8 ms·

Interview with Yann Lecun on what AI can do

59 points by sconxu 11y ago

misiti3780 11y ago
FYI this was submitted a few days ago and no one seemed to care: https://news.ycombinator.com/item?id=10521398 https://news.ycombinator.com/item?id=10521398
- prawn 11y ago
  Sometimes the front page is too busy or something doesn't take. Don't worry about it - they're just internet points. No point linking to it unless there are comments that might also be interesting to readers of these ones, right?
  - misiti3780 11y ago
    i could careless - i was under the impression HN had URL dup algorithms to make sure you cant double submitted within a few months of the OP
    - adenadel 11y ago
      I think dang said recently it was something like 8 hours. Beyond that you can resubmit. I've had cases where I've submitted something and it just takes me to the thread where someone else posted it and it automatically gives them an upvote from me.
nicklo 11y ago
Yann gave a talk at my university last week. It's really astounding how far deep learning has come from performing classification and regression to now doing things like reasoning and generation. Does anyone else find this wild? These are tasks that historically required a tremendous amount of domain-specific engineering to perform well. And recurrent memory networks just power right on through them. I understand that learned, dense vector representations are powerful blocks to operate on, but hot damn the trend of general systems that require less domain-specific engineering is an exciting one that blows my mind.
- tachyonbeam 11y ago
  I definitely find it wild. Recent developments make me very optimistic that I might see useful domestic robots within my lifetime, maybe even something like Data. It definitely seems way less far-fetched now that we have machine learning techniques for semantic segmentation, object and face recognition, reasoning, voice recognition and synthesis and even translation, extracting useful meaning from text/speech.
hyperion2010 11y ago
You know, I see many different big names in the ML field shooting for a personal 'assistant' or something like that. For whatever reason I have always thought what would be preferable would be an advocate. A being that would always have your back and be watching out for your best self and for you in general, preventing you from getting screwed by someone trying to make an information asymmetry play or trying to access your data. Somehow I worry that most big companies aren't going to be trying to create something that puts the user first. I'd love to be wrong.
- __Joker 11y ago
  I too hope that there would some Linux equivalent in the personal assistant space. It simply runs on my machine/mobile with my data, and I am totally in control of it. Currently this seems little intractable for availability of data and personal computing power but I hope these will be a lesser concern another decade in future.
  - kybernetikos 11y ago
    Ideally there'd be a standardised api for personal assistants, so you can move between different services or swap the whole thing out for an open source alternative.
graycat 11y ago
"Unsupervised learning"? Well, setting aside the jargon, one approach is just a statistical hypothesis test, and a lot is known about that.
- nl 11y ago
  Unsupervised feature extraction (eg in visual tasks with backprog) goes well beyond what would conventionally be called "a statistical hypothesis test". For example, look at the image of the features learnt by the AlexNet CNN[1]. In a more conventional "statistical hypothesis test" these would be manually defined by hand. IMHO a system that automatically extracts those features itself deserves to be called more than "just a statistical hypothesis test" [1] "Example filters learned by Krizhevsky et al" http://cs231n.github.io/convolutional-networks/ http://cs231n.github.io/convolutional-networks/
  - graycat 11y ago
    Clearly my remark was > ... one approach is just a statistical hypothesis test ... So we have no disagreement. E.g., is this JPG an image of a human face? So, for some variables, extract data on those variables from known (supervised?) human faces and do an hypothesis test with null hypothesis that the JPG is of a human face. Or, are these human faces like those human faces (unsupervised)? Then get data on the variables and do a two sample test with null hypothesis that the two collections of faces are the same, i.e., from the same distribution.
    - nl 11y ago
      Well yeah. But that is like saying that IBM Watson is just a statistical hypothesis test: "Is this answer or this answer correct?" That is absolutely true, and completely useless. The hard part isn't telling the difference once you've done the feature extraction, it's doing the feature extraction automatically itself. (Actually that undersells it too, because you have so many combinations of features to evaluate that making that part work is non-trivial too. But at least that part is just calculus)
graycat 11y ago
He was right: For the progress he is seeking now, neural networks stand to play at most a peripheral role. Instead, he needs some new and quite different ideas. That the networks are neural might mean that they could simulate a worm; that he got more out of them, as, say, non-linear fitting functions, is cute but not much progress for the next challenges he has in mind.

59 points by sconxu 11y ago

FYI this was submitted a few days ago and no one seemed to care: https://news.ycombinator.com/item?id=10521398 https://news.ycombinator.com/item?id=10521398

prawn 11y ago
Sometimes the front page is too busy or something doesn't take. Don't worry about it - they're just internet points. No point linking to it unless there are comments that might also be interesting to readers of these ones, right?
- misiti3780 11y ago
  i could careless - i was under the impression HN had URL dup algorithms to make sure you cant double submitted within a few months of the OP
  - adenadel 11y ago
    I think dang said recently it was something like 8 hours. Beyond that you can resubmit. I've had cases where I've submitted something and it just takes me to the thread where someone else posted it and it automatically gives them an upvote from me.

nicklo 11y ago

Yann gave a talk at my university last week. It's really astounding how far deep learning has come from performing classification and regression to now doing things like reasoning and generation. Does anyone else find this wild? These are tasks that historically required a tremendous amount of domain-specific engineering to perform well. And recurrent memory networks just power right on through them. I understand that learned, dense vector representations are powerful blocks to operate on, but hot damn the trend of general systems that require less domain-specific engineering is an exciting one that blows my mind.

tachyonbeam 11y ago
I definitely find it wild. Recent developments make me very optimistic that I might see useful domestic robots within my lifetime, maybe even something like Data. It definitely seems way less far-fetched now that we have machine learning techniques for semantic segmentation, object and face recognition, reasoning, voice recognition and synthesis and even translation, extracting useful meaning from text/speech.

hyperion2010 11y ago

You know, I see many different big names in the ML field shooting for a personal 'assistant' or something like that. For whatever reason I have always thought what would be preferable would be an advocate. A being that would always have your back and be watching out for your best self and for you in general, preventing you from getting screwed by someone trying to make an information asymmetry play or trying to access your data. Somehow I worry that most big companies aren't going to be trying to create something that puts the user first. I'd love to be wrong.

__Joker 11y ago
I too hope that there would some Linux equivalent in the personal assistant space. It simply runs on my machine/mobile with my data, and I am totally in control of it. Currently this seems little intractable for availability of data and personal computing power but I hope these will be a lesser concern another decade in future.
- kybernetikos 11y ago
  Ideally there'd be a standardised api for personal assistants, so you can move between different services or swap the whole thing out for an open source alternative.

graycat 11y ago

"Unsupervised learning"? Well, setting aside the jargon, one approach is just a statistical hypothesis test, and a lot is known about that.

nl 11y ago
Unsupervised feature extraction (eg in visual tasks with backprog) goes well beyond what would conventionally be called "a statistical hypothesis test". For example, look at the image of the features learnt by the AlexNet CNN[1]. In a more conventional "statistical hypothesis test" these would be manually defined by hand. IMHO a system that automatically extracts those features itself deserves to be called more than "just a statistical hypothesis test" [1] "Example filters learned by Krizhevsky et al" http://cs231n.github.io/convolutional-networks/ http://cs231n.github.io/convolutional-networks/
- graycat 11y ago
  Clearly my remark was > ... one approach is just a statistical hypothesis test ... So we have no disagreement. E.g., is this JPG an image of a human face? So, for some variables, extract data on those variables from known (supervised?) human faces and do an hypothesis test with null hypothesis that the JPG is of a human face. Or, are these human faces like those human faces (unsupervised)? Then get data on the variables and do a two sample test with null hypothesis that the two collections of faces are the same, i.e., from the same distribution.
  - nl 11y ago
    Well yeah. But that is like saying that IBM Watson is just a statistical hypothesis test: "Is this answer or this answer correct?" That is absolutely true, and completely useless. The hard part isn't telling the difference once you've done the feature extraction, it's doing the feature extraction automatically itself. (Actually that undersells it too, because you have so many combinations of features to evaluate that making that part work is non-trivial too. But at least that part is just calculus)

graycat 11y ago

He was right: For the progress he is seeking now, neural networks stand to play at most a peripheral role. Instead, he needs some new and quite different ideas. That the networks are neural might mean that they could simulate a worm; that he got more out of them, as, say, non-linear fitting functions, is cute but not much progress for the next challenges he has in mind.