{"schema_version":"onlylabs.public_signal.v1","title":"Together AI Writing: AI for Systems: Using LLMs to Optimize Database Query Execution","description":"Together AI writing signal with public source context, captured evidence pages, related signals, and category-scoped analysis context.","url":"https://onlylabs.fyi/signals/d6c64804-a123-4648-9c83-c4ac8352d5a9","json_url":"https://onlylabs.fyi/signals/d6c64804-a123-4648-9c83-c4ac8352d5a9/signal.json","generated_at":"2026-06-07T21:14:51.217996+00:00","org":{"slug":"together-ai","name":"Together AI","category":"neocloud","category_label":"Neocloud","dossier_url":"https://onlylabs.fyi/labs/together-ai","dossier_json_url":"https://onlylabs.fyi/labs/together-ai/dossier.json"},"related_urls":{"signal":"https://onlylabs.fyi/signals/d6c64804-a123-4648-9c83-c4ac8352d5a9","signal_json":"https://onlylabs.fyi/signals/d6c64804-a123-4648-9c83-c4ac8352d5a9/signal.json","source":"https://www.together.ai/blog/using-llms-to-optimize-database-query-execution","lab_dossier":"https://onlylabs.fyi/labs/together-ai","lab_dossier_json":"https://onlylabs.fyi/labs/together-ai/dossier.json","analysis":"https://onlylabs.fyi/analysis/together-ai","analysis_json":"https://onlylabs.fyi/analysis/together-ai/analysis.json","analysis_evidence_json":"https://onlylabs.fyi/analysis/together-ai/evidence.json","category":"https://onlylabs.fyi/neoclouds","category_json":"https://onlylabs.fyi/neoclouds.json","category_feed":"https://onlylabs.fyi/neoclouds/feed.xml","category_signals_json":"https://onlylabs.fyi/signals.json?category=neocloud","topic":"https://onlylabs.fyi/topics/talking","topic_signals_json":"https://onlylabs.fyi/topics/talking/signals.json?category=neocloud","topic_feed":"https://onlylabs.fyi/topics/talking/feed.xml?category=neocloud","data_business":null},"answer_pack":{"answer":"Together AI published AI for Systems: Using LLMs to Optimize Database Query Execution. 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Links in this article Paper Code Summary We worked in collaboration with Stanford University, the University of Wisconsin–Madison, and Bauplan to test whether LLMs can optimize database query execution plans. The results show that LLM-guided plan rewrites can improve execution performance without modifying the database engine itself. Recent advances in AI have been driven..."},"evidence_pages":[{"url":"https://www.together.ai/blog/using-llms-to-optimize-database-query-execution","final_url":"https://www.together.ai/blog/using-llms-to-optimize-database-query-execution","title":"AI for Systems: Using LLMs to Optimize Database Query Execution","http_status":200,"content_type":"text/html; charset=utf-8","capture_method":"plain","fetched_at":"2026-06-07T21:14:51.217996+00:00","bytes":313524,"raw_path":"912a316a3fad2447515e8337bb11a7b15326f07af08243f79d7cf87f600c64bd.html","content_hash":"011645fa6398a21406c31e440be1b784ecaf8b97b2e1f5d65ec3c139a7d3b4b5","excerpt_chars":1200,"truncated":true,"excerpt":"AI for Systems: Using LLMs to Optimize Database Query Execution ⚡️ FlashAttention-4: up to 1.3× faster than cuDNN on NVIDIA Blackwell → Introducing Together AI's new look → 🔎 ATLAS: runtime-learning accelerators delivering up to 4x faster LLM inference → ⚡ Together GPU Clusters: self-service NVIDIA GPUs, now generally available → 📦 Batch Inference API: Process billions of tokens at 50% lower cost for most models → 🪛 Fine-Tuning Platform Upgrades: Larger Models, Longer Contexts → All blog posts Research Published 4/3/2026 AI for Systems: Using LLMs to Optimize Database Query Execution Authors Mehmet Hamza Erol, Xiangpeng Hao, Federico Bianchi, Ciro Greco, Jacopo Tagliabue, James Zou Table of contents 40+ Models Chosen for Production...40+ Models Chosen for Production...40+ Models Chosen for Production... Links in this article Paper Code Summary We worked in collaboration with Stanford University, the University of Wisconsin–Madison, and Bauplan to test whether LLMs can optimize database query execution plans. The results show that LLM-guided plan rewrites can improve execution performance without modifying the database engine itself. 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