episode stringlengths 45 100 | text stringlengths 1 528 | timestamp_link stringlengths 56 56 |
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Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | compressing that data to act efficiently in that | https://karpathy.ai/lexicap/0011-large.html#00:45:48.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | data you yourself appear very often. | https://karpathy.ai/lexicap/0011-large.html#00:45:54.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | So it's useful to form compressions of yourself | https://karpathy.ai/lexicap/0011-large.html#00:45:57.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | and it's a really beautiful formulation of what | https://karpathy.ai/lexicap/0011-large.html#00:46:00.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | consciousness is a necessary side effect. | https://karpathy.ai/lexicap/0011-large.html#00:46:03.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | It's actually quite compelling to me. | https://karpathy.ai/lexicap/0011-large.html#00:46:05.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | You've described RNNs, developed LSTMs, long | https://karpathy.ai/lexicap/0011-large.html#00:46:11.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | short term memory networks that are a type of | https://karpathy.ai/lexicap/0011-large.html#00:46:16.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | recurrent neural networks that have gotten a lot | https://karpathy.ai/lexicap/0011-large.html#00:46:20.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | of success recently. | https://karpathy.ai/lexicap/0011-large.html#00:46:23.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | So these are networks that model the temporal | https://karpathy.ai/lexicap/0011-large.html#00:46:24.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | aspects in the data, temporal patterns in the | https://karpathy.ai/lexicap/0011-large.html#00:46:27.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | data and you've called them the deepest of the | https://karpathy.ai/lexicap/0011-large.html#00:46:30.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | neural networks. | https://karpathy.ai/lexicap/0011-large.html#00:46:34.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | So what do you think is the value of depth in | https://karpathy.ai/lexicap/0011-large.html#00:46:35.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | the models that we use to learn? | https://karpathy.ai/lexicap/0011-large.html#00:46:38.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | Since you mentioned the long short term memory | https://karpathy.ai/lexicap/0011-large.html#00:46:41.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | and the LSTM I have to mention the names of the | https://karpathy.ai/lexicap/0011-large.html#00:46:46.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | brilliant students who made that possible. | https://karpathy.ai/lexicap/0011-large.html#00:46:50.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | First of all my first student ever Sepp Hochreiter | https://karpathy.ai/lexicap/0011-large.html#00:46:52.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | who had fundamental insights already in his | https://karpathy.ai/lexicap/0011-large.html#00:46:56.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | diploma thesis. | https://karpathy.ai/lexicap/0011-large.html#00:46:58.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | Then Felix Geers who had additional important | https://karpathy.ai/lexicap/0011-large.html#00:46:59.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | contributions. | https://karpathy.ai/lexicap/0011-large.html#00:47:03.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | Alex Gray is a guy from Scotland who is mostly | https://karpathy.ai/lexicap/0011-large.html#00:47:04.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | responsible for this CTC algorithm which is now | https://karpathy.ai/lexicap/0011-large.html#00:47:08.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | often used to train the LSTM to do the speech | https://karpathy.ai/lexicap/0011-large.html#00:47:11.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | recognition on all the Google Android phones and | https://karpathy.ai/lexicap/0011-large.html#00:47:15.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | whatever and Siri and so on. | https://karpathy.ai/lexicap/0011-large.html#00:47:18.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | So these guys without these guys I would be | https://karpathy.ai/lexicap/0011-large.html#00:47:21.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | nothing. | https://karpathy.ai/lexicap/0011-large.html#00:47:26.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | It's a lot of incredible work. | https://karpathy.ai/lexicap/0011-large.html#00:47:27.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | What is now the depth? | https://karpathy.ai/lexicap/0011-large.html#00:47:29.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | What is the importance of depth? | https://karpathy.ai/lexicap/0011-large.html#00:47:30.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | Well most problems in the real world are deep in | https://karpathy.ai/lexicap/0011-large.html#00:47:32.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | the sense that the current input doesn't tell you | https://karpathy.ai/lexicap/0011-large.html#00:47:36.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | all you need to know about the environment. | https://karpathy.ai/lexicap/0011-large.html#00:47:40.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | So instead you have to have a memory of what | https://karpathy.ai/lexicap/0011-large.html#00:47:44.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | happened in the past and often important parts of | https://karpathy.ai/lexicap/0011-large.html#00:47:48.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | that memory are dated. | https://karpathy.ai/lexicap/0011-large.html#00:47:51.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | They are pretty old. | https://karpathy.ai/lexicap/0011-large.html#00:47:54.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | So when you're doing speech recognition for | https://karpathy.ai/lexicap/0011-large.html#00:47:56.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | example and somebody says 11 then that's about | https://karpathy.ai/lexicap/0011-large.html#00:47:59.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | half a second or something like that which means | https://karpathy.ai/lexicap/0011-large.html#00:48:05.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | it's already 50 time steps. | https://karpathy.ai/lexicap/0011-large.html#00:48:09.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | And another guy or the same guy says 7. | https://karpathy.ai/lexicap/0011-large.html#00:48:11.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | So the ending is the same even but now the | https://karpathy.ai/lexicap/0011-large.html#00:48:15.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | system has to see the distinction between 7 and | https://karpathy.ai/lexicap/0011-large.html#00:48:19.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | 11 and the only way it can see the difference is | https://karpathy.ai/lexicap/0011-large.html#00:48:22.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | it has to store that 50 steps ago there was an | https://karpathy.ai/lexicap/0011-large.html#00:48:25.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | S or an L, 11 or 7. | https://karpathy.ai/lexicap/0011-large.html#00:48:30.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | So there you have already a problem of depth 50 | https://karpathy.ai/lexicap/0011-large.html#00:48:34.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | because for each time step you have something | https://karpathy.ai/lexicap/0011-large.html#00:48:37.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | like a virtual layer in the expanded unrolled | https://karpathy.ai/lexicap/0011-large.html#00:48:41.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | version of this recurrent network which is doing | https://karpathy.ai/lexicap/0011-large.html#00:48:44.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | the speech recognition. | https://karpathy.ai/lexicap/0011-large.html#00:48:46.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | So these long time lags they translate into | https://karpathy.ai/lexicap/0011-large.html#00:48:48.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | problem depth. | https://karpathy.ai/lexicap/0011-large.html#00:48:51.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | And most problems in this world are such that | https://karpathy.ai/lexicap/0011-large.html#00:48:53.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | you really have to look far back in time to | https://karpathy.ai/lexicap/0011-large.html#00:48:57.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | understand what is the problem and to solve it. | https://karpathy.ai/lexicap/0011-large.html#00:49:01.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | But just like with LSTMs you don't necessarily | https://karpathy.ai/lexicap/0011-large.html#00:49:05.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | need to when you look back in time remember every | https://karpathy.ai/lexicap/0011-large.html#00:49:08.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | aspect you just need to remember the important | https://karpathy.ai/lexicap/0011-large.html#00:49:11.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | aspects. | https://karpathy.ai/lexicap/0011-large.html#00:49:13.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | That's right. | https://karpathy.ai/lexicap/0011-large.html#00:49:14.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | The network has to learn to put the important | https://karpathy.ai/lexicap/0011-large.html#00:49:15.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | stuff into memory and to ignore the unimportant | https://karpathy.ai/lexicap/0011-large.html#00:49:18.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | noise. | https://karpathy.ai/lexicap/0011-large.html#00:49:22.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | But in that sense deeper and deeper is better | https://karpathy.ai/lexicap/0011-large.html#00:49:23.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | or is there a limitation? | https://karpathy.ai/lexicap/0011-large.html#00:49:28.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | I mean LSTM is one of the great examples of | https://karpathy.ai/lexicap/0011-large.html#00:49:30.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | architectures that do something beyond just | https://karpathy.ai/lexicap/0011-large.html#00:49:34.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | deeper and deeper networks. | https://karpathy.ai/lexicap/0011-large.html#00:49:40.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | There's clever mechanisms for filtering data, | https://karpathy.ai/lexicap/0011-large.html#00:49:42.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | for remembering and forgetting. | https://karpathy.ai/lexicap/0011-large.html#00:49:45.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | So do you think that kind of thinking is | https://karpathy.ai/lexicap/0011-large.html#00:49:47.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | necessary? | https://karpathy.ai/lexicap/0011-large.html#00:49:50.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | If you think about LSTMs as a leap, a big leap | https://karpathy.ai/lexicap/0011-large.html#00:49:51.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | forward over traditional vanilla RNNs, what do | https://karpathy.ai/lexicap/0011-large.html#00:49:54.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | you think is the next leap within this context? | https://karpathy.ai/lexicap/0011-large.html#00:49:57.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | So LSTM is a very clever improvement but LSTM | https://karpathy.ai/lexicap/0011-large.html#00:50:02.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | still don't have the same kind of ability to see | https://karpathy.ai/lexicap/0011-large.html#00:50:06.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | far back in the past as us humans do. | https://karpathy.ai/lexicap/0011-large.html#00:50:10.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | The credit assignment problem across way back | https://karpathy.ai/lexicap/0011-large.html#00:50:14.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | not just 50 time steps or 100 or 1000 but | https://karpathy.ai/lexicap/0011-large.html#00:50:18.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | millions and billions. | https://karpathy.ai/lexicap/0011-large.html#00:50:22.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | It's not clear what are the practical limits of | https://karpathy.ai/lexicap/0011-large.html#00:50:24.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | the LSTM when it comes to looking back. | https://karpathy.ai/lexicap/0011-large.html#00:50:28.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | Already in 2006 I think we had examples where | https://karpathy.ai/lexicap/0011-large.html#00:50:31.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | it not only looked back tens of thousands of | https://karpathy.ai/lexicap/0011-large.html#00:50:35.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | steps but really millions of steps. | https://karpathy.ai/lexicap/0011-large.html#00:50:38.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | And Juan Perez Ortiz in my lab I think was the | https://karpathy.ai/lexicap/0011-large.html#00:50:41.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | first author of a paper where we really, was it | https://karpathy.ai/lexicap/0011-large.html#00:50:45.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | 2006 or something, had examples where it learned | https://karpathy.ai/lexicap/0011-large.html#00:50:49.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | to look back for more than 10 million steps. | https://karpathy.ai/lexicap/0011-large.html#00:50:53.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | So for most problems of speech recognition it's | https://karpathy.ai/lexicap/0011-large.html#00:50:57.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | not necessary to look that far back but there | https://karpathy.ai/lexicap/0011-large.html#00:51:01.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | are examples where it does. | https://karpathy.ai/lexicap/0011-large.html#00:51:05.040 |
Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Lex Fridman Podcast #11 | Now the looking back thing, that's rather easy | https://karpathy.ai/lexicap/0011-large.html#00:51:07.040 |
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