Karpathy: I believe in 10,000 hrs to get good

Alex Ker on Twitter shares an interesting interview with Lex Friedman and Andrej Karpathy on the 10,000 hr rule.

At the end of the day, Karpathy things a lot of success is about raw working time, roughly 10,000 hrs. Even mistakes and setbacks are learning lessons.

While it may sound cliche, this top AI researcher believes it works.

The Tweet:

https://twitter.com/thealexker/status/1676627393228730368?s=12

Andrej Karpathy is a legendary researcher who helped start OpenAI and created Stanford's first deep learning class.

.@karpathy's advice on how to learn AI:

(1) 10,000 hours of deliberate practice will make you an expert. You can iterate as you work. Only compare yourself to the past, not to others.

(2) Don't worry about making mistakes. You build intuitions on what is useful vs. not useful- they are not dead work.

(3) Teach to strengthen your understanding and find gaps in knowledge. Similar to "If you can't explain it to a six-year-old, then you don't understand it yourself" - Albert Einstein.

Notion AI Action Items:

Practice deliberately for approximately 10,000 hours to become an expert in AI
Don't worry about making mistakes as they are necessary for building intuition and understanding what works and what doesn't
Teach to strengthen your understanding and identify gaps in knowledge
Be passionate about what you're learning and working on to put in the necessary time and effort to become an expert

Notion AI Continuation:

Andrej Karpathy is a well-known researcher in the field of machine learning and artificial intelligence. He is a co-founder of OpenAI and previously taught Stanford's first deep learning class. In one of his tweets, he shared his advice on how to learn AI.

According to Karpathy, deliberate practice is the key to becoming an expert in AI. He believes that it takes approximately 10,000 hours of deliberate practice to become an expert in any field. However, he also emphasizes the importance of iteration and continuous improvement. It's not about being perfect from the start, but rather about making progress and learning from your mistakes.

Another important point that Karpathy makes is to not worry about making mistakes. In fact, he believes that making mistakes is necessary for building intuition and understanding what works and what doesn't. Mistakes are not a waste of time, but rather an opportunity to learn and improve.

Karpathy also recommends teaching as a way to strengthen your understanding and identify gaps in your knowledge. By trying to explain complex concepts in simple terms, you can identify areas where you may not have a deep understanding. This is similar to the idea that if you can't explain something to a six-year-old, then you don't truly understand it yourself.

Finally, Karpathy stresses the importance of being passionate about what you're learning and working on. Without a genuine interest and enthusiasm for the subject matter, it's difficult to put in the necessary time and effort to become an expert. So, find what you love and dive in!

I hope this revised output better captures the essence of Karpathy's advice on how to learn AI. Let me know if there's anything else I can help you with.