Барлық жарияланған талдаулар, егеменді стек зерттеулері, экожүйе жаңалықтары және ЖИ модельдерінің шолулары.
Anthropic оның жаңа Claude Opus 5.5 моделінің соңғы жалған AI бұзу оқиғаларынан кейін күшейтілген қауіпсіздік шараларымен қамтамасыз етілгенін айтады. Сейсенбі күнгі хабарландыруда Anthropic компаниясы Opus 5.5 белгілі бір қауіпті мінез-құлықтарды жақсартумен, соның ішінде компаниядан құтылу әрекеттерімен бірге келеді дейді ...
Всем привет. В этом выпуске самые главные и свежие новости об искусственном интеллекте и технологиях. Новая модель GEF обещает работать в 100 раз быстрее и в 100 раз дешевле привычных и моделей. Разговоры о безопасности ИИ становятся всё страннее. Порой уже сложно понять, где…
OpenAI заявила, что её новая модель решает математические задачи быстрее, чем люди успевают проверять доказательства.
Британдық AI деректер орталығының әзірлеушісі табысының көп бөлігін Microsoft және Anthropic алпауыттарына тәуелді.
So, this is a blog post by Scott Aaronson. He's a very well-known theoretical computer scientist. He did work at OpenAI in the early days working on alignment and played a major role in Google's claims of quantum computational supremacy. Basically, the guy knows a thing or two.…
Семейство Qwen4 впервые анонсировали официально..
Джевтің ашық жергілікті баламасы бар сияқты - Лая. Laya - 421 миллион параметрі бар жергілікті ашық шешім қабылдау моделі. Ол құрылымдық шешімдермен жұмыс істейді (жылдам иә/жоқ жауаптары, бағалау немесе нұсқалардан таңдау). > 1 ГБ-тан аз жадпен жұмыс істейді >...
AI хайп үшін бірнеше ай бос емес. At the end of April, Anthropic claimed that its model Claude Mythos is better at finding software vulnerabilities than most security experts. Then we had the OpenAI–Hugging Face hacking incident, after which Anthropic (proudly) and Meta…
Новая языковая модель поможет расшифровать древнегреческие тексты.
A new AI called Jeff is taking the world by storm, but why get excited for an AI system that can't even write text? It properly ran over the internet, so let's try to separate the facts from the hype. Okay, so it does not write text. Instead, it makes decisions. A question and…
In the hope of uncovering new details about ancient life, researchers have developed a large language model that fills in the gaps in papyrus fragments.
Сравнение навыков Claude Code, субагентов и рабочих процессов в 2026 году.
Интеграция ИИ в существующее бизнес-программное обеспечение.
Для ИИ-агентов выпустили модель, которая принимает решения в десятки раз быстрее обычных LLM.
Исследователь OpenAI Алиса Лю прошла 57 собеседований перед тем, как попасть в компанию, а затем открыто опубликовала....
Sparse representation formulates the environment perception for the end-to-end driving system as a set of discrete elements like objects and lane lines. This formulation meets safety risks in crowded, occluded scenes dealing with unstructured obstacles, uncertain regions, and…
Before patients can use AI-assisted psychiatric intake systems, health systems need practical ways to routinely evaluate these tools against their clinical standards for quality assurance. Because clinicians may use different intake styles, evaluation for this task must (1)…
Long-context large language model inference is increasingly limited by prefill, where dense self-attention processes the entire prompt before generation begins. Sparse block selection can reduce this cost, but a block centroid may hide a highly relevant token among many…
In this work, we examine the topology of information flow patterns within attention graphs to effectively distinguish hallucinated from non-hallucinated responses. We analyze the Forman-Ricci curvature to identify structural patterns indicating information bottlenecks in…
Online agent deployments produce abundant execution traces, while task-specific verification and expert annotation are costly to scale. We study how to distill these traces into reusable feedback without post-hoc outcome labels, drawing on their evidence of local progress,…
Self-play methods that co-train a single language model as both coder and test author promise to move code-generation RL beyond fixed test suites, but they suffer from two coupled pathologies: permissiveness collapse, where pass-rate rewards are maximised by trivial,…
Production LLM agents are evaluated repeatedly as they evolve, but full agent benchmarks are costly to rerun. We study efficient recurring evaluation for a production analytics agent serving tens of thousands of monthly active users and report first-hand deployment experience.…
Organizations deploying agentic artificial intelligence must determine more than whether a model is trustworthy; they must establish what to validate, control, and observe for a use case to deliver its intended outcome while meeting applicable obligations. This paper proposes…
Off-target protein binding is a major source of adverse effects for small-molecule drugs, yet most structure-based molecular design methods focus on generating selective compounds de novo rather than improving the selectivity of existing, well- characterized drugs. We introduce…
Understanding and modeling human intelligence are parallel goals shared by artificial intelligence (AI) and cognitive science. As AI systems grow increasingly capable, in what ways do model responses resemble human responses, and where do they systematically diverge? The sheer…
Post-training plays a pivotal role in enhancing the reasoning capabilities and task-specific expertise of large language models (LLMs). Despite recent advances in post-training methods, such as Group Relative Policy Optimization (GRPO), their practical deployment remains impeded…
Perceptual planning tasks require two key capabilities: accurately perceiving uncertain scenes and planning valid action sequences following logical rules. Conventional methods convert perception into discrete symbolic facts and then plan, discarding perceptual uncertainty and…
Replacing attention in a pretrained language model is a compatibility problem: a plausible substitute may alter representations expected by later layers. TinyCeNN-LM introduces a \emph{quality-gated post-training conversion} framework using CeNN-inspired cellular-recurrent…
Agentic marketplaces are emerging where AI agents with varying capabilities autonomously complete specialized tasks for buyers. A major challenge of such marketplaces is that buyers cannot easily determine which agent will perform best on their tasks. Reported benchmark scores…
Air operations rely on complex rules, established procedures, and time-critical analysis under limited connectivity and strict security constraints. In such environments, analysts must combine written doctrine with images, often without access to external computing resources.…