GitHub - tobi/qmd: mini cli search engine for your docs, knowledge bases, meeting notes, whatever. Tracking current sota approaches while being all localYou signed in with another tab or window. Reload to refresh your session. You signed out in another tab or window. Reload to refresh your session. You switched accounts on another tab or window. Reload to refresh your session. Dismiss alert
SAM 3: Segment Anything with Concepts
We present Segment Anything Model (SAM) 3, a unified model that detects, segments, and tracks objects in images and videos based on concept prompts, which we define as either short noun phrases (e.g., "yellow school bus"), image exemplars, or a combination of both. Promptable Concept Segmentation (PCS) takes such prompts and returns segmentation masks and unique identities for all matching object
Google 検索ã«ã‚ˆã‚‹ã‚°ãƒ©ã‚¦ãƒ³ãƒ‡ã‚£ãƒ³ã‚°  | Gemini API  | Google AI for Developers
Google 検索ã«ã‚ˆã‚‹ã‚°ãƒ©ã‚¦ãƒ³ãƒ‡ã‚£ãƒ³ã‚°ã¯ã€Gemini モデルをリアルタイムã®ã‚¦ã‚§ãƒ– コンテンツã«æŽ¥ç¶šã—ã€åˆ©ç”¨å¯èƒ½ãªã™ã¹ã¦ã®è¨€èªžã§å‹•ä½œã—ã¾ã™ã€‚ã“ã‚Œã«ã‚ˆã‚Šã€Gemini ã¯ã‚ˆã‚Šæ£ç¢ºãªå›žç”ã‚’æä¾›ã—ã€çŸ¥è˜ã®ã‚«ãƒƒãƒˆã‚ªãƒ•ã‚’超ãˆã¦æ¤œè¨¼å¯èƒ½ãªæƒ…å ±æºã‚’引用ã§ãã¾ã™ã€‚ グラウンディングã¯ã€æ¬¡ã®ã“ã¨ãŒã§ãるアプリケーションã®æ§‹ç¯‰ã«å½¹ç«‹ã¡ã¾ã™ã€‚ 事実ã®æ£ç¢ºæ€§ã‚’高ã‚ã‚‹: 回ç”を実世界ã®æƒ…å ±ã«åŸºã¥ã„ã¦ç”Ÿæˆã™ã‚‹ã“ã¨ã§ã€ãƒ¢ãƒ‡ãƒ«ã®ãƒãƒ«ã‚·ãƒãƒ¼ã‚·ãƒ§ãƒ³ã‚’減らã—ã¾ã™ã€‚ リアルタイムã®æƒ…å ±ã«ã‚¢ã‚¯ã‚»ã‚¹ã™ã‚‹: 最近ã®å‡ºæ¥äº‹ã‚„トピックã«é–¢ã™ã‚‹è³ªå•ã«ç”ãˆã¾ã™ã€‚ 引用をæä¾›ã™ã‚‹: モデルã®ä¸»å¼µã®å‡ºå…¸ã‚’示ã™ã“ã¨ã§ã€ãƒ¦ãƒ¼ã‚¶ãƒ¼ã®ä¿¡é ¼ã‚’築ãã¾ã™ã€‚ from google import genai from google.genai import types client = genai.Client() grounding_tool = type
Introducing Amazon S3 Vectors: First cloud storage with native vector support at scale (preview) | Amazon Web Services
AWS News Blog Introducing Amazon S3 Vectors: First cloud storage with native vector support at scale (preview) Today, we’re announcing the preview of Amazon S3 Vectors, a purpose-built durable vector storage solution that can reduce the total cost of uploading, storing, and querying vectors by up to 90 percent. Amazon S3 Vectors is the first cloud object store with native support to store large ve
LLM x Slack x Notion ã§è«–文インプットを効率化ã—ã€ç¤¾å†…ナレッジ蓄ç©ã‚‚ã§ãるよã†ã«ã—ãŸè©±
ã¯ã˜ã‚ã« æ ªå¼ä¼šç¤¾ neoAI ã®å¤§å‚洋豊ã§ã™ã€‚æ±äº¬å¤§å¦ã«åœ¨å¦ä¸ã§ã€æ¾å°¾ãƒ»å²©æ¾¤ç ”究室ã«æ‰€å±žã—ã¦ã„ã¾ã™ã€‚AI ソリューション事æ¥éƒ¨ã¨ã—ã¦ã€ãƒ—ãƒã‚¸ã‚§ã‚¯ãƒˆãƒžãƒã‚¸ãƒ¡ãƒ³ãƒˆã‚’è¡Œã„ãªãŒã‚‰ã€ç ”究開発組織 neoAI Research ã¨ã—ã¦å…ˆç«¯æŠ€è¡“ã®å®Ÿè·µã«å–り組んã§ã„ã¾ã™ã€‚ 今回ã¯ã€å¼Šç¤¾ã® Slack 上ã§è«–æ–‡ã®ã‚¤ãƒ³ãƒ—ットを効率化ã™ã‚‹ãŸã‚ã«é–‹ç™ºã—㟠LLM Bot ã«ã¤ã„ã¦ã”紹介ã—ã¾ã™ã€‚開発ã—ãŸã®ã¯2023å¹´ã§ã€å½“時㯠NotebookLM ã®ã‚ˆã†ãªã‚µãƒ¼ãƒ“スãŒã¾ã å˜åœ¨ã—ãªã‹ã£ãŸãŸã‚ã€ç¤¾å†…ã§ã¯è«–æ–‡ã®æ¦‚è¦ã‚’スピーディーã«æŠŠæ¡ã§ãる点ã§é‡å®ã•ã‚Œã¦ã„ã¾ã—ãŸã€‚ã¾ãŸã€ãã®è¦ç´„çµæžœã‚’社内ã®ãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹ã«è“„ç©ã§ãã‚‹ã¨ã„ã†æ©Ÿèƒ½ã‚‚ã‚ã‚‹ãŸã‚ã€å¼Šç¤¾ã®ãƒŠãƒ¬ãƒƒã‚¸åŸºç›¤ã‚’支ãˆã¦ã„ã‚‹å˜åœ¨ã§ã‚‚ã‚ã‚Šã¾ã™ã€‚ AI ソリューション事æ¥éƒ¨ã«ã¤ã„ã¦ã¯ã“ã¡ã‚‰ã‚’å‚ç…§ãã ã•ã„。 背景ã¨èª²é¡Œ 論文をèªã‚€æ–‡åŒ–ã®é‡è¦æ€§ AI ソリューション事æ¥éƒ¨ã§ã¯ã€å¸¸ã«æœ€æ–°ã®
GitHub - dkozlov/awesome-knowledge-distillation: Awesome Knowledge Distillation
Neural Network Ensembles, L.K. Hansen, P. Salamon, 1990 Neural Network Ensembles, Cross Validation, and Active Learning, Andres Krogh, Jesper Vedelsby, 1995 Combining labeled and unlabeled data with co-training, A. Blum, T. Mitchell, 1998 Ensemble Methods in Machine Learning, Thomas G. Dietterich, 2000 Model Compression, Rich Caruana, 2006 Dark knowledge, Geoffrey Hinton, Oriol Vinyals, Jeff Dean,
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Scaling Open-Vocabulary Object Detection
https://dl.acm.org/doi/10.1145/2629489
SAM 3: Segment Anything with Concepts
https://bryon.io/from-facts-to-knowledge-the-layer-cake-of-rdfs-and-owl-e84819d8075d
GitHub - PleasePrompto/notebooklm-skill: Use this skill to enable Claude Code to communicate directly with your Google NotebookLM notebooks. Query your uploaded documents and get source-grounded, citation-backed answers from Gemini. Features browser autom
Gemini API ã® URL コンテã‚スト ツールãŒä¸€èˆ¬å…¬é–‹ã«- Google Developers Blog
AI Alliance Joined by Senzing
Obsidianã‚’LLM時代ã®ãƒŠãƒ¬ãƒƒã‚¸ãƒ™ãƒ¼ã‚¹ã«ï¼ クリッピング→Markdown→CLI連æºã®å®Ÿè·µ
Entity Linking with Wikipedia and Wikidata on spaCy v3.7 · explosion/spaCy · Discussion #13049
https://dl.acm.org/doi/abs/10.1145/3543873.3587585
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Downloads/yago 4 5 | Yago Project
AIP Now
GitHub - HKUST-KnowComp/FolkScope: Codes and Datasets for the ACL2023 Findings Paper: FolkScope: Intention Knowledge Graph Construction for Discovering E-commerce Commonsense
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