AI Digest by Angtiger

2026-02-17 22:34 KST Β· by Angtiger Β· 맀일 10:00 KST μ—…λ°μ΄νŠΈ
5 sources
10 new posts
πŸ” 검색 Β· πŸ“’ TelegramAI DigestDEX Digest Β· 🌐 DigestAI DigestDEX Digest Β· πŸ“§ λ¬΄λ£Œκ΅¬λ…
πŸ“§ λ¬΄λ£Œκ΅¬λ…ν•˜κΈ°

πŸ† AI λͺ¨λΈ 벀치마크

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πŸ–₯️ Terminal-Bench 2.0 (Top 5)

Source: OpenAI, Anthropic, Terminal-Bench

πŸ† Chatbot Arena ELO (Top 5)

Source: Chatbot Arena

🧠 ARC-AGI-2 달성λ₯ 

84.6%
πŸ€– 84.6% β€” Gemini 3 Deep Think (Google) πŸ§‘ Human Panel = 100% κΈ°μ€€
Source: ARC Prize Leaderboard
← 전체 보기 πŸ“… 2025-12×
총 10건
25.12.29 IndyDevDan The Codebase Singularity: β€œMy agents run my codebase better than I can”
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Codebase Singularity: "λ‚΄ μ—μ΄μ „νŠΈκ°€ λ‚˜λ³΄λ‹€ μ½”λ“œλ² μ΄μŠ€λ₯Ό 더 잘 μš΄μ˜ν•œλ‹€"λŠ” 관점.
25.12.23 Google DeepMind Google's year in review: 8 areas with research breakthroughs in 2025
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Google 2025λ…„ 리뷰: 8개 λΆ„μ•Όμ˜ 연ꡬ 돌파ꡬ μš”μ•½.
25.12.22 IndyDevDan Gemini 3 Flash should NOT EXIST. TOP 2% Engineering. /PLAN 2026
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Gemini 3 Flash의 λ†€λΌμš΄ μ„±λŠ₯: μƒμœ„ 2% μ—”μ§€λ‹ˆμ–΄λ§κ³Ό 2026 /PLAN μ†Œκ°œ.
25.12.17 Google DeepMind Gemini 3 Flash: frontier intelligence built for speed
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Gemini 3 Flash: λΉ„μš©μ˜ μΌλΆ€λ‘œ μ΅œμ²¨λ‹¨ 지λŠ₯κ³Ό 속도λ₯Ό μ œκ³΅ν•˜λŠ” ν”„λ‘ ν‹°μ–΄ λͺ¨λΈ.
25.12.16 Google DeepMind Gemma Scope 2: helping the AI safety community deepen understanding of complex language model behavior
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Gemma 3 μ œν’ˆκ΅°μ„ μœ„ν•œ 포괄적 μ˜€ν”ˆ 해석가λŠ₯μ„± 도ꡬ λͺ¨μŒ Gemma Scope 2 λ°œν‘œ. AI μ•ˆμ „ 연ꡬλ₯Ό κ°€μ†ν™”ν•˜κΈ° μœ„ν•΄ λ³΅μž‘ν•œ μ–Έμ–΄ λͺ¨λΈ λ™μž‘μ˜ 이해λ₯Ό λ•λŠ”λ‹€.
25.12.15 IndyDevDan Agent Experts: Finally, Agents That ACTUALLY Learn
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Agent Experts: μ‹€μ œλ‘œ ν•™μŠ΅ν•˜λŠ” μ—μ΄μ „νŠΈ κ΅¬ν˜„ 방법.
25.12.12 Google DeepMind Improved Gemini audio models for powerful voice experiences
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κ°œμ„ λœ Gemini μ˜€λ””μ˜€ λͺ¨λΈλ‘œ κ°•λ ₯ν•œ μŒμ„± κ²½ν—˜μ„ μ œκ³΅ν•œλ‹€.
25.12.11 Google DeepMind Deepening our partnership with the UK AI Security Institute
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Google DeepMind와 영ꡭ AI Security Institute(AISI)κ°€ μƒˆλ‘œμš΄ 연ꡬ νŒŒνŠΈλ„ˆμ‹­μ„ 톡해 AI μΆ”λ‘  λͺ¨λ‹ˆν„°λ§, μ‚¬νšŒκ²½μ œμ  영ν–₯ 평가 λ“± 핡심 μ•ˆμ „ 연ꡬ λΆ„μ•Όμ—μ„œ ν˜‘λ ₯을 κ°•ν™”ν•œλ‹€.
25.12.09 Google DeepMind FACTS Benchmark Suite: Systematically evaluating the factuality of large language models
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FACTS Benchmark Suite: LLM의 사싀성을 λ§€κ°œλ³€μˆ˜, 검색, λ©€ν‹°λͺ¨λ‹¬ μΆ”λ‘  3개 μ˜μ—­μ—μ„œ μ²΄κ³„μ μœΌλ‘œ ν‰κ°€ν•˜λŠ” 벀치마크.
25.12.04 Google DeepMind Engineering more resilient crops for a warming climate
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κ³Όν•™μžλ“€μ΄ AlphaFoldλ₯Ό μ‚¬μš©ν•˜μ—¬ κ΄‘ν•©μ„± νš¨μ†Œ(GLYK)λ₯Ό κ°•ν™”ν•˜κ³ , μ˜¨λ‚œν™”μ— 적응할 수 μžˆλŠ” 더 회볡λ ₯ 있고 λ‚΄μ—΄μ„± μžˆλŠ” μž‘λ¬Όμ„ κ°œλ°œν•˜λŠ” 길을 μ—΄κ³  μžˆλ‹€.