Stanford Webinar - Large Language Models Get the Hype, but Compound Systems Are the Future of AI
For more information about Stanford's Artificial Intelligence programs visit: https://stanford.io/ai
In recent years AI has taken center stage with the rise of Large Language Models (LLMs) that can be used to perform a wide range of tasks, from question answering to coding. There is now a strong focus on large pretrained foundation models as the core of AI application development. But on their own, these models don’t do much besides taking up significant disk space—it’s only when they’re embedded within larger systems that they start to deliver state-of-the-art results.
In this webinar, Prof…
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Chapters (21)
Introduction
0:14
The Present and Future of Compound Systems
0:38
Large Language Models and Industry Trends
0:55
The Impact of GPT-3 on AI
1:07
Google PaLM and Model Announcements
1:41
OpenAI's Transition to Systems Thinking
2:01
Building Effective AI Systems
2:23
Minimal System for Model Interaction
2:56
Importance of Prompting and Sampling Methods
3:22
Various Sampling Techniques
4:04
Chain-of-Thought Reasoning
4:30
Majority Completion Strategies
5:00
Exploring Innovative Sampling Techniques
5:37
Importance of Systems Thinking
5:56
Tool Access and System Design
6:40
Understanding the Evolution of Google Search
6:58
Scaling Systems for AI
7:53
Learning from Past Experiences
8:04
Guardrails and Regulation
9:53
The Future Impact of AI on Society
10:34
Insights for Technical and Busine
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