiv:2610.20939v1 Announce Type: new Abstract: Online reinforcement learning (RL) with verifiable rewards has driven rapid progress in mathematics, coding, and tool use, but scaling this success to GUI agents remains challenging due to the high cost of interactive environments…
arXiv:2610.20822v1 Announce Type: new Abstract: Text-to-video models often generate the visual concepts requested in natural language prompts but fail to satisfy their intended ordering, timing, and persistence requirements. We propose representing these requirements as…
arXiv:2610.20805v1 Announce Type: new Abstract: A reasoning trace retained at answer time plays two roles: it can raise accuracy, and it can compete with the current evidence when the two disagree. We disentangle these roles by crossing verified evidence versions with the traces…
arXiv:2610.20667v1 Announce Type: new Abstract: Rapid advances in AI capabilities are causing benchmarks to saturate. Once several models approach perfect scores, a benchmark loses its power to differentiate between them, and with it its utility for informing AI safety cases and…
arXiv:2610.20669v1 Announce Type: new Abstract: Reward-guided discrete diffusion enables test-time alignment with downstream objectives, but applying Sequential Monte Carlo (SMC) guidance at every denoising step is computationally expensive. Active guidance steps require…
arXiv:2610.20921v1 Announce Type: new Abstract: Most debate about releasing capable AI systems treats the choice as binary: keep the model behind an API, or publish the weights. That framing runs together two separate decisions. One is how capable a system may become. The other…
arXiv:2610.20809v1 Announce Type: new Abstract: A self-improving agent has to decide which new skills to keep, and in practice it keeps whatever earns a high reward, convinces a judge model, or compresses its library, even when the skill is wrong. That is fine until the answers…
arXiv:2610.20764v1 Announce Type: new Abstract: This paper challenges the understanding capabilities of existing AI paradigms and emerging world models by asking a fundamental question: How quickly can reality change before an intelligent system can no longer reliably perceive,…
arXiv:2610.20935v1 Announce Type: new Abstract: Engineering agents must produce artifacts that satisfy exact, coupled constraints. Existing solutions often require agents to make semantic decisions and also derive consequences such as precise geometry or timing from those…
arXiv:2610.20675v1 Announce Type: new Abstract: Agents pair reasoning models with harnesses that organize model calls, execute tools, load skill instructions, and retain history in memory. Understanding agent performance requires linking execution conditions to outcomes,…
arXiv:2610.20679v1 Announce Type: new Abstract: Representation-based safety defenses for vision-language models (VLMs) often learn to separate harmful from benign inputs, but separation alone does not establish what a risk score means or when it should be trusted. We introduce…
arXiv:2610.20922v1 Announce Type: new Abstract: Compositional structure is pervasive in nature and across scales: atoms combine into molecules, molecules into cells, and cells into organisms, while further compositional hierarchies appear within each level. More broadly,…