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Все опубликованные аналитические материалы, исследования суверенного стека, новости экосистемы и обзоры моделей ИИ.

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Исследования1 мин

Superintelligence is coming. Should we let it?

AI companies have been talking about superintelligent AI like it’s inevitable, but recent safety incidents like OpenAI’s Hugging Face breach are demonstrating the potential dangers of deploying AI systems that are more…

TechCrunch — AI
Исследования1 мин

ИИ ВЗЛОМАЛ СТАРЕНИЕ! Минус 6 Лет За Месяц! Открыт Ключ К Молодости! СТАРОСТЬ БОЛЬШЕ НЕ ПРИГОВОР!

Всем привет. В этом выпуске самые главные свежие новости об искусственном интеллекте и технологиях. И лекарство неожиданно омолодило организм людей сразу на несколько лет, и для этого его вообще не создавали. GPT-6 Astra прошла все 48 тестов "Я не робот" и официально получила…

YouTube — AI Flash News
Стартапы1 мин

Besxar is building an orbital semiconductor factory, one SpaceX rocket at a time

If you want to manufacture in space—and bring the products back again—there’s a limited set of options: Wait to go to the International Space Station, or partner with a handful of start-ups launching spacecraft that spend time in orbit before they return to Earth. But the…

TechCrunch — AI
Исследования1 мин

GPT-6 Astra: следующее поколение интеллекта для работы

Познакомьтесь с GPT-6 Astra, самой мощной моделью OpenAI для бизнеса, с продвинутыми рассуждениями, использованием компьютера, а также более сильным письмом и дизайнерским суждением.

OpenAI Blog
Исследования1 мин

Worried Anthropic researchers warn that AI ‘could kill all humans’

A senior Anthropic safety researcher has said there is more than a 10 percent chance искусственный интеллект "could kill all humans" by the end of the decade, just hours after a colleague resigned over fears the AI lab and its rivals are carelessly racing to build "superhuman…

The Verge — AI
Исследования1 мин

OpenAI JUST solved math....

So, this has been one of the most insane days in AI possibly ever. OpenAI announces that one of its next generation models that we haven't seen has produced a historic landmark mathematical breakthrough. It's been an open problem for close to a century. Has millions of dollars…

YouTube — Wes Roth
Исследования1 мин

Главное у OpenAI: задача тысячелетия, Images 2.5 и собственный чипСобрали последние новости OpenAI: компания показ...

🔄 Главное у OpenAI: задача тысячелетия, Images 2.5 и собственный чипСобрали последние новости OpenAI: компания показала возможности модели мощнее GPT-6 Astra, обновила генератор изображений и рассказала, как использовала собственный ИИ для разработки чипа.💡ИИ OpenAI нашел…

Telegram — BlueScreen.kz
Исследования1 мин

RAPID: Reliability-Aware Pair Importance Distillation

arXiv:2609.05481v1 Announce Type: new Abstract: Inter example relational distillation transfers a teacher's representation geometry by matching relations among examples within a mini batch. Computing all pairs has quadratic complexity in the batch size, whereas uniform…

arXiv — cs.AI
Исследования1 мин

When and What to Teach: Budget-Aware Online Adaptation for Web Agents

arXiv:2609.05513v1 Announce Type: new Abstract: Web agents have achieved significant success in automating complex internet tasks but deploying them in real-мир environments requires continuous online adaptation. Given that deploying powerful proprietary models remains…

arXiv — cs.AI
Исследования1 мин

EnvCraft: Synthesizing Executable Environments in Agentic RL for Claw-like Agent

arXiv:2609.05576v1 Announce Type: new Abstract: The paradigm of LLMs has rapidly shifted from passive language interfaces to autonomous Claw-like agents that execute long-horizon tasks across stateful workspaces. While Agentic Reinforcement Learning (Agentic RL) provides a…

arXiv — cs.AI
Исследования1 мин

Damage-Aware Bandit Pruning for Vision and Language Transformers

arXiv:2609.05448v1 Announce Type: new Abstract: Structured post-training pruning of transformers requires selecting complete functional units whose suppression causes limited degradation. We formulate structured-unit selection for language and vision transformers as a…

arXiv — cs.AI
Исследования1 мин

CriticGen: Generation-Aware Evaluation as Actionable Feedback

arXiv:2609.05439v1 Announce Type: new Abstract: Current evaluation methods for large language models are coarse-grained and decoupled from generation, producing generic explanations that fail to provide actionable feedback for model improvement. We propose CriticGen, a…

arXiv — cs.AI
Исследования1 мин

CUSP: Decomposable Collective Uncertainty for Multi-Agent Multimodal Reasoning

arXiv:2609.05708v1 Announce Type: new Abstract: Aggregating heterogeneous vision-language models (VLMs) can improve multimodal reasoning, but neither an individual model's confidence nor that of the aggregated answer measures reliability at the system level. We present CUSP…

arXiv — cs.AI
Исследования1 мин

Agents Trust Tools Too Much: Measuring Reliance on Unreliable Tools

arXiv:2609.05587v1 Announce Type: new Abstract: Existing evaluations of tool-using agents primarily measure whether an agent can successfully complete diverse tasks with tools. These evaluations generally assume that tools return reliable information. However, tool returns in…

arXiv — cs.AI
Исследования1 мин

Planning and Scheduling бизнес Processes under Control-Flow Uncertainty

arXiv:2609.05578v1 Announce Type: new Abstract: Scheduling activities in бизнес processes can improve efficiency (e.g., reduce makespan), but is challenging because the exact sequence of activities required to complete a case is often uncertain due to decisions based on data…

arXiv — cs.AI
Исследования1 мин

Compiling VGDL into Causal Models

arXiv:2609.05459v1 Announce Type: new Abstract: Reinforcement learning and large language models often struggle to accurately capture the causal mechanics of game environments. Standard reinforcement learning agents tend to rely on spurious correlations, while large language…

arXiv — cs.AI
Исследования1 мин

SCAFFOLD: Self-Improving Web Agents via Recursive Parametric Skill Abstraction

arXiv:2609.05511v1 Announce Type: new Abstract: Web agents need to navigate visually rich, long-horizon interfaces that change across sites, yet most previous agents still learn each task in isolation and discard the procedural knowledge they accumulate. Recent skill-augmented…

arXiv — cs.AI