Ilya Sutskever


Ilya Sutskever: Deep Learning | AI Podcast #94 with Lex Fridman

May 8, 2020

Ilya Sutskever is the co-founder of OpenAI, is one of the most cited computer scientist in history with over 165,000 citations, and to me, is one of the most brilliant and insightful minds ever in the field of deep learning. There are very few people in this world who I would rather talk to and brainstorm with about deep learning, intelligence, and life than Ilya, on and off the mic. This conversation is part of the Artificial Intelligence podcast.

Outline:
0:00 - Introduction
2:23 - AlexNet paper and the ImageNet moment
8:33 - Cost functions
13:39 - Recurrent neural networks
16:19 - Key ideas that led to success of deep learning
19:57 - What's harder to solve: language or vision?
29:35 - We're massively underestimating deep learning
36:04 - Deep double descent
41:20 - Backpropagation
42:42 - Can neural networks be made to reason?
50:35 - Long-term memory
56:37 - Language models
1:00:35 - GPT-2
1:07:14 - Active learning
1:08:52 - Staged release of AI systems
1:13:41 - How to build AGI?
1:25:00 - Question to AGI
1:32:07 - Meaning of life
 

Ilya Sutskever: the Mastermind behind GPT-4 and the future of AI

Mar 15, 2023

In this podcast episode, Ilya Sutskever, the co-founder and chief scientist at OpenAI, discusses his vision for the future of artificial intelligence (AI), including large language models like GPT-4.

Sutskever starts by explaining the importance of AI research and how OpenAI is working to advance the field. He shares his views on the ethical considerations of AI development and the potential impact of AI on society.

The conversation then moves on to large language models and their capabilities. Sutskever talks about the challenges of developing GPT-4 and the limitations of current models. He discusses the potential for large language models to generate a text that is indistinguishable from human writing and how this technology could be used in the future.

Sutskever also shares his views on AI-aided democracy and how AI could help solve global problems such as climate change and poverty. He emphasises the importance of building AI systems that are transparent, ethical, and aligned with human values.

Throughout the conversation, Sutskever provides insights into the current state of AI research, the challenges facing the field, and his vision for the future of AI. This podcast episode is a must-listen for anyone interested in the intersection of AI, language, and society.

Timestamps:

00:04 Introduction of Craig Smith and Ilya Sutskever.
01:00 Sutskever's AI and consciousness interests.
02:30 Sutskever's start in machine learning with Hinton.
03:45 Realization about training large neural networks.
06:33 Convolutional neural network breakthroughs and imagenet.
08:36 Predicting the next thing for unsupervised learning.
10:24 Development of GPT-3 and scaling in deep learning.
11:42 Specific scaling in deep learning and potential discovery.
13:01 Small changes can have big impact.
13:46 Limits of large language models and lack of understanding.
14:32 Difficulty in discussing limits of language models.
15:13 Statistical regularities lead to better understanding of world.
16:33 Limitations of language models and hope for reinforcement learning.
17:52 Teaching neural nets through interaction with humans.
21:44 Multimodal understanding not necessary for language models.
25:28 Autoregressive transformers and high-dimensional distributions.
26:02 Autoregressive transformers work well on images.
27:09 Pixels represented like a string of text.
29:40 Large generative models learn compressed representations of real-world processes.
31:31 Human teachers needed to guide reinforcement learning process.
35:10 Opportunity to teach AI models more skills with less data.
39:57 Desirable to have democratic process for providing information.
41:15 Impossible to understand everything in complicated situations.
 
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