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Comment on The Future of Machine Learning: A New Breakthrough Technique (MLC)

TropicalDingdong@lemmy.world ⁨1⁩ ⁨year⁩ ago

Traditional deep neural network’s training requires millions of example and so, despite its great success, is immensely inefficient.

Is this a limited advancement in training techniques? Right now I’m working on several types of image classification models. How would this be able to help me?

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A_A@lemmy.world ⁨1⁩ ⁨year⁩ ago
Sorry, I just read a lot… but I don’t work in this field.

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- ripcord@kbin.social ⁨1⁩ ⁨year⁩ ago
  If you don't really understand it, why do you believe this is so big?
  
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  - QueriesQueried@sh.itjust.works ⁨1⁩ ⁨year⁩ ago
    Admittedly, they were quoting someone else in the message you responded to. That may have been edited after the fact, but the person they’re quoting did in fact say those words (“this is big”).
    
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  - A_A@lemmy.world ⁨1⁩ ⁨year⁩ ago
    I am not sure what “image classification models” incompasses. I would have to read more and understand and I don’t have enough time and energy.
    Yet in the past I have read and understand a few books about neural networks and this new article in nature is something else : it’s clear when reading it.
    
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    TropicalDingdong@lemmy.world ⁨1⁩ ⁨year⁩ ago
    I mean is this any different than standard gradient descent with something like Adam as optimiser.
    
    That’s my assumption based on the headline. But the quick skim I gave the article seemed to only discuss it in the context of NLP. Not exactly my field of study.
    
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- TropicalDingdong@lemmy.world ⁨1⁩ ⁨year⁩ ago
  Based on your reading, swag?
  
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