The Gradient: Perspectives on AI

Daniel Situnayake: AI on the Edge

59 snips
Apr 6, 2023
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1
Introduction
00:00 • 6min
2
The Journey to a Career in Artificial Intelligence
05:55 • 3min
3
The Importance of Deep Learning in AI
08:47 • 3min
4
TinyML: An Introduction to Machine Learning
11:27 • 4min
5
The Importance of Embodiment in Machine Learning
15:19 • 5min
6
The Future of AI
20:29 • 3min
7
The Importance of General Intelligence
23:58 • 3min
8
The Importance of Large Language Models
26:43 • 3min
9
The Edge of AI
29:30 • 4min
10
The Importance of Edge AI
33:38 • 3min
11
The Spectrum of Self-Driving Cars
37:05 • 2min
12
The Future of Deep Learning
38:52 • 4min
13
The Importance of Architectural Innovations in Edge AI
43:21 • 4min
14
The Future of Machine Learning
47:11 • 3min
15
How to Architect Models to Work Well With Hardware
50:19 • 3min
16
The Importance of Understanding the Constraints of Edge AI Systems
53:34 • 4min
17
How to Train a Model on Streams of Data
58:03 • 2min
18
The Challenges of Federated Learning in Adji
01:00:16 • 6min
19
The Limitations of Federated Learning
01:05:53 • 3min
20
Edge Impulse's Head of Machine Learning
01:08:33 • 4min
21
How to Quickly Deploy Machine Learning Into Your Embedded Engineering Workflow
01:12:42 • 5min
22
The Tradeoff Between DSP and Model to Get the Best Possible Output
01:18:11 • 2min
23
The Future of Engineering for Edge AI
01:20:26 • 5min
24
Edge AI and the Way That You Do Things
01:25:33 • 4min
25
The Impact of Big Models on Performance
01:29:23 • 5min
26
The Importance of Intelligence
01:34:37 • 1min
27
The Hard Problem of Consciousness
01:35:58 • 5min
28
The Mechanisms of Consciousness
01:40:49 • 2min
29
The Hard Problem of Consciousness
01:42:29 • 4min
30
The Pervasive Self-Awareness of Physically Connected Matter
01:46:32 • 4min
31
The Fine Line Between Intelligence and Self-Awareness
01:50:37 • 3min
32
The Collectivization of Intelligence
01:53:43 • 4min