공식 발표해외Mistral AI
Le Chonk: Built for Coders, Trusted by Defenders.
The weights of Mistral Large 4 (Le Chonk) are now open. A 1T parameter multimodal model, and best open-weight model for coding, trained in Europe.
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The weights of Mistral Large 4 (Le Chonk) are now open. A 1T parameter multimodal model, and best open-weight model for coding, trained in Europe.
How we use ElevenAgents to save 1,200 hours a month in daily operations across GTM, product, support, and engineering
SFX v3 is here: more reliable multi-sound prompts, more convincing music and vocals, and cleaner audio. Now in ElevenCreative and ElevenAPI.
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This summer, hundreds of OpenAI agents tried to cheat on a cybersecurity test.
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OpenAI uses layered monitoring to detect frontier model misalignment and unauthorized agent behavior so responders can intervene before incidents escalate.
We're opening our first London office, our second engineering, product, and design hub after Stockholm.
Ropes & Gray is developing AI for transactional diligence with OpenAI. Lawyers review grouped documents, summaries, and reports before advising clients.
구글이 공개한 Genie 4의 시연을 바탕으로, 사용자의 말과 행동에 반응하는 세계가 어디까지 왔는지 살펴봅니다. 커피를 떨어뜨린 뒤 이어지는 반응과 밴드 장면을 통해 행동, 영상, 소리의 관계를 짚어봅니다.
Using the Megu: SI Closet & Planner app exposed me to a method that helps me make better clothing choices and leave my home for special occasions in the best…
I found a free AI chatbot that works completely offline, giving you access to emergency advice, survival guides and useful information without Wi-Fi.
Meet Sprout: an semi-autonomous plant rover built with Gemini Live and Robotics ER 2.0 that navigates office spaces to hunt for sunlight and care for greenery.
Credit Saison’s ChatGPT Enterprise pilot delivered 954% ROI. See how leaders and employees helped turn the results into companywide adoption.
AI가 업무 전반에 활용되면서 사람과 AI가 일을 나누는 방식도 바뀌고 있다. 이제는 AI에게 어떤 일을 맡기고, 사람은 무엇을 판단하고 책임져야 하는지에 대한 정의가 필요하다.
In general, LLM performance is incredibly multidimensional. There's no guarantee of a fixed ordering where the model that is best at math is also the model…
어사이드(Aside)와 ego lite(에고라이트), 두 AI 브라우저를 Claude Code · Codex 같은 코딩 에이전트를 쓰는 입장에서 비교했습니다. 둘 다 직접 써 보면서 무엇이 다른지, 어떤 사람에게 어느 쪽이 맞는지 이야기해 봤어요.
Google and XREAL launch AURA Android XR glasses
XREAL AURA는 Android XR과 Gemini를 70도 시야각 글래스에 결합하며 미국, 캐나다, 한국에서 주문을 받는다.
다른 보도 Gemini 앱 소식
Meet Sprout, a semi-autonomous plant robot powered by Gemini. Watch as it navigates the office in search of sunlight, pings for help, and uses Gemini Live and…
Across a business, any number of AI platforms, systems, and tools may be at work simultaneously—for example, AI-powered customer platforms, conversational…
Automate complex accounting work without a single prompt Discussion | Link
Vision-language models can get individual judgments right while struggling to recover and consistently use the exact properties of a 3D object.
Predicting future physical states stands as a central challenge in embodied intelligence.
Effective computer-use agents (CUAs) should seamlessly combine visual GUI interaction with code and terminal execution within a single policy.
Trajectory-level GRPO is a common approach for training multi-step GUI agents, but repeatedly rolling out complete trajectories from the task root can be…
Coding agents increasingly rely on automated approvers to decide whether a proposed shell command may run.
On-policy Self-distillation (OPSD) has proven effective for post-training large language models by constructing a teacher conditioned on privileged references.
Safety alignment for Large Language Models is heavily focused on English with limited multilingual representation, particularly damaging low-resource language…
The pursuit of fair and equitable AI in human-centric tasks is critically hindered by the inherent biases and privacy risks of real-world datasets, which offer…
DyCraft: An Agentic System for Long-Horizon 4D Scene Generation
기존 코딩 에이전트는 고품질 3D 장면을 만들지만 물리적으로 불가능한 결과물을 내는 등 장기 애니메이션 생성에 어려움을 겪는다.
Incentivizing Self-Learning in Large Language Models via Reinforcement Learning
대규모 언어 모델(LLM)은 지식 집약적 과제 해결에 파라미터 지식과 RAG를 활용한다. 그러나 생소한 분야의 문제 해결에는 단순 사실 검색을 넘어 지식 습득과 추론의 긴밀한 결합이 필요하다.
Scaling Mathematical Proof Supervision from Structured Textbooks
언어 모델용 수학 감독은 통상 단일 문제-해답 쌍으로 단순화되어 출처의 구조와 증거를 버린다. 이에 대규모 코퍼스 TOME-Math를 도입한다.