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 23 24 25 26 27 28 29 30 31 32
Introduction
00:00 • 6min
The Journey to a Career in Artificial Intelligence
05:55 • 3min
The Importance of Deep Learning in AI
08:47 • 3min
TinyML: An Introduction to Machine Learning
11:27 • 4min
The Importance of Embodiment in Machine Learning
15:19 • 5min
The Future of AI
20:29 • 3min
The Importance of General Intelligence
23:58 • 3min
The Importance of Large Language Models
26:43 • 3min
The Edge of AI
29:30 • 4min
The Importance of Edge AI
33:38 • 3min
The Spectrum of Self-Driving Cars
37:05 • 2min
The Future of Deep Learning
38:52 • 4min
The Importance of Architectural Innovations in Edge AI
43:21 • 4min
The Future of Machine Learning
47:11 • 3min
How to Architect Models to Work Well With Hardware
50:19 • 3min
The Importance of Understanding the Constraints of Edge AI Systems
53:34 • 4min
How to Train a Model on Streams of Data
58:03 • 2min
The Challenges of Federated Learning in Adji
01:00:16 • 6min
The Limitations of Federated Learning
01:05:53 • 3min
Edge Impulse's Head of Machine Learning
01:08:33 • 4min
How to Quickly Deploy Machine Learning Into Your Embedded Engineering Workflow
01:12:42 • 5min
The Tradeoff Between DSP and Model to Get the Best Possible Output
01:18:11 • 2min
The Future of Engineering for Edge AI
01:20:26 • 5min
Edge AI and the Way That You Do Things
01:25:33 • 4min
The Impact of Big Models on Performance
01:29:23 • 5min
The Importance of Intelligence
01:34:37 • 1min
The Hard Problem of Consciousness
01:35:58 • 5min
The Mechanisms of Consciousness
01:40:49 • 2min
The Hard Problem of Consciousness
01:42:29 • 4min
The Pervasive Self-Awareness of Physically Connected Matter
01:46:32 • 4min
The Fine Line Between Intelligence and Self-Awareness
01:50:37 • 3min
The Collectivization of Intelligence
01:53:43 • 4min