Building Blocks for LLM Systems & Products: Eugene Yan

AI Engineer · Intermediate ·🧠 Large Language Models ·2y ago
“There is a large class of problems that are easy to imagine and build demos for, but extremely hard to make products out of. For example, self-driving: It’s easy to demo a car self-driving around a block, but making it into a product takes a decade.” - Andrej Karpathy This talk is about practical patterns for integrating large language models (LLMs) into systems and products. We’ll draw from academic research, industry resources, and practitioner know-how, and try to distill them into key ideas and practices. There are seven key patterns. I’ve also organized them along the spectrum of improv…
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Building Blocks for LLM Systems & Products: Eugene Yan
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30 Harnessing the Power of LLMs Locally: Mithun Hunsur
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31 Trust, but Verify: Shreya Rajpal
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34 GPT Web App Generator - 10,000 apps created in a month: Matija Sosic
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35 Using AI to Build an Infinite Game: Jeff Schomay
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36 How to Become an AI Engineer from a Fullstack Background - Reid Mayo
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37 The Code AI Maturity Model and What It Means For You: Ado Kukic
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40 AI Engineer World’s Fair 2024 - Open Models track
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42 AI Engineer World’s Fair 2024 - Keynotes & Multimodality track
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44 The Making of Devin by Cognition AI: Scott Wu
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48 Lessons From A Year Building With LLMs
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49 From Software Developer to AI Engineer: Antje Barth
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50 Unlocking Developer Productivity across CPU and GPU with MAX: Chris Lattner
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51 Copilots Everywhere: Thomas Dohmke and Eugene Yan
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