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Зерттеулер1 мин

OpenAI's model just JAILBROKE ITSELF...

So, OpenAI posted their framework for tracking, investigating, and disclosing instances of model misalignment at OpenAI. And we'll talk about that in just a little bit. But here's the thing. They've published six reports of instances where AI agents behaved, you know, in a…

YouTube — Wes Roth
Зерттеулер1 мин

Google DeepMind launches institute to widen the AGI debate

The new institute aims to surface differing views between Google, Google DeepMind, and the broader global research community around AGI. "They will not always agree, and they will likely change their minds, as more data and information comes to light at the fast-moving frontier."

TechCrunch — AI
Зерттеулер1 мин

The AI Superintelligence Slowdown

Remember when tech leaders would tell their employees to “move fast and break things”? It seemed that would be the way of AI too. But after a summer where rogue AI agents became reality, and researchers warned that AI could kill us all, a number of leading US AI companies are…

The Verge — AI
Зерттеулер1 мин

The AI Slowdown Debate Crashed Salesforce’s Party

The Dreamforce conference became an unlikely battleground for the CEOs of OpenAI, Anthropic, and Nvidia to debate whether AI development should slow down.

Wired — Artificial Intelligence
Зерттеулер1 мин

LLMs respond differently to harmful prompts when AI watermarking is used

In response to a new European Union law, AI platforms are implementing new schemes for watermarking the content they generate. Anthropic recently disclosed its future Claude models will use SynthID-Text, an approach Google created and released as open source. It uses a secret…

Ars Technica — AI
Зерттеулер1 мин

Ресейлік орындаушылардың жүздеген әндері AI үйретуге арналған шетелдік деректер жинағында табылды - авторлық құқық иелері ...

🎵 AI үйретуге арналған шетелдік деректер жинағында ресейлік орындаушылардың жүздеген әндері табылды - авторлық құқық иелері рұқсат берілмеді деп мәлімдейді. Ұлттық музыкалық индустрия федерациясының сарапшылары екі ашық дерекқорды зерттеді - Laion-Disco-12M және Sleeping-D 9M, барлығында...

Telegram — GPT Time | Нейросети | ИИ
Зерттеулер1 мин

OpenAI Показала Нечто ОПАСНЕЕ AGI. Больше Чем ASI. Новая Угроза Человечества! Запущен Новый Цикл ИИ!

Всем привет. В этом выпуске самые главные свежие новости об искусственном интеллекте и технологиях. И приближается к новому рубежу. Модели начинают помогать создавать более совершенные версии самих себя. И агенты теперь могут доносить на другие нейросети, если замечают…

YouTube — AI Flash News
Зерттеулер1 мин

DeepSeek V4.1 Flash: хайп vs реальность. Тестирую модель, которую называют «убийцей топов»

Привет. И сегодня у нас на тесте первый раз псик на моём канале. Я по разным причинам, которые я не озвучиваю, я его саботирую. Но в этот раз саботировать Deeps не удалось, потому что модель довольно хайповая получилась, да. Deepsic 4.1 Flash вроде как по бенчмаркам, по разным…

YouTube — Amorev
Саясат және реттеу1 мин

Microsoft AI CEO says AI threats are real, and Anthropic is making it worse

Today, I’m talking with Mustafa Suleyman, the CEO of Microsoft AI. As you’re no doubt aware, the biggest story in tech right now is the spiraling debate about AI safety and regulation. It should come as no surprise that Mustafa has strong opinions on how AI should be built and…

The Verge — AI
Зерттеулер1 мин

Anthropic IPO-ның мағынасы жоқ

Бұл Anthropic бір мезгілде: «Ей, біз алдымен жоспарымыз жоқ, оны қалай басқаруға болатын ағымдағы жоспарымыз жоқ, бүкіл адамзатты жою мүмкіндігі бар нәрсені салып жатырмыз, және айтпақшы, біз бірнеше аптадан кейін IPO-ға шығамыз». Мысалы, сіз маған осы логиканы түсінуге көмектесе аласыз ба?…

YouTube — Matthew Berman
Зерттеулер1 мин

Большая новость в ИИ.

Google продемонстрировала цикл рекурсивного самоулучшения.

Telegram — Вайб-кодинг
Зерттеулер1 мин

Imitation Learning for Autonomous Driving in CARLA

Behavioral cloning trains a policy offline on expert demonstrations, but deployment is closed loop: each action affects the observations the policy receives next. We study how much closed-loop driving competence a compact multimodal policy can acquire from offline demonstrations…

arXiv — cs.AI
Зерттеулер1 мин

Learning Heterogeneous Preferences

Learning from human feedback has become a central paradigm for training modern AI systems, where models of human utility are used as reward models in policy learning. Existing methods typically assume a \emph{universal utility} function shared across a population and treat…

arXiv — cs.AI
Зерттеулер1 мин

SAGE: Governed Artifact Generation from Enterprise Guidelines

Enterprise guideline documents mix narrative text, complex tables, and embedded images, and converting them into structured work artifacts still takes two to three days of manual effort each. Current language and vision-language models extract from such documents but offer no…

arXiv — cs.AI
Зерттеулер1 мин

GVD: Governed Versioning and Deduplication for Document Repositories

Document repositories evolve continuously. Guidelines and policies are revised, superseded, and re-uploaded, so the same content recurs in different wording and newer versions refine or contradict earlier ones. These inconsistencies belong to the growing collection rather than…

arXiv — cs.AI
Зерттеулер1 мин

CapMem: A Benchmark for Caption-Based Episodic Memory in Egocentric Video

Wearable assistants require episodic memory over egocentric video, yet current vision-language models face bounded frame budgets, growing visual-token costs, and long-context retrieval failures. Under these practical constraints, we study whether textual captions can serve as…

arXiv — cs.AI
Зерттеулер1 мин

SNOMED CT Concept Recommendation from Masked Clinical Context

Standardizing clinical language to SNOMED CT supports interoperability, analytics, and reusable phenotyping, but concept recommendation remains difficult when relevant concepts are rare or absent from training data. We present a masked-concept recommendation benchmark using the…

arXiv — cs.AI
Зерттеулер1 мин

Collaborative Memory for Multi-Agent VLM Systems

Vision-language model (VLM) agents combine specialized perception, tools, and reasoning to address complex visual tasks. In multi-agent settings, different agents inspect different image regions, video frames, or visual representations, so collaboration extends beyond…

arXiv — cs.AI
Зерттеулер1 мин

A Systematic Evaluation of the COTQ Provincial Land Cover Product: Structural Consistency, Spectral Separability, and Relative Positioning Against ESA, ESRI, and Google Products

High-resolution land use and land cover (LULC) products derived from Sentinel-2 imagery are widely used for environmental monitoring and land management, yet their performance can vary across regions with complex ecological gradients and heterogeneous surface conditions. In…

arXiv — cs.AI