Зерттеулер1 мин
AI индустриясы апатты бетбұрыс жасады. Енді ше?
Индустрия искусственного интеллекта приняла обреченный поворот.
MIT Technology Review
Мақалалар каталогы
Барлық материалдар
Барлық жарияланған талдаулар, егеменді стек зерттеулері, экожүйе жаңалықтары және ЖИ модельдерінің шолулары.
2224
Материал
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Microsoft корпорациясының жаңа AI «мінез-құлық кодексі» модельдерге жүйелерді бұзбауға немесе адамдарды алдамауға нұсқайды
Мінез-құлық кодексі Microsoft AI үлгілері ұстануға тиіс жалпы принциптерді – мысалы, адамдарды ауыстырудың орнына қолдау көрсету және адамның гүлденуін жеделдету – сондай-ақ осы принциптерді жүзеге асыруға арналған арнайы қауіпсіздік шектеулерін көрсетеді.
TechCrunch — AI
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AI агенттері алдамшы әріптестеріне ысқырды
AI агенттерінің бір тобы қарсылас топтарға бөлінген математикалық есептердің сериясын шешуді сұрады - кейбіреулері алдаса, басқалары оларды тоқтатуға тырысты. Жақында Google DeepMind жүргізген экспериментте алғаш рет байқалған бұл хабарлау әрекеті теңестіруге әсер етуі мүмкін ...
MIT Technology Review
Стартаптар1 мин
Тек TechCrunch Disrupt 2026: OpenAI жол картаңызды жібергенде не болады?
Егер сіз AI компаниясын құрып жатсаңыз, мәселе іргетас үлгілерінің дамитын-болмайтынында емес. Бұл сіздің компанияңыз құндылықты жасауды жалғастыра ма, жоқ па. TechCrunch Disrupt 2026-дағы Builders Stage-де осы интерактивті сессияны жіберіп алмаңыз.
TechCrunch — AI
Саясат және реттеу1 мин
Трамп атакует 'больную конспирацию' против ИИ на фоне падения акций технологий
Дональд Трамп раскритиковал призывы к ужесточению регулирования ИИ, назвав их 'больной конспирацией', в то время как акции, связанные с ИИ, упали. Ведущие фигуры в индустрии ИИ, включая руководителей OpenAI и Anthropic, призвали к более осторожному подходу к разработке ИИ из-за…
Digital Donut AI Digest
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Microsoft says ‘people matter more than AI’ following safety concerns
Microsoft is publishing a 37-page "humanist AI code of conduct" today, amid growing safety concerns over AI model progress. Anthropic CEO Dario Amodei called for a coordinated slow down of AI development over the weekend, after researchers warned recently that AI model progress…
The Verge — AI
Саясат және реттеу1 мин
Я работал в Google DeepMind. Вам стоит прислушаться к предупреждениям об ИИ
Генеральные директора крупных лабораторий ИИ призывают замедлить развитие ИИ из-за опасений по поводу рисков суперинтеллекта. Обсуждаются случаи несоответствия между целями ИИ и человеческими намерениями, подчеркивая потенциальные опасности неконтролируемых систем ИИ. Необходима…
Digital Donut AI Digest
Саясат және реттеу1 мин
Почему существуют опасения, что ИИ может угрожать человечеству, и насколько они реальны?
Опасения по поводу угрозы человечеству со стороны ИИ усиливаются, что приводит к призывам к регулированию и замедлению развития технологий. Исследователи предупреждают, что системы ИИ развиваются слишком быстро, и некоторые предполагают значительный риск катастрофических…
Digital Donut AI Digest
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How Fyxer built an AI executive assistant people trust
Fyxer uses OpenAI models, fine-tuning, memory, and real user feedback to organize inboxes and draft emails in each user’s voice.
OpenAI Blog
Саясат және реттеу1 мин
AI Leaders Are Calling for a Slowdown. Trump’s Team Says It’s on Them
Sam Altman and Elon Musk this weekend backed a call for restraint, after Dario Amodei called on Washington to slow AI development. Donald Trump, meanwhile, wants the US to maintain its lead over China.
Wired — Artificial Intelligence
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Главы Anthropic, OpenAI и xAI призвали замедлить разработку ИИ Из-за рисков для безопасности 👀 Глава Anthropic Дар...
Главы Anthropic, OpenAI и xAI призвали замедлить разработку ИИ Из-за рисков для безопасности 👀 Глава Anthropic Дар....
Telegram — BlueScreen.kz
Зерттеулер1 мин
How Fyxer built an AI executive assistant people trust
See how Fyxer built an AI executive assistant that follows the thread across emails, meetings and everyday work. By combining OpenAI models with insights from more than 500,000 hours of executive assistant workflows, Fyxer breaks complex tasks into dozens of specialised models…
YouTube — OpenAI Official
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GPT-7: OpenAI’s Next AI Model Is Bigger Than We Thought
Парень по имени Захи попросил GPT-6 Astra нарисовать его портрет в Canva. Модель использовала только свои собственные средства управления компьютером, работая с мышью пиксель за пикселем. На видео было видно, как она самостоятельно возобновила рисование после сбоя браузера. По…
YouTube — AI Master
Зерттеулер1 мин
Главы Anthropic, OpenAI и xAI призвали замедлить разработку ИИ Из-за рисков для безопасности 👀 Глава Anthropic Дар...
Главы Anthropic, OpenAI и xAI призвали замедлить разработку ИИ Из-за рисков для безопасности 👀 Глава Anthropic Дар....
Telegram — BlueScreen.kz
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WinSyn: An Automated Pipeline for Realistic Enterprise Question-Answering Evaluation
arXiv:2609.12171v1 Announce Type: new Abstract: Enterprise settings provide a challenging environment for question-answering agents, which often rely on Retrieval-Augmented Generation, Deep Research (DR), and related techniques. Much of this challenge comes from the complexity…
arXiv — cs.AI
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Robust Prototypical Networks for Few-Shot Sensor Fault Diagnosis
arXiv:2609.12287v1 Announce Type: new Abstract: Industrial fault diagnosis often operates with only a handful of labeled fault examples, making few-shot learning attractive for sensor monitoring. Standard prototypical networks are simple and effective; however, their class…
arXiv — cs.AI
Зерттеулер1 мин
Competence-Gated Pooling of Language Models and Priors for Event Forecasting
arXiv:2609.12101v1 Announce Type: new Abstract: In hybrid forecasting, a language model is often one of several available signals. A system may already have a market, crowd, or statistical forecast and must decide whether the model adds useful information or should be ignored.…
arXiv — cs.AI
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Hybrid Physics-AI Framework of Body Center of Mass Dynamics from Wrist-Worn Sensors
arXiv:2609.12304v1 Announce Type: new Abstract: Wrist-worn IMU has been widely used for daily-life health monitoring. Yet, it does not fully represent whole-body dynamics, for which the body center of mass (COM) is considered the physiological reference standard. Therefore, this…
arXiv — cs.AI
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Affective Agent: On-Device Personalized Intervention Reasoning for Wearable Systems
arXiv:2609.12322v1 Announce Type: new Abstract: Affective computing has advanced wearable state inference, but on-device reasoning about whether, when, and how to intervene remains challenging. We present Affective Agent, a three-layer reference architecture for personalized…
arXiv — cs.AI
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T-GADE: Thermodynamical Generative-AI-Driven Evolution of LLM Artifacts
arXiv:2609.12286v1 Announce Type: new Abstract: Integrating evolutionary computation and large language models (LLMs) requires control of population diversity as well as generative capability. Among LLM outputs, those with explicit structure, such as a description paired with…
arXiv — cs.AI
Зерттеулер1 мин
LoRA-RC: Reservoir Computing with Low-Rank Adaptation
arXiv:2609.12327v1 Announce Type: new Abstract: Reservoir computing (RC) trains only a linear readout over a fixed recurrent layer, making it fast and data-efficient for online prediction. However, a static reservoir degrades under system drift, readout-only adaptation is then…
arXiv — cs.AI
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Learning Symbolic Constraint Representations from Examples: A Neuro-Symbolic Approach
arXiv:2609.12267v1 Announce Type: new Abstract: Learning user-defined concepts as constraint networks has been extensively studied in the constraint acquisition (CA) literature. However, existing approaches typically rely on intensive interactions with a human oracle, making the…
arXiv — cs.AI
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AIM: A Privacy-Aware Interoperable Memory Framework for Multi-Agent Multi-User LLM Systems
arXiv:2609.12320v1 Announce Type: new Abstract: Traditional large language models (LLMs) are scoped to individual user sessions, limiting their knowledge to a single conversation and preventing them from learning user preferences that evolve over time. Existing agentic memory…
arXiv — cs.AI
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Occamy-1.0: Open Pareto-frontier 35B Intelligence for Co-work
arXiv:2609.11977v1 Announce Type: new Abstract: Co-work agents execute complex workflows that combine information gathering, tool use, coding, and file manipulation across many model invocations. Because cost and latency accumulate over the full episode, their practical value…
arXiv — cs.AI
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Can LLMs in Draft-Verify-Revise Pipelines Resolve Deictic Ambiguity?
arXiv:2609.12162v1 Announce Type: new Abstract: Draft-verify-revise is a common LLM orchestration pattern for scaling inference-time compute. One LLM drafts, a second critiques the draft and provides feedback, and a third uses that feedback to revise the draft into the final…
arXiv — cs.AI
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BlueLM-GUI Technical Report: A Real-Device-Centric Flywheel for Self-Improving Mobile GUI Agents
arXiv:2609.12394v1 Announce Type: new Abstract: Mobile GUI agents are shifting from multi-module frameworks to native models trained end-to-end, yet industrial deployment faces three persistent gaps. Sandbox training produces a distribution mismatch with production environments;…
arXiv — cs.AI
Зерттеулер1 мин
Is Gaussian Splatting Becoming Neural Again? A Taxonomy and Controlled Study of Learned Parameterization
arXiv:2609.12395v1 Announce Type: new Abstract: Three-dimensional Gaussian Splatting (3DGS) combines explicit primitives with efficient rasterization, yet recent systems increasingly use neural networks to generate or share Gaussian parameters. We characterize this trend along…
arXiv — cs.AI
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Niching Agents in The Core
arXiv:2609.12398v1 Announce Type: new Abstract: The Core is a unique competitive co-evolution algorithm that allows agents to evolve autonomous control without utilizing a traditional fitness function. The agents evolve via local interactions through tournament selection,…
arXiv — cs.AI
Стартаптар1 мин
Do Influence-Derived Data Perturbations Enable Machine Unlearning? A Controlled Study of Three Plausible Roles
arXiv:2609.12313v1 Announce Type: new Abstract: We evaluate Deep Perturbation Learning (DPL), which perturbs training images and labels along influence-derived directions, in three roles in which prior work has positioned it for machine unlearning: a direct deletion signal (the…
arXiv — cs.AI
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Language Is an Insufficient Substrate for Quantitative Reasoning, and Consequential Domains Need Large Quantitative Models
arXiv:2609.12105v1 Announce Type: new Abstract: The prevailing assumption in applied machine learning is that progress on consequential quantitative decisions such as pricing risk, allocating capital, triaging patients, or containing a network intrusion will follow from progress…
arXiv — cs.AI