All published intelligence, sovereign stack research, ecosystem news, and AI foundation model reviews.
👤 Кто стоит за казахстанскими стартапами: первое национальное исследование раскрыло портрет современного фаундера Исследование Kazakhstan Startup Landscape 2026 составило портрет казахстанского фаундера: чаще всего это мужчина в возрасте 31–40 лет (42% основателей) с высшим…
Jump Trading uses OpenAI to expand quantitative research. See how longer-running AI workflows combine multiple data sources with human review.
OpenAI publishes new results on open problems in mathematics from an internal frontier model and shares Lean proof formalizations and research details on GitHub.
Кевин Рус рассказывает о своей книге «Хроники AGI» и обсуждает будущее ИИ.
Исследование Kazakhstan Startup Landscape 2026 составило портрет казахстанского фаундера: чаще всего это мужчина в возрасте 31–40 лет (42% основателей) с высшим образованием (82%). 58% опрошенных основателей имели международный опыт до запуска компании — учились или работали за…
Google создала ИИ-оркестратор для поиска доказательств открытых задач в математике и теоретической информатике Команда Google Research и DeepMind создала харнесс под названием Cogentic. Cogentic делит работу между агентами: одни предлагают направления доказательства, а другие…
Learn how OpenAI and Ironclad are training and evaluating AI agents on complex contracting workflows to advance computer use for professional work.
Статья рассматривает различия между ограниченным декодированием и подсказками в ИИ.
🚀 Astana Hub открывает набор на программу Alem AI Talent Lab для магистрантов QAIRU Astana Hub открывает набор на программу Alem AI Talent Lab для магистрантов QAIRU, заинтересованных в исследованиях и разработке прикладных решений с применением искусственного интеллекта. 🧠…
Бывший вице-министр Дмитрий Мун создал компанию по разработке ИИ в МФЦА Profit.kz
В Астане и Алматы появятся заводы по производству робототехники Новости Zakon.kz
Казахстан начнет развивать собственное производство роботов Total.kz
✔️ Anthropic передала полиции логи чата с угрозами Жительница Флориды была задержана после того, как автоматические фильтры безопасности Anthropic зафиксировали в ее запросах намерения устроить стрельбу в местном офисе шерифа и упоминание покупки оружия. Алгоритмы мониторинга…
🕵️ OpenAI начнёт встраивать скрытые водяные знаки в тексты ChatGPT — пока только в Евросоюзе В ближайшие недели ChatGPT и Codex начнут добавлять в подходящие тексты пользователей из ЕС невидимый сигнал textGrain. Так OpenAI выполняет требования европейского AI Act. Это не…
Узбекистанец Мухаммадсаид Мамасаидов создал ИИ-переводчик Tilmoch для тюркских языков. Сервисом пользуются 200 тысяч человек в месяц, а стартап оценили в $1,5 млн.
Financial LLM agents are often evaluated by comparing their end-to-end returns with those of a baseline and testing the paired difference against zero. This measures whether deploying the agent changes realized performance, but it does not isolate event-selection skill. An agent…
Existing analog integrated circuit design benchmarks make two questions hard to answer: whether a model has learned transferable circuit skills rather than recalled familiar examples, and whether its output works under defined process and test conditions. We introduce a…
Autonomous coding agents solve repository issues by reading code, running commands, editing files, and submitting patches. Extra inference-time compute yields gains only when it produces a useful repair and supplies reliable evidence for choosing one. Three behaviors decide…
AI agents are becoming increasingly capable of generating scientific code, but generating code is not the same as improving the algorithms behind it. For numerical solvers, execution feedback can expose poor performance, but rarely reveals its underlying cause and how to address…
Language-model systems can separate contextual computation, persistent storage, and exact execution instead of updating all capabilities through one shared parameter system. We investigate FEM-ASM, a finite-element-method-inspired organization in which independently constructed…
Agentic multimodal large language models (MLLMs) have recently pushed the frontier of visual reasoning by calling tools such as zooming and tagging. Despite the recent strong success of agentic MLLMs, this work uncovers a critical safety failure in the tool-use paradigm: agentic…
A deployed LLM agent emits tool calls, queries, and code that can be silently wrong -- by the time the error surfaces, the action has run. Frontier chat APIs hide the model's token probabilities; the agent's stated confidence barely beats chance on the mistakes that matter; and…
Each run of an AI-driven research system (ADRS) is an expensive search over a vast solution space, and dependable evaluation requires many runs, making run data both costly to produce and valuable to retain for large-scale analysis. Yet this data remains fragmented: teams…
Autonomous agents built on Large Language Models (LLMs) need standardized protocols to interoperate across systems. Several now exist (A2A, MCP, ACP, ANP, NLIP), but the Natural Language Interaction Protocol (NLIP) has not appeared in any controlled performance study, and no…
Reconstructing global sea surface pH from sparse observations is critical for monitoring ocean acidification and understanding marine carbon cycling. Traditional assimilation and inverse models are physically grounded but costly for large-scale reconstruction. Recent black-box…
The prevailing approach to computer-use agents couples a model with a domain-specific harness: a browser or desktop environment equipped with human engineered tools that are fixed before task execution. As models' coding capabilities improve, the GUI native and static harness…
Multi-agent systems built on large language models (LLMs) are increasingly applied to scientific discovery and hypothesis generation. Both the effect of refinement and the diversity of the delivered set are hard to interpret before experimental ground truth exists, and both are…
Graph based cyber attack detection studies employ various graph construction and representation strategies across different cybersecurity application domains. This diversity motivates a quantitative examination of how representation strategies are distributed across these…
Before autonomous driving systems can be deployed on public roads, it is vital that these systems comply with safety standards, traffic rules, and social norms. Although neural networks trained on large amounts of driving data perform well in routine driving tasks, these models…
Sparse Autoencoders (SAEs) decompose model activations into sparse combinations of interpretable dictionary atoms. Although SAEs are grounded in the Linear Representation Hypothesis (LRH), their objective smuggles in an additional prior: concepts across patches are treated as…