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Machine Learning Confronts the Elephant in the Room

quantamagazine.org

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Re: Machine Learning Confronts the Elephant in the Room

#11

Post by antpls »

The title is a bit misleading / clickbait. It should be "Neural networks Confronts...". Machine Learning isn't all about neutral networks and deep learning.

As another comment said, "second take" is not what neural networks are made for. Neural networks are a building block of more complex decision systems, where the weakness of the neural networks are taken into account before automatically commiting to decisions.

Otherwise, I guess the article is good at pointing the current limitation of neural networks alone.

Re: Machine Learning Confronts the Elephant in the Room

#12

Post by sorokod »

TheArcane wrote: post #10
sorokod wrote: post #6

Is this not a whole new attack surface?

Not really. In addition to object classes, object detection networks learn to ID teh context of an object's presence. In almost every scenario, this context is a desirable learning trait.

How about a scenario where an image of an elephant ( or any other out of context example ) is projected on purpose with intent to cause damage?

Re: Machine Learning Confronts the Elephant in the Room

#14

Post by antpls »

majos wrote: post #9
doombolt wrote: post #5

Wrong. They can do a second take. You should just code it in.

Is this sarcasm? The point of the second take is that humans often know they're confused and will go back to think about the image and remedy the confusion, whereas having a neural network just look at the image again isn't going to do anything (plus, existing architectures don't seem to have any capacity to say "I'm confused" anyway).

Parent is not sarcastic. Automated recognition systems are systems, which means they are made of several components (sensors, databases, hardwares, softwares) working together. Neural networks are one of those sub-components and no one ever claimed that neural networks are 100% accurate and sufficient to build automated decision systems.

The problem described in the article is taken into account when building systems (like autonomous cars) using neural networks.

Re: Machine Learning Confronts the Elephant in the Room

#15

Post by LeanderK »

antpls wrote: post #11

The title is a bit misleading / clickbait. It should be "Neural networks Confronts...". Machine Learning isn't all about neutral networks and deep learning. As another comment said, "second take" is not what neural networks are made for. Neural networks are a building block of more complex decision systems, where the weakness of the neural networks are taken into account before automatically commiting to decisions. O…

i wouldn't be so critical. It's journalism and I would intrepret the title more as "Machine Learning-community confronts...".

And while ML isn't all about NNs and deep learning, we're quite enticed by them right now and try to push them to see where their limitations are. So I think with a bit more generous interpretation the title is acceptable. I think it's certainly not clickbait, since NNs are right now a very significant part of the ML-research landscape.

Re: Machine Learning Confronts the Elephant in the Room

#16

Post by calhoun137 »

In this article, learn the secret AI researchers dont want you to know, my non tech friends love talking about it! Gonna have to agree with everyone else here, the title is clickbait and you can just code around it.

There is nothing fatal here its just one more problem to solve. Havent we heard all about this issue of image recognition being trickable 1000 times, why is this the top post?

Re: Machine Learning Confronts the Elephant in the Room

#18

Post by sorokod »

antpls wrote: post #14
majos wrote: post #9

Earlier quoted context omitted.

Is this sarcasm? The point of the second take is that humans often know they're confused and will go back to think about the image and remedy the confusion, whereas having a neural network just look at the image again isn't going to do anything (plus, existing architectures don't seem to have any capacity to say "I'm confused" anyway).

Parent is not sarcastic. Automated recognition systems are systems , which means they are made of several components (sensors, databases, hardwares, softwares) working together. Neural networks are one of those sub-components and no one ever claimed that neural networks are 100% accurate and sufficient to build automated decision systems. The problem described in the article is taken into account when building system…

The problem described in the article is taken into account when building systems (like autonomous cars) using neural networks.

Where can I find more information on this?

Re: Machine Learning Confronts the Elephant in the Room

#19

Post by ag71668 »

calhoun137 wrote: post #16

In this article, learn the secret AI researchers dont want you to know, my non tech friends love talking about it! Gonna have to agree with everyone else here, the title is clickbait and you can just code around it. There is nothing fatal here its just one more problem to solve. Havent we heard all about this issue of image recognition being trickable 1000 times, why is this the top post?

Yeah, rubbish clickbait article which at best misleads uniformed readers.
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