Dive into the fascinating history of AI hardware from the early days of computing to the rise of GPUs and TPUs. Discover how advancements have catalyzed the evolution of deep learning models. Explore the critical challenges faced, including the memory wall and the dynamics of chip fabrication. Learn about recent restrictions on AI chip exports, which could reshape the tech landscape. Delve into the synergy between hardware and AI applications, revealing how modern technology continues to push boundaries.
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Early AI Programs
Early AI programs, like a checkers-playing program in 1951, showcased the potential of AI.
Marvin Minsky's SNARC, a neural net built with vacuum tubes, simulated rat learning.
insights INSIGHT
Custom-Built Hardware
Early computing hardware was largely custom-built for specific AI applications.
This bespoke approach limited scalability compared to later general-purpose hardware.
question_answer ANECDOTE
Early Machine Learning and Neural Nets
Arthur Samuel's checkers program on the IBM 701 demonstrated early machine learning.
The perceptron in 1958, a custom-built machine, showcased the first real neural net.
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The Generator - An interdisciplinary AI lab empowering innovators from all fields to bring visionary ideas to life by harnessing the capabilities of artificial intelligence.
In this episode:
- Google and Mistral sign deals with AP and AFP, respectively, to deliver up-to-date news through their AI platforms.
- ChatGPT introduces a tasks feature for reminders and to-dos, positioning itself more as a personal assistant.
- Synthesia raises $180 million to enhance its AI video platform for generating videos of human avatars.
- New U.S. guidelines restrict exporting AI chips to various countries, impacting Nvidia and other tech firms.
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Timestamps:
00:00:00 Introduction
00:03:08 Historical Recap: Early AI and Hardware
00:11:51 The Rise of GPUs and Deep Learning
00:15:39 Scaling Laws and the Evolution of AI Models
00:24:05 The Bitter Lesson and the Future of AI Compute
00:25:58 Moore's Law and Huang's Law
00:30:12 Memory and Logic in AI Hardware
00:34:53 Challenges in AI Hardware: The Memory Wall
00:37:08 The Role of GPUs in Modern AI
00:42:27 Fitting Neural Nets in GPUs
00:48:04 Batch Sizes and GPU Utilization
00:52:47 Parallelism in AI Models
00:55:53 Matrix Multiplications and GPUs
00:59:57 Understanding B200 and GB200
01:05:41 Data Center Hierarchy
01:13:42 High Bandwidth Memory (HBM)
01:16:45 Fabrication and Packaging
01:20:17 The Complexity of Semiconductor Fabrication