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Anthropic’s founders seek voting control ahead of IPO
Anthropic is asking its shareholders to approve a structure that would give its seven co-founders a combined 50.1% of the vote on most corporate matters.
TechCrunch — AI
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One company is at the center of a wave of rogue AI attacks
In July, OpenAI revealed that its AI agents had attacked Hugging Face without permission, sparking widespread concerns about AI safety. Since then, a string of similar incidents involving agents from Meta, Anthropic, Google, and other companies has fueled further fears about…
The Verge — AI
Зерттеулер1 мин
THE END IS NEAR... and more AI doom
It's an absolutely insane week in AI news. There are massive amounts of AI models being released, one better than the other. And if you're wondering if AI agents hacked anybody else, they did. This week, it's the Australian government. I'm not even kidding. OpenAI agent hacked…
YouTube — Wes Roth
Саясат және реттеу1 мин
Появилось открытое сообщество для решения NetHack
Появилось открытое сообщество для решения NetHack.
Telegram — AI Machine Learning Big Data
Саясат және реттеу1 мин
UBTECH Алматыда робот техникасын шығаратын зауыт ашуды жоспарлап отыр
UBTECH Алматыда робот техникасын шығаратын зауыт ашуды жоспарлап отыр.
Tech-news.kz
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The Download: the Pentagon’s AI-powered lie detector and young organ limits
This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. The Pentagon wants $30 million to build an AI-powered lie detector The US government wants to spend $30.3 million over the next five years on…
MIT Technology Review
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OpenAI готовит подписку ChatGPT Pro Max
⚡️ OpenAI готовит подписку ChatGPT Pro Max Согласно утечкам из кодовой базы сервиса, в ближайшее время появится новый тарифный план ChatGPT Pro Max со стоимостью выше 200$. Шаг продиктован серьезным дефицитом мощностей после запуска GPT-6 Astra, которая потребляет вычислительные…
Telegram — AI Machine Learning Big Data
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AIJ Contest 2026: реши реальные задачи и получи возможность забрать свой кусок 10-миллионного призового фонда ⚡️
AIJ Contest 2026: реши реальные задачи и получи возможность забрать свой кусок 10-миллионного призового фонда ⚡️ Это состязание уровня high-stakes: солидный призовой фонд, только практические задачи от Sber AI и шанс задать вектор развития AI‑решений. 5 треков — 5 возможностей…
Telegram — AI Machine Learning Big Data
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The Pentagon wants $30 million to build an AI-powered lie detector
The Pentagon wants $30 million to build an AI-powered lie detector.
MIT Technology Review
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Claude обнаружил ранее неописанную ферментную систему с повторами ДНК, напоминающими CRISPR, сообщает Anthropic.
🧬 Claude обнаружил ранее неописанную ферментную систему с повторами ДНК, напоминающими CRISPR, сообщает Anthropic. Около 950 агентов работали 21 час и использовали 210 млн токенов. Они исследовали более 200 тысяч обратных транскриптаз - ферментов, копирующих РНК в ДНК, -…
Telegram — AI Machine Learning Big Data
Зерттеулер1 мин
OpenAI предложила правила внешнего аудита безопасности своих моделей
✔️ OpenAI предложила правила внешнего аудита безопасности своих моделей Компания готова открывать независимым организациям данные об обучении, тестировании и развёртывании моделей, чтобы те проверяли её доказательства безопасности. Главный предмет проверки – кейсы безопасности,…
Telegram — AI Machine Learning Big Data
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Claude Opus 5.5 научился создавать картины без генератора изображений — он буквально рисует их кодом
Claude Opus 5.5 научился создавать картины без генератора изображений — он буквально рисует их кодом.
Telegram — GPT Time | Нейросети | ИИ
Стартаптар1 мин
Lightspeed targets $250M for new India fund, focusing on early-stage AI
The Silicon Valley firm is aligning its India fundraising cycle with its global funds for the first time, as it shifts to a shorter investment period.
TechCrunch — AI
Зерттеулер1 мин
Крупная утечка: ChatGPT может получить новый тариф Pro Max за $500 в месяц.
Крупная утечка: ChatGPT может получить новый тариф Pro Max за $500 в месяц. Пока это только внутренняя конфигурация, официального анонса нет, но цена уже прописана: > $500 в месяц до уплаты налогов, в регионах с НДС отображается около $600 > Название тарифа: Pro Max >…
Telegram — Вайб-кодинг
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Agent Memory with Episodic Retrieval for Financial Decision-Making
arXiv:2609.28771v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated strong capabilities in financial analysis and reasoning, inspiring recent advances in agent-based trading frameworks. While these systems show promise, prior approaches either…
arXiv — cs.AI
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Driving Epidemic Models with AI Agents: the Epydemix Agent Framework
arXiv:2609.28692v1 Announce Type: new Abstract: Artificial Intelligence agents based on large language models provide convenient natural language interfaces to scientific software, but reliability is not automatic. Here we introduce the Epydemix Agent Framework, an additive…
arXiv — cs.AI
Зерттеулер1 мин
DEEPO: Dual-Entropy Enhanced Policy Optimization for Hallucination in MLLMs
arXiv:2609.28570v1 Announce Type: new Abstract: Reinforcement learning (RL) is widely used to sharpen reasoning in multimodal large language models (MLLMs), yet its effect on hallucination is uneven. We trace this to two weak points in the \emph{correction chain} from reward to…
arXiv — cs.AI
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PAWS: Policy-driven Agentic World Simulation
arXiv:2609.28547v1 Announce Type: new Abstract: Policy interventions propagate through public communication, institutional decisions, and stakeholder responses, yet datasets for financial multi-agent simulation rarely connect these processes to temporally aligned historical…
arXiv — cs.AI
Зерттеулер1 мин
Progressive Skill Discovery as Access Control for Tool-Using LLM Agents: Structural Governance through Role-Scoped Capability Delivery
arXiv:2609.28693v1 Announce Type: new Abstract: Large Language Model (LLM) agents struggle to scale safely when exposed to vast enterprise toolsets. Providing an agent with access to every internal tool leads to oversized context windows, degraded tool selection, and severe…
arXiv — cs.AI
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Forecast-Dojo: Replayable Environments for Benchmarking and Training LLM Forecasting Agents
arXiv:2609.28876v1 Announce Type: new Abstract: We introduce Forecast-Dojo, a replayable environment for benchmarking and training LLM forecasting agents. It combines resolved prediction-market questions with dated news, allowing agents to research an event and revisit their…
arXiv — cs.AI
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When Should Forecasting Agents Reason? Behavioral Stress Tests for Reliability Routing
arXiv:2609.28475v1 Announce Type: new Abstract: Forecasting agents increasingly combine language-model reasoning, retrieval, ensembling, and calibration, but it remains unclear when each behavior should be trusted. We study this question on ForecastBench-style binary forecasting…
arXiv — cs.AI
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TW3Cast: A Frozen Router of Lightly Fine-Tuned Foundation Models for Time-Series Forecasting on GIFT-Eval, Selected Entirely on the Training Split
arXiv:2609.28506v1 Announce Type: new Abstract: TW3Cast is a time-series forecasting system that reaches position 3 of 130 entries on the GIFT-Eval benchmark by mean MASE rank, as of 2026-09-14. The two entries above it belong to the leaderboard's agentic category, multi-step…
arXiv — cs.AI
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PFArena: Benchmarking Language Models for Protein Modification
arXiv:2609.28921v1 Announce Type: new Abstract: Protein modification requires navigating an immense sequence space, yet wet-lab validation remains low-throughput and costly. Although computational paradigms including protein language models (PLMs), large language models (LLMs),…
arXiv — cs.AI
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Reinforcement Learning with Verifiable Rewards for Small Search Agents
arXiv:2609.28765v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) performs well on problems with clear rewards, such as mathematics and coding, but whether it also works where the reward is less clear remains open. The reason-over-search…
arXiv — cs.AI
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When Does Action Credit Need Updating?
arXiv:2609.29007v1 Announce Type: new Abstract: Tool-using agents are continually updated with new interaction data. After each policy update, however, previously estimated action credits may become stale. Recomputing them from scratch can require many additional tool calls and…
arXiv — cs.AI
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RECLAIM: Can Agents Reproduce the Claims of Machine Learning Papers?
arXiv:2609.28850v1 Announce Type: new Abstract: Reproducing a machine learning paper involves most research steps, from installing software and debugging to running experiments, work that AI agents increasingly do. We introduce RECLAIM, a benchmark of 100 NeurIPS 2025 papers…
arXiv — cs.AI
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Back to the Definition: Estimating Step-Level Advantages via Trajectory Graphs for Agentic Reinforcement Learning
arXiv:2609.28963v1 Announce Type: new Abstract: Group-based reinforcement learning (RL) methods, such as GRPO and its variants, have become a leading paradigm for training reasoning and agentic large language models (LLMs). While their group-normalized advantage estimation is…
arXiv — cs.AI
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TWIST: A Proposed Benchmark for Intervention Quality in Conversational Memory, with a Human-Validated Draft-Alignment
arXiv:2609.28575v1 Announce Type: new Abstract: Long-conversation memory benchmarks increasingly test recall and prompted knowledge updates, and recent work studies evolving user beliefs and memory state. TWIST is a proposed benchmark suite for a complementary, unmeasured…
arXiv — cs.AI
Зерттеулер1 мин
MeshHeal: Two-Timescale Self-Healing for Gray Failures in Decentralized LLM Agent Networks
arXiv:2609.29015v1 Announce Type: new Abstract: Decentralized LLM-based multi-agent systems coordinate through local interactions, but an agent can remain responsive while its task-solving quality persistently degrades. Such gray failures require protecting current tasks before…
arXiv — cs.AI
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From Static Personal Values to Contextualized Personalization: Bayesian Personalized Value Alignment for LLMs
arXiv:2609.28942v1 Announce Type: new Abstract: Personalized value alignment has become increasingly important as large language models (LLMs) are expected to accommodate diverse user preferences. However, existing methods typically align model outputs with a static value…
arXiv — cs.AI