Advice for Beginners: Don’t Focus on What You Do, But How Much You Do

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The key advice for beginners in machine learning is not to focus on what to do, but instead focus on how much time to invest. The concept of the '10,000 hours' rule emphasizes the importance of spending a significant amount of time on the subject. Deliberate effort and forming a daily habit are necessary to maximize the likelihood of reaching 10,000 hours. Rather than comparing oneself to others, it is more beneficial to compare personal progress over time. Beginners may get paralyzed by the choices and worry about making the wrong decisions, but making mistakes and accumulating experience is part of the learning process. It is essential to focus on consistent and continuous work.

Andrej Karpathy is a legendary AI researcher, engineer, and educator. He’s the former director of AI at Tesla, a founding member of OpenAI, and an educator at Stanford. Please support this podcast by checking out our sponsors:
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OUTLINE:
Here’s the timestamps for the episode. On some podcast players you should be able to click the timestamp to jump to that time.
(00:00) – Introduction
(05:41) – Neural networks
(10:45) – Biology
(16:15) – Aliens
(26:27) – Universe
(38:18) – Transformers
(46:34) – Language models
(56:45) – Bots
(1:03:05) – Google’s LaMDA
(1:10:28) – Software 2.0
(1:21:28) – Human annotation
(1:23:25) – Camera vision
(1:28:30) – Tesla’s Data Engine
(1:32:39) – Tesla Vision
(1:39:09) – Elon Musk
(1:44:17) – Autonomous driving
(1:49:11) – Leaving Tesla
(1:54:39) – Tesla’s Optimus
(2:03:45) – ImageNet
(2:06:23) – Data
(2:16:15) – Day in the life
(2:29:31) – Best IDE
(2:36:37) – arXiv
(2:41:06) – Advice for beginners
(2:50:24) – Artificial general intelligence
(3:03:44) – Movies
(3:09:37) – Future of human civilization
(3:13:56) – Book recommendations
(3:20:05) – Advice for young people
(3:21:56) – Future of machine learning
(3:28:44) – Meaning of life