Chapters
Transcript
Episode notes
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22
Introduction
00:00 • 3min
The Convergence of Stars Aligning
03:04 • 4min
Cerebras GPT Family of Large Language Models
07:26 • 2min
The Evolution of Deep Learning in AI
09:41 • 4min
The Importance of Empirical Laws in AI
13:46 • 5min
The Transferability of Scaling Laws to Task Level Tasks
19:04 • 2min
Scaling Laws for AI Development
21:10 • 2min
The Importance of Scaling Models
22:56 • 2min
The Importance of Diffusion in AI
25:25 • 2min
Cerebral's Role in Inference
27:29 • 4min
The Importance of Graceful Scaling
31:43 • 3min
The Advantages of Disaggregated Memory for Language Modeling
34:44 • 2min
NVIDIA's Approach to GPU Training Is Similar to the GDC Presentation
36:35 • 2min
The Pros and Cons of Dojo's Approach to Training Tiles
38:40 • 4min
Ceripras AI Model Studio: A Platform Offering
42:42 • 5min
The Cost of Platform as a Service
47:16 • 2min
The Future of AI
49:15 • 4min
The Differences Between GPT and Existing Software
53:05 • 2min
The Importance of Generalization in Language Models
54:47 • 5min
The Future of AI
59:26 • 3min
The Future of AI
01:02:33 • 4min
The Future of Chat GPT
01:06:52 • 2min