All published intelligence, sovereign stack research, ecosystem news, and AI foundation model reviews.
Выставка AI-Sana показала возможности превратить знания студентов в области искусственного интеллекта в реальные проекты и разработать новые технологические решения.
🕵️ 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…
Выставка продемонстрировала возможности программы по преобразованию знаний студентов в сфере искусственного интеллекта в реальные проекты и созданию новых технологических решений.
Astra и GPT-6.1 Sol теперь должны работать примерно в полтора раза быстрее — выдавать около 50 токенов в секунду вместо прежних ~30.
Искусственный интеллект все активнее проникает в бизнес-процессы, но вместе с первыми успешными пилотами у компаний возникает более сложный вопрос: что делать дальше? Строить собственную инфраструктуру, идти в облако, готовить данные или сначала вообще разобраться, какую задачу…
AI & Digital Bridge 2026 собрал мировых экспертов, инвесторов и сотни технологических проектов
Казахстан становится центром технологий и инвестиций: итоги AI & Digital Bridge 2026 El.kz
Казахстан становится центром притяжения технологий и инвестиций: итоги AI & Digital Bridge 2026 Liter.kz
Казахстан как евразийский AI-хаб: в Астане завершился AI & Digital Bridge 2026 BAQ.KZ
AI & Digital Bridge 2026 собрал более 18 тысяч участников и завершился 61 соглашением «Астана» телеарнасы
AI & Digital Bridge 2026 собрал более 18 тысяч участников и завершился 61 соглашением «Астана» телеарнасы
47 тысяч посещений и 61 соглашение: чем запомнился AI & Digital Bridge 2026 Azattyq Ruhy
ҚТЖ представило ИТ-стратегию до 2030 года на форуме Digital Bridge Қазақстан теміржолшысы
Узбекистанец Мухаммадсаид Мамасаидов создал ИИ-переводчик Tilmoch для тюркских языков. Сервисом пользуются 200 тысяч человек в месяц, а стартап оценили в $1,5 млн.
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…
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…
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…
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…
Autonomous driving decision systems must balance safety, efficiency, and social norms in complex traffic interactions. Philosophical and ethical considerations have received limited attention in existing autonomous driving decision-making approaches based on numerical…
Recent world action models (WAMs) reuse pretrained video VAEs whose encoder latents directly condition downstream action policies. Quantization must therefore preserve not only reconstruction fidelity but also the policy-facing latent contract expected by the frozen policy.…
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 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…
Large language models (LLMs) are increasingly used as synthetic personas representing survey respondents. Their validity as substitutes for particular respondents depends on whether they reproduce individuals' decisions. We examine what information helps synthetic respondents…
Executable Agent Skills combine natural-language instructions and scripts into reusable packages for LLM agents, and revising them requires fixing errors without breaking correct behavior. Existing benchmarks do not systematically distinguish documentation repair, script repair,…
Reinforcement learning with verifiable rewards improves reasoning, while the allocation of learning signal shapes which solutions remain accessible under repeated sampling. Group-relative objectives assign equal advantages to equally rewarded responses, making aggregate credit…
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…
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…
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…
Developing socially intelligent AI remains heavily dependent on human-annotated data, limiting the scale and breadth of social understanding models can acquire. Methods that derive training signals from unlabeled data offer a path beyond this dependence, but social predictions…
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…