3 ms·

It's quite easy to explain. You take a bunch of tensors and multiply them by a bunch of tensors. Humans can't wrap their heads around multiple tensors being mu

by joxel 4y ago

It's quite easy to explain. You take a bunch of tensors and multiply them by a bunch of tensors. Humans can't wrap their heads around multiple tensors being multiplied together and never will. It's not a problem with AI. It's a problem with humans. It's not AIs fault that we can understand F=ma but can't understand 50 tensors being stacked.

djmips 4y ago
That's like saying you can explain how some code works by saying you take a bunch of transistors and turn them off and on.
datpiff 4y ago
>It's not a problem with AI. It's a problem with humans. It's not AIs fault This is a really, really funny defense of AI.
- joxel 4y ago
  Why? How is it AI's fault that it can solve problems humans have proven unable to solve? And then you think it's AI's fault when we can't explain how it's solving the problems we can't solve? There's a reason we can't explain why a neural network detects it as a cat or dog, it's because we can't solve it ourselves, so the exact mathematical intuition is literally beyond our ability to describe (so far).
  - aliqot 4y ago
    "How can a thousand monkeys solve what humans can't solve"
    - joxel 4y ago
      That is not analogous
      - deleted 4y ago
        [deleted]
      - aliqot 4y ago
        Tell me how a GAN works. it's 1000 pedantic monkeys trying to out-HN the other. At the root of all AI is a similar process.
        joxel 4y ago
        Comparing brute force to backpropogation with stochastic gradient descent shows you don't understand the process, or are being purposefully obtuse.
noobermin 4y ago
I can't believe you think the tediousness of a calculation means "humans can't understand it." You should look into multi loop calculations in quantum field theory.
mdp2021 4y ago
> You take a bunch of tensors No, radically not. That is not the kind of understanding we seek. The advance in knowledge is given by, e.g., "simulated annealing returned a blueprint for very odd circuit schematic with No-Op loops: we were puzzled but then understood they were there to correct timing". And this is not the level of explanation where tensors are.
deleted 4y ago
[deleted]
ripe 4y ago
> tensors multiplied by tensors This argument is ignoring the problem. What a neural network cannot do is to explain which invisible "rules" it has learned. For example, when trying to classify movie reviews into good and bad [1], two invisible rules that it learned to apply were: 1. The word "horrible" indicates a bad review. 2. The term "Daniel Day Lewis" indicates a good review. A human would judge the first rule to be reasonable, the second rule to be a mistake. [1] https://www.science.org/content/article/how-ai-detectives-are-cracking-open-black-box-deep-learning https://www.science.org/content/article/how-ai-detectives-ar...

by joxel 4y ago

djmips 4y ago

That's like saying you can explain how some code works by saying you take a bunch of transistors and turn them off and on.

datpiff 4y ago

>It's not a problem with AI. It's a problem with humans. It's not AIs fault This is a really, really funny defense of AI.

joxel 4y ago
Why? How is it AI's fault that it can solve problems humans have proven unable to solve? And then you think it's AI's fault when we can't explain how it's solving the problems we can't solve? There's a reason we can't explain why a neural network detects it as a cat or dog, it's because we can't solve it ourselves, so the exact mathematical intuition is literally beyond our ability to describe (so far).
- aliqot 4y ago
  "How can a thousand monkeys solve what humans can't solve"
  - joxel 4y ago
    That is not analogous
    - deleted 4y ago
      [deleted]
    - aliqot 4y ago
      Tell me how a GAN works. it's 1000 pedantic monkeys trying to out-HN the other. At the root of all AI is a similar process.
      - joxel 4y ago
        Comparing brute force to backpropogation with stochastic gradient descent shows you don't understand the process, or are being purposefully obtuse.

noobermin 4y ago

I can't believe you think the tediousness of a calculation means "humans can't understand it." You should look into multi loop calculations in quantum field theory.

mdp2021 4y ago

> You take a bunch of tensors No, radically not. That is not the kind of understanding we seek. The advance in knowledge is given by, e.g., "simulated annealing returned a blueprint for very odd circuit schematic with No-Op loops: we were puzzled but then understood they were there to correct timing". And this is not the level of explanation where tensors are.

deleted 4y ago

[deleted]

ripe 4y ago

> tensors multiplied by tensors This argument is ignoring the problem. What a neural network cannot do is to explain which invisible "rules" it has learned. For example, when trying to classify movie reviews into good and bad [1], two invisible rules that it learned to apply were: 1. The word "horrible" indicates a bad review. 2. The term "Daniel Day Lewis" indicates a good review. A human would judge the first rule to be reasonable, the second rule to be a mistake. [1] https://www.science.org/content/article/how-ai-detectives-are-cracking-open-black-box-deep-learning https://www.science.org/content/article/how-ai-detectives-ar...