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Co-Scientist: 연구 가속화를 위한 멀티 에이전트 AI 파트너 – Google DeepMind
Co-Scientist: A multi-agent AI partner to accelerate research â Google DeepMind
Introducing Co-Scientist, a collaborative AI partner built with Gemini to help researchers accelerate scientific breakthroughs.
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FOD#152: AI Agent Skills: Why Skill Curation Is the Next Bottleneck
This Week in Turing Post:
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AWS에서 기초 모델 학습 및 추론을 위한 구성 요소
Building Blocks for Foundation Model Training and Inference on AWS
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You Should Install Hermes Agent This Weekend
Cheap 1M-context models changed the model layer. Claude Code and Codex changed the coding layer. Hermes is starting to look like the runtime layer.
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Import AI 456: RSI와 경제성장; AI 규제에 대한 급진적 선택지; 신경 컴퓨터
Import AI 456: RSI and economic growth; radical optionality for AI regulation; and a neural computer
What laws does superintelligence demand?
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새로운 AI 기반의 Google Finance가 유럽으로 확대되고 있습니다
The new AI-powered Google Finance is expanding to Europe.
A screenshot of the AI-powered experience on Google Finance.
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딥 에이전트, LangSmith, 병렬 처리를 사용한 회사 실사 에이전트 구축
https://www.langchain.com/blog/building-a-company-due-diligence-agent-with-deep-agents-langsmith-and-parallel
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AI 101: What’s So Magical About Embeddings? - by Ksenia Se
How tokens become learnable coordinates, and geometry shapes how context connects and meaning comes to life
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창의적인 거장들이 AI로 중소기업 광고를 만들 때 나타나는 결과 보기
See what happens when creative legends use AI to make ads for small businesses.
black and white card with headshots of susan credle, jayonta jenkins and tiffany rolfe
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vLLM V0에서 V1로: 강화학습에서 수정보다 정확성을 먼저
vLLM V0 to V1: Correctness Before Corrections in RL
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검색에서 바로 해볼 수 있는 5가지 가드닝 팁
5 gardening tips you can try right in Search
An abstract background featuring soft, stippled illustrations of flowers and a butterfly in a bright palette of blue, green, and red. In the center of the image is a white circle c…
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AlphaEvolve: Gemini 기반 코딩 에이전트로 다양한 분야의 영향력 확장 – Google DeepMind
AlphaEvolve: Gemini-powered coding agent scaling impact across fields â Google DeepMind
Explore how AlphaEvolve's Gemini-powered algorithms are driving impact across business, infrastructure, and science.
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에이전트 관찰성: 학습을 강화하기 위한 피드백의 필요성
https://www.langchain.com/blog/agent-observability-needs-feedback-to-power-learning
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오픈 ASR 리더보드에 벤치마킹 조작 방지 기능 추가
Adding Benchmaxxer Repellant to the Open ASR Leaderboard
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구글이 XPRIZE, Range Media Partners와 함께 350만 달러 규모의 'Future Vision' 영화 경진대회 개최
Google is partnering with XPRIZE and Range Media Partners on the $3.5 million Future Vision film competition.
<img src="https://storage.googleapis.com/gweb-uniblog-publish-prod/images/futurevisionxprize_social.max-600x600.format-webp.webp" />Google is partnering with XPRIZE and Range Media…
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FOD#151: Recursive Self-Learning: Why It Matters Now
From Turing's "child machine" to Jack Clark's 2028 forecast – what changes when the system starts working on the system that builds it
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Open SWE: 내부 코딩 에이전트를 위한 오픈소스 프레임워크
Open SWE: An Open-Source Framework for Internal Coding Agents
Built on Deep Agents and LangGraph, Open SWE provides the core architectural components for internal coding agents.
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오픈 모델이 임계점을 돌파했다
Open Models have crossed a threshold
Open models like GLM-5 and MiniMax M2.7 now match closed frontier models on core agent tasks — file operations, tool use, and instruction following — at a fraction of the cost and …
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Import AI 455: AI 시스템들이 자신들을 스스로 구축하기 시작할 것이다
Import AI 455: AI systems are about to start building themselves.
The first step towards recursive self improvement
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AI와 함께 일하고 성과를 복합하는 방법
How to Work and Compound with AI
Context as infra, taste as config, verification for autonomy, scale via delegation, closing the loop.
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Interrupt 2026: 엔터프라이즈 규모의 에이전트
Previewing Interrupt 2026: Agents at Enterprise Scale
This year, we're doing it again. Interrupt 2026 is May 13–14 at The Midway in San Francisco, and the lineup, the format, and the scale have all leveled up.
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메모리 검색 개선: New Computer가 LangSmith로 50% 높은 회상률을 달성한 방법
Improving Memory Retrieval: How New Computer achieved 50% higher recall with LangSmith
New Computer used LangSmith to improve their memory retrieval system, achieving 50% higher recall by tracking regressions in comparison view and adjusting conversation prompts acco…
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AI 에이전트란 무엇인가?
What is an AI agent?
Introducing a new series of musings on AI agents, called "In the Loop".
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LLM 판사를 인간 선호도에 정렬하기
Aligning LLM-as-a-Judge with Human Preferences
Deep dive into self-improving evaluators in LangSmith, motivated by the rise of LLM-as-a-Judge evaluators plus research on few-shot learning and aligning human preferences.
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LangSmith를 이용한 회귀 테스트
Regression Testing with LangSmith
Evaluate and iterate on LLM applications with confidence using LangSmith's regression testing. Compare experiments, track performance, and identify changes.
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Azure 마켓플레이스에서 LangSmith이 거래 가능한 상품으로 출시 발표
Announcing LangSmith is now a transactable offering in the Azure Marketplace
LangSmith is now available in Azure Marketplace. Deploy the DevOps platform for LLM apps in your Azure VPC with full data control and MACC credit support.
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평가 주도 개발을 통한 LLM 신뢰성의 반복적 향상
Iterating Towards LLM Reliability with Evaluation Driven Development
Dosu uses evaluation driven development and LangSmith to build reliable LLM products at scale, monitor production performance, and iterate with confidence.
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테스트 실행 비교
Test Run Comparisons
Compare LLM test runs side-by-side with LangSmith's Test Run Comparisons. Manually inspect data, filter results, and gain insights faster.
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에이전틱 엔지니어링: AI 에이전트 스웜이 소프트웨어 엔지니어링을 재정의하는 방법
Agentic Engineering: How Swarms of AI Agents Are Redefining Software Engineering
Multi-agent systems that mirror real engineering teams — not just code faster — can cut debug time by 93% and compress cross-team delivery. Here's the architecture built on LangGra…
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에이전트 관찰성: 프로덕션 LLM 에이전트 모니터링 및 평가 방법
Agent Observability: How to Monitor and Evaluate LLM Agents in Production
Production monitoring for LLM agents requires new observability tools. Learn how to trace, evaluate, and improve AI agents at scale.
