WTF is Artificial Intelligence Really? | Yann LeCun x Nikhil Kamath | People by WTF Ep #4

Nikhil Kamath
01:35:57 Report Issue
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Chapters & Sections (61)

0:31 Early Life and Career Influences in Science chapter 3
0:31 Origins of Artificial Intelligence and Career Path
2:59 The Intersection of AI and Human Consequences
4:30 The Role of Collaboration in Scientific Progress
7:44 Human Intelligence and Problem Solving Limitations chapter 3
7:44 Human Limitations and Problem-Solving Capacity
9:21 Importance of Critical Thinking and Education
10:51 Origins and Definition of Artificial Intelligence
12:59 Defining Intelligence and AI Problem-Solving Approaches chapter 2
12:59 Defining Intelligence and Problem-Solving Approaches
14:51 Early AI Development and Branching Theories
17:31 Emergence of Classical Computer Science and AI chapter 3
17:31 Heuristics in Classical Computer Science and AI
19:18 Approaches to Artificial Intelligence Development
21:08 Early Image Recognition and Neural Networks
24:59 Early History of Artificial Neural Networks chapter 2
24:59 Early AI Development and Neural Network Evolution
27:23 Supervised Learning and its Limitations
29:28 Overview of Artificial Intelligence Subfields chapter 2
29:28 Overview of Artificial Intelligence Subfields
32:12 Types of Machine Learning Techniques Explained
34:44 Self-Supervised Learning for Image Recovery chapter 3
34:44 Self-Supervised Learning for Image Recovery
36:33 Neural Networks and Self-Supervised Learning
38:06 Building a Simple Neural Network for Image Recognition
39:39 Neural Network Activation and Backpropagation chapter 2
39:39 Neural Network Activation and Backpropagation
41:55 Convolutional Neural Networks and Image Recognition
44:36 Convolutional Neural Networks for Natural Data chapter 2
44:36 Convolutional Neural Networks for Natural Data
47:48 Neural Network Components and Equivariance
50:11 History and Basics of Language Models chapter 2
50:11 Origins of Language Model Theory
52:13 Limitations of N-Gram Language Models
54:43 Predictive Modeling of Language Sequences chapter 2
54:43 Predicting Next Word in Language Models
56:45 Emergent Properties of Large Language Models
59:50 Limitations of Autoregressive Models in Predictions chapter 2
59:50 Limitations of Autoregressive Models in AI
1:01:37 Limitations of Large Language Models Explained
1:04:26 Designing Architectures for Self-Supervised Learning chapter 5
1:04:26 Designing Architectures for Self-Supervised Learning
1:05:58 Limitations of Predicting Pixel Sequences in Video
1:07:18 Human Reasoning and Planning Abilities
1:09:28 Limitations of Current AI Architectures
1:12:10 Predictive Modeling and Long-term Forecasting Limitations
1:13:36 Predictive Capabilities of Artificial Intelligence chapter 2
1:13:36 Predictive Capabilities of Artificial Intelligence
1:15:56 Limitations of Current LLM Architectures and Training
1:19:15 Importance of Local Computing Infrastructure chapter 3
1:19:15 Future of AI Infrastructure in Emerging Markets
1:21:18 Benefits of Advanced Education in Innovation
1:22:42 Building a Business with Narrow Intelligence
1:24:42 Potential Applications of AI in Various Industries chapter 2
1:24:42 Potential Applications of AI in Various Industries
1:26:44 Future of Open-Source Technology Platforms
1:29:13 Human Intelligence in an AI-Driven World chapter 4
1:29:13 Human Intelligence in an AI-Driven World
1:30:44 Impact of Automation on Human Productivity
1:32:03 Defining Artificial Intelligence and Human Intelligence
1:33:43 Importance of Accessible Education and Self-Learning

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