-
Waypoint-1.5: 일반 GPU를 위한 고충실도 인터랙티브 월드
Waypoint-1.5: Higher-Fidelity Interactive Worlds for Everyday GPUs
-
Safetensors가 PyTorch 재단에 합류합니다
Safetensors is Joining the PyTorch Foundation
-
FOD#147: Can your OpenClaw dream? - by Ksenia Se
Two stories about the inner life of AI that deserve to be read together. Plus all other amazing news, models and research from the last week
-
Import AI 452: 사이버전쟁의 확장 법칙, AI 자동화의 급증, 그리고 GDP 예측의 미스터리
Import AI 452: Scaling laws for cyberwar; rising tides of AI automation; and a puzzle over gDP forecasting
How much could AI revolutionize the economy?
-
#2: The Unsexy Truth of AI Adoption - by Ksenia Se
Institutional redesign, step by step: how companies actually become ready for AI
-
코딩 에이전트의 구성 요소 - Sebastian Raschka 박사
Components of A Coding Agent - by Sebastian Raschka, PhD
How coding agents use tools, memory, and repo context to make LLMs work better in practice
-
🎙️ Be Bold, Stay Safe: How NVIDIA Is Engineering the Hardest Tradeoff in Self-Driving
A field guide to DRIVE AV, Halos, Hyperion, Alpamayo, and the path from Level 2 to Level 4
-
AI 101: Hermes Agent – OpenClaw’s Rival? Differences and Best Use Cases
A breakdown of the new self-improving local agent – and why it’s now a main competitor to OpenClaw
-
Gemma 4: 바이트 대 바이트, 가장 강력한 오픈 모델
Gemma 4: Byte for byte, the most capable open models
Gemma 4: Our most intelligent open models to date, purpose-built for advanced reasoning and agentic workflows.
-
Gemma 4 환영합니다: 기기 내 최첨단 멀티모달 지능
Welcome Gemma 4: Frontier multimodal intelligence on device
-
팔콘 인식
Falcon Perception
-
Gradio 백엔드를 이용한 커스텀 프론트엔드
Any Custom Frontend with Gradio's Backend
-
그래나이트 4.0 3B 비전: 엔터프라이즈 문서용 소형 멀티모달 인공지능
Granite 4.0 3B Vision: Compact Multimodal Intelligence for Enterprise Documents
-
25개 종의 mRNA 언어 모델을 $165로 학습하기
Training mRNA Language Models Across 25 Species for $165
-
FOD#146: Stop Telling Kids AI Will Steal Their Future
From the lump-of-labor fallacy to today’s worker shortages + our curated list of news and research papers
-
TRL v1.0: 분야와 함께 성장하는 포스트-트레이닝 라이브러리
TRL v1.0: Post-Training Library Built to Move with the Field
-
Import AI 451: 정치적 초지능; 구글의 마음의 사회, 그리고 로봇 드러머
Import AI 451: Political superintelligence; Google's society of minds, and a robot drummer
Are there any genies that can be put back in the bottle?
-
마우스 포인터의 재상상으로 AI 상호작용의 미래를 열다 – Google DeepMind
Shaping the future of AI interaction by reimagining the mouse pointer â Google DeepMind
Google DeepMind is transforming the mouse pointer into a context-aware AI partner. Move beyond the friction of traditional prompting with intuitive AI collaboration in Chrome and b…
-
OpenClaw을 자유롭게 활용하세요
Liberate your OpenClaw
-
Gemini 3.1 Flash Live: 더욱 자연스럽고 신뢰할 수 있는 음성 AI
Gemini 3.1 Flash Live: Making audio AI more natural and reliable
Our latest voice model has improved precision and lower latency to make voice interactions more fluid, natural and precise.
-
AI 101: Transformers Depth Is an Addressable Dimension
Deep transformers used to accumulate layer history. Now they are starting to retrieve from it.
-
사람들을 해로운 조작으로부터 보호하기 – Google DeepMind
Protecting People from Harmful Manipulation â Google DeepMind
Google DeepMind researches AI's harmful manipulation risks across areas like finance and health, leading to new safety measures.
-
Lyria 3가 더 많은 Google 제품으로 확장되며 새로운 기능 추가
Lyria 3 expands to more Google products, adds more features
Introducing Lyria 3 Pro, which unlocks longer tracks with structural awareness. We’re also bringing Lyria to more Google products and surfaces.
-
FOD#145: What 100,000 Subscribers Taught Us About the Future of Turing Post
What we’re doubling down on, what we’re postponing, and where Turing Post goes next
-
#1: AI Feels Powerful. So Why Is the ROI Still Missing?
Why workflow redesign is necessary? In the new series: The Org Age of AI
-
Import AI 450: 중국의 전자전 모델; 트라우마 입은 LLM들; 사이버 공격의 확장 법칙
Import AI 450: China's electronic warfare model; traumatized LLMs; and a scaling law for cyberattacks
How will timeless minds value time?
-
🎙️The New Inner Loop of Software Engineering with Michael Bolin
OpenAI Codex lead explains the agent loop, sandboxing, repo design, and how software engineering changes when agents generate most of the code.
-
현대 LLM의 어텐션 변형 시각 가이드
A Visual Guide to Attention Variants in Modern LLMs
From MHA and GQA to MLA, sparse attention, and hybrid architectures
-
AGI를 향한 진전 측정: 인지 프레임워크
Measuring Progress Towards AGI: A Cognitive Framework
We’re introducing a framework to measure progress toward AGI, and launching a Kaggle hackathon to build the relevant evaluations.
-
ImportAI 449: LLM이 다른 LLM을 학습시킴; 72B 분산 학습 실행; 컴퓨터 비전은 생성 텍스트보다 더 어렵다
ImportAI 449: LLMs training other LLMs; 72B distributed training run; computer vision is harder than generative text
Will AI cause a political interregnum