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How to build a robot that “sees” with $100 and TensorFlow

oreilly.com

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Re: How to build a robot that “sees” with $100 and TensorFlow

#21

Post by kowdermeister »

Swizec wrote: post #7
taneq wrote: post #6

Earlier quoted context omitted.

Like so many other things in the field of AI, general object recognition was the "holy grail" because it was assumed that it required AGI. Now we've figured out a way to do general object recognition without AGI.

Whenever we figure out how to do something, we stop calling it AI or AGI. If the trend continues, will we eventually have a general AI, but won't consider it anything special? Will it have been just a small incremental step by then?

I think it will need some kind of breakthrough. Current advancements are probably incremental as you stated, but having an AGI might need some new theory we don't have currently.

Re: How to build a robot that “sees” with $100 and TensorFlow

#23

Post by dharma1 »

bernardopires wrote: post #15

Just a nit, but the author keeps talking about object recognition while what he was actually doing is image classification. Object recognition actually consists of two tasks, one is classifying the object (this is a beer bottle) and the other is also says where in the image the object is. Additionally it can/should detect multiple objects in the image. This is a more complex than classification, which only associates…

http://pjreddie.com/darknet/yolo/, https://github.com/daijifeng001/MNC, https://bitbucket.org/aquariusjay/deeplab-public-ver2 or similar should do the job. Choose depending on how fast it needs to be, and how accurate the segmentation boundaries need to be

Re: How to build a robot that “sees” with $100 and TensorFlow

#24

Post by xiphias »

kowdermeister wrote: post #21
Swizec wrote: post #7

Earlier quoted context omitted.

Whenever we figure out how to do something, we stop calling it AI or AGI. If the trend continues, will we eventually have a general AI, but won't consider it anything special? Will it have been just a small incremental step by then?

I think it will need some kind of breakthrough. Current advancements are probably incremental as you stated, but having an AGI might need some new theory we don't have currently.

Deep learning is the opposite of incremental. For a long time it was not clear whether/how we can learn multi layer networks efficiently. ImageNet changed everything.

Re: How to build a robot that “sees” with $100 and TensorFlow

#25

Post by sidarape »

dharma1 wrote: post #14
icemelt8 wrote: post #3

This was amazing, I am amazed at your command of both hardware and software technology. Even as a Software Engineer, I have a hard time trying to make TensorFlow do something for me.

To do the task in the article (classify images, pretrained model) - it's pretty easy - just follow the tutorial here: https://www.tensorflow.org/versions/r0.10/tutorials/image_re...

I tried that (https://www.tensorflow.org/versions/r0.9/how_tos/image_retra...) which seems to work well.

Re: How to build a robot that “sees” with $100 and TensorFlow

#26

Post by bonoboTP »

bernardopires wrote: post #15

Just a nit, but the author keeps talking about object recognition while what he was actually doing is image classification. Object recognition actually consists of two tasks, one is classifying the object (this is a beer bottle) and the other is also says where in the image the object is. Additionally it can/should detect multiple objects in the image. This is a more complex than classification, which only associates…

I don't think there's a consistent terminology. In my computer vision class we called it "object recognition" when it was about recognizing one specific object (this particular car) and "object classification" when deciding the category of the object in the image (in general, like 'car', 'bottle').

One may also call the localization of the object as object detection and subsequent classification.

But I don't think it's too important how we call it as long as we understand what the task is.

Re: How to build a robot that “sees” with $100 and TensorFlow

#27

Post by bonoboTP »

argonaut wrote: post #8
taneq wrote: post #6

Earlier quoted context omitted.

Like so many other things in the field of AI, general object recognition was the "holy grail" because it was assumed that it required AGI. Now we've figured out a way to do general object recognition without AGI.

Is there a story somewhere of AI researchers concluding general object recognition was the holy grail of AI? I get that a lot of people downplay achievements in machine learning by saying it's nothing like AGI, but it's almost a meme now that "once upon a time everyone thought that was the holy grail and they're moving the signposts" even when 1) nobody thought that, or 2) some people thought that and some people did…

In fact, the first thing you learn in an introductory computer vision class is that Marvin Minsky assigned "computer vision" to an undergrad as a summer project in 1966 (wire up a camera to a computer and write a program to understand images). It was the opposite of a holy grail.

Even today, it's hard to make laymen appreciate the advancements in computer vision because for them "seeing" doesn't seem like a difficult thing. Even stupid chickens can see. A chess program is much more impressive to laypeople.

Re: How to build a robot that “sees” with $100 and TensorFlow

#28

Post by bonoboTP »

xiphias wrote: post #24
kowdermeister wrote: post #21

Earlier quoted context omitted.

I think it will need some kind of breakthrough. Current advancements are probably incremental as you stated, but having an AGI might need some new theory we don't have currently.

Deep learning is the opposite of incremental. For a long time it was not clear whether/how we can learn multi layer networks efficiently. ImageNet changed everything.

Machine learning people basically agree that there weren't any big breakthroughs in deep learning. The success and the hype is mostly a combination of more computing power and more data. The algorithms (convolutional neural network etc.) were invented back in the 1980s and even earlier.

There have been some improvements but they are incremental indeed. More use of ReLU, dropout etc. But it's not a new paradigm at all.

Re: How to build a robot that “sees” with $100 and TensorFlow

#29

Post by bbctol »

Swizec wrote: post #7
taneq wrote: post #6

Earlier quoted context omitted.

Like so many other things in the field of AI, general object recognition was the "holy grail" because it was assumed that it required AGI. Now we've figured out a way to do general object recognition without AGI.

Whenever we figure out how to do something, we stop calling it AI or AGI. If the trend continues, will we eventually have a general AI, but won't consider it anything special? Will it have been just a small incremental step by then?

I think deep, natural language processing will be unambiguous: if you create a machine that says "Yes, I am intelligent, thanks for asking" in a way indistinguishable from a human, it would be hard to disagree. On the other hand, it's entirely possible that that goal will take so much longer than others we'll have incredibly strong AIs affecting our lives before we notice.

Re: How to build a robot that “sees” with $100 and TensorFlow

#30

Post by bonoboTP »

taneq wrote: post #6
rbanffy wrote: post #4

> recognizing arbitrary objects within a larger image has been the Holy Grail of artificial intelligence The Holy Grail is general AI. Recognizing objects is a side quest, perhaps a required step, but, by no means, the end goal.

Like so many other things in the field of AI, general object recognition was the "holy grail" because it was assumed that it required AGI. Now we've figured out a way to do general object recognition without AGI.

I think a "holy grail" could be understanding complicated intentions and social reasoning. Like "he's only doing that so that it seems that he thinks that the other girl doesn't know that he could otherwise not do the etc. etc."

And general common sense reasoning.

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