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Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | So, machine capable to pick up one function from the admissible set of function. | https://karpathy.ai/lexicap/0005-large.html#00:18:54.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | But set of admissible function can be big. | https://karpathy.ai/lexicap/0005-large.html#00:19:02.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | So, it contain all continuous functions and it's useless. | https://karpathy.ai/lexicap/0005-large.html#00:19:07.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | You don't have so many examples to pick up function. | https://karpathy.ai/lexicap/0005-large.html#00:19:11.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | But it can be small. | https://karpathy.ai/lexicap/0005-large.html#00:19:15.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | Small, we call it capacity but maybe better called diversity. | https://karpathy.ai/lexicap/0005-large.html#00:19:17.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | So, not very different function in the set. | https://karpathy.ai/lexicap/0005-large.html#00:19:24.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | It's infinite set of function but not very diverse. | https://karpathy.ai/lexicap/0005-large.html#00:19:27.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | So, it is small VC dimension. | https://karpathy.ai/lexicap/0005-large.html#00:19:31.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | When VC dimension is small, you need small amount of training data. | https://karpathy.ai/lexicap/0005-large.html#00:19:34.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | So, the goal is to create admissible set of functions which is have small VC dimension and contain good function. | https://karpathy.ai/lexicap/0005-large.html#00:19:41.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | Then you will be able to pick up the function using small amount of observations. | https://karpathy.ai/lexicap/0005-large.html#00:19:53.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | So, that is the task of learning? | https://karpathy.ai/lexicap/0005-large.html#00:20:02.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | Yeah. | https://karpathy.ai/lexicap/0005-large.html#00:20:06.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | Is creating a set of admissible functions that has a small VC dimension and then you've figure out a clever way of picking up? | https://karpathy.ai/lexicap/0005-large.html#00:20:07.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | No, that is goal of learning which I formulated yesterday. | https://karpathy.ai/lexicap/0005-large.html#00:20:17.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | Statistical learning theory does not involve in creating admissible set of function. | https://karpathy.ai/lexicap/0005-large.html#00:20:22.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | In classical learning theory, everywhere, 100% in textbook, the set of function, admissible set of function is given. | https://karpathy.ai/lexicap/0005-large.html#00:20:30.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | But this is science about nothing because the most difficult problem to create admissible set of functions | https://karpathy.ai/lexicap/0005-large.html#00:20:39.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | given, say, a lot of functions, continuum set of function, create admissible set of functions. | https://karpathy.ai/lexicap/0005-large.html#00:20:47.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | That means that it has finite VC dimension, small VC dimension and contain good function. | https://karpathy.ai/lexicap/0005-large.html#00:20:55.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | So, this was out of consideration. | https://karpathy.ai/lexicap/0005-large.html#00:21:02.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | So, what's the process of doing that? | https://karpathy.ai/lexicap/0005-large.html#00:21:05.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | I mean, it's fascinating. | https://karpathy.ai/lexicap/0005-large.html#00:21:07.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | What is the process of creating this admissible set of functions? | https://karpathy.ai/lexicap/0005-large.html#00:21:08.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | That is invariant. | https://karpathy.ai/lexicap/0005-large.html#00:21:13.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | That's invariant. | https://karpathy.ai/lexicap/0005-large.html#00:21:15.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | Yeah, you're looking of properties of training data and properties means that you have some function | https://karpathy.ai/lexicap/0005-large.html#00:21:16.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | and you just count what is value, average value of function on training data. | https://karpathy.ai/lexicap/0005-large.html#00:21:30.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | You have model and what is expectation of this function on the model and they should coincide. | https://karpathy.ai/lexicap/0005-large.html#00:21:39.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | So, the problem is about how to pick up functions. | https://karpathy.ai/lexicap/0005-large.html#00:21:46.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | It can be any function. | https://karpathy.ai/lexicap/0005-large.html#00:21:51.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | In fact, it is true for all functions. | https://karpathy.ai/lexicap/0005-large.html#00:21:54.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | But because when we're talking, say, duck does not jumping, so you don't ask question jump like a duck | https://karpathy.ai/lexicap/0005-large.html#00:22:00.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | because it is trivial. | https://karpathy.ai/lexicap/0005-large.html#00:22:11.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | It does not jumping and doesn't help you to recognize jump. | https://karpathy.ai/lexicap/0005-large.html#00:22:13.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | But you know something, which question to ask and you're asking it seems like a duck, | https://karpathy.ai/lexicap/0005-large.html#00:22:16.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | but looks like a duck at this general situation. | https://karpathy.ai/lexicap/0005-large.html#00:22:24.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | Looks like, say, guy who have this illness, this disease. | https://karpathy.ai/lexicap/0005-large.html#00:22:28.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | It is legal. | https://karpathy.ai/lexicap/0005-large.html#00:22:36.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | So, there is a general type of predicate looks like and special type of predicate, | https://karpathy.ai/lexicap/0005-large.html#00:22:39.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | which related to this specific problem. | https://karpathy.ai/lexicap/0005-large.html#00:22:47.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | And that is intelligence part of all this business and that where teacher is involved. | https://karpathy.ai/lexicap/0005-large.html#00:22:51.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | Incorporating the specialized predicates. | https://karpathy.ai/lexicap/0005-large.html#00:22:56.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | What do you think about deep learning as neural networks, these arbitrary architectures | https://karpathy.ai/lexicap/0005-large.html#00:23:01.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | as helping accomplish some of the tasks you're thinking about? | https://karpathy.ai/lexicap/0005-large.html#00:23:08.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | Their effectiveness or lack thereof? | https://karpathy.ai/lexicap/0005-large.html#00:23:13.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | What are the weaknesses and what are the possible strengths? | https://karpathy.ai/lexicap/0005-large.html#00:23:15.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | You know, I think that this is fantasy, everything which like deep learning, like features. | https://karpathy.ai/lexicap/0005-large.html#00:23:20.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | Let me give you this example. | https://karpathy.ai/lexicap/0005-large.html#00:23:29.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | One of the greatest books is Churchill book about history of Second World War. | https://karpathy.ai/lexicap/0005-large.html#00:23:34.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | And he started this book describing that in old time when war is over, so the great kings, | https://karpathy.ai/lexicap/0005-large.html#00:23:39.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | they gathered together, almost all of them were relatives, and they discussed what should | https://karpathy.ai/lexicap/0005-large.html#00:23:53.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | be done, how to create peace. | https://karpathy.ai/lexicap/0005-large.html#00:24:00.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | And they came to agreement. | https://karpathy.ai/lexicap/0005-large.html#00:24:03.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | And when happened First World War, the general public came in power. | https://karpathy.ai/lexicap/0005-large.html#00:24:05.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | And they were so greedy that robbed Germany. | https://karpathy.ai/lexicap/0005-large.html#00:24:13.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | And it was clear for everybody that it is not peace, that peace will last only 20 years | https://karpathy.ai/lexicap/0005-large.html#00:24:18.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | because they were not professionals. | https://karpathy.ai/lexicap/0005-large.html#00:24:24.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | And the same I see in machine learning. | https://karpathy.ai/lexicap/0005-large.html#00:24:28.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | There are mathematicians who are looking for the problem from a very deep point of view, | https://karpathy.ai/lexicap/0005-large.html#00:24:32.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | mathematical point of view. | https://karpathy.ai/lexicap/0005-large.html#00:24:38.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | And there are computer scientists who mostly does not know mathematics. | https://karpathy.ai/lexicap/0005-large.html#00:24:40.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | They just have interpretation of that. | https://karpathy.ai/lexicap/0005-large.html#00:24:46.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | And they invented a lot of blah, blah, blah interpretations like deep learning. | https://karpathy.ai/lexicap/0005-large.html#00:24:49.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | Why you need deep learning? | https://karpathy.ai/lexicap/0005-large.html#00:24:54.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | Mathematic does not know deep learning. | https://karpathy.ai/lexicap/0005-large.html#00:24:55.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | Mathematic does not know neurons. | https://karpathy.ai/lexicap/0005-large.html#00:24:57.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | It is just function. | https://karpathy.ai/lexicap/0005-large.html#00:25:00.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | If you like to say piecewise linear function, say that and do in class of piecewise linear | https://karpathy.ai/lexicap/0005-large.html#00:25:02.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | function. | https://karpathy.ai/lexicap/0005-large.html#00:25:09.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | But they invent something. | https://karpathy.ai/lexicap/0005-large.html#00:25:10.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | And then they try to prove advantage of that through interpretations, which mostly wrong. | https://karpathy.ai/lexicap/0005-large.html#00:25:12.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | And when it's not enough, they appeal to brain, which they know nothing about that. | https://karpathy.ai/lexicap/0005-large.html#00:25:22.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | Nobody knows what's going on in the brain. | https://karpathy.ai/lexicap/0005-large.html#00:25:27.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | So, I think that more reliable work on math. | https://karpathy.ai/lexicap/0005-large.html#00:25:30.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | This is a mathematical problem. | https://karpathy.ai/lexicap/0005-large.html#00:25:34.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | Do your best to solve this problem. | https://karpathy.ai/lexicap/0005-large.html#00:25:36.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | Try to understand that there is not only one way of convergence, which is strong way of | https://karpathy.ai/lexicap/0005-large.html#00:25:39.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | convergence. | https://karpathy.ai/lexicap/0005-large.html#00:25:45.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | There is a weak way of convergence, which requires predicate. | https://karpathy.ai/lexicap/0005-large.html#00:25:46.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | And if you will go through all this stuff, you will see that you don't need deep learning. | https://karpathy.ai/lexicap/0005-large.html#00:25:49.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | Even more, I would say one of the theory, which called represented theory. | https://karpathy.ai/lexicap/0005-large.html#00:25:56.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | It says that optimal solution of mathematical problem, which is described learning is on | https://karpathy.ai/lexicap/0005-large.html#00:26:03.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | shadow network, not on deep learning. | https://karpathy.ai/lexicap/0005-large.html#00:26:16.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | And a shallow network. | https://karpathy.ai/lexicap/0005-large.html#00:26:21.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | Yeah. | https://karpathy.ai/lexicap/0005-large.html#00:26:22.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | The ultimate problem is there. | https://karpathy.ai/lexicap/0005-large.html#00:26:23.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | Absolutely. | https://karpathy.ai/lexicap/0005-large.html#00:26:24.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | In the end, what you're saying is exactly right. | https://karpathy.ai/lexicap/0005-large.html#00:26:25.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | The question is you have no value for throwing something on the table, playing with it, not | https://karpathy.ai/lexicap/0005-large.html#00:26:29.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | math. | https://karpathy.ai/lexicap/0005-large.html#00:26:37.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | It's like a neural network where you said throwing something in the bucket or the biological | https://karpathy.ai/lexicap/0005-large.html#00:26:38.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | example and looking at kings and queens or the cells or the microscope. | https://karpathy.ai/lexicap/0005-large.html#00:26:43.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | You don't see value in imagining the cells or kings and queens and using that as inspiration | https://karpathy.ai/lexicap/0005-large.html#00:26:47.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | and imagination for where the math will eventually lead you. | https://karpathy.ai/lexicap/0005-large.html#00:26:55.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | You think that interpretation basically deceives you in a way that's not productive. | https://karpathy.ai/lexicap/0005-large.html#00:26:59.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | I think that if you're trying to analyze this business of learning and especially discussion | https://karpathy.ai/lexicap/0005-large.html#00:27:06.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | about deep learning, it is discussion about interpretation, not about things, about what | https://karpathy.ai/lexicap/0005-large.html#00:27:17.120 |
Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5 | you can say about things. | https://karpathy.ai/lexicap/0005-large.html#00:27:24.120 |
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