# Deep learning and machine vision see huge improvements



## Amine (Feb 23, 2014)

The Revolutionary Technique That Quietly Changed Machine Vision Forever | MIT Technology Review

Research Blog: Building a deeper understanding of images

http://bits.blogs.nytimes.com/2014/...lot-more-accurate/?_php=true&_type=blogs&_r=0



> The accuracy results this year improved to 43.9 percent, from 22.5 percent, and the error rate fell to 6.6 percent, from 11.7 percent, according to Olga Russakovsky, a Stanford University graduate researcher who is the lead organizer for the contest. Since the Imagenet Challenge began in 2010, the classification error rate has decreased fourfold, she said.


1st link is the best if you go to any of them.

What does this mean? Basically, machines now "see" and recognize objects almost as well as humans--and the rate of improvement seems to be increasing _very_ quickly. Performance basically doubled from 2013 to 2014. That means that in a year or two, machines will see much _better_ than humans.

This has major implications for things like self driving cars, image and video searches, emotion recognition, and more other things than you could think of. Basically any time you might think it useful for a computer to recognize an object.

But that's nothing. The next step, of course, is recognizing the context the objects are in. That's the kind of technology that could lead to something like machines recognizing when a crime is being committed. Sounds an awful lot like human level AI.

We shouldn't forget to mention natural language processing, which is also seeing exponential improvement via the same technique. Computers will be talking to us on a conversational level in a few years... and then they will keep improving beyond us, or something.

Sooner or later someone is going to have the bright idea of training a deep learning system with deep learning research. Then it's going to get weird, really quickly... think: metacognition. Uh oh.

I say: buckle your seatbelts.


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## Tezcatlipoca (Jun 6, 2014)

Also now they can predict avatar motion in a virtual environment. Thank you for your unbridled technological optimism!


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## Amine (Feb 23, 2014)

The OP was entirely neutral as to whether this is good or bad. It's interesting that you saw "unbridled optimism" in it, though. What motivates a person to go around desperately (apparently) searching for optimism to criticize for its own sake?


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## orni (Sep 19, 2012)

Deep learning isn't really some hip new algorithm.
It's just neural networks with more processing capability and improving the efficiency/performance of distributing the load across how ever many thousands of servers they're using.


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## Amine (Feb 23, 2014)

Not sure when I said it was hip and new.. what is up with people being so blase? Guess I'm the only one who is impressed by machines now being able to id objects as well as humans. I'd love to be hearing about the way more impressive shit you guys are onto though.


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## bluekitdon (Dec 19, 2012)

This type of stuff is really interesting to me. I've been working in the IT field for 20+ years and it is incredible how far we've come. When I was growing up we didn't even have computers around. Now my cell phone can do more than my computer could do 10 years ago. I think we're going to see computers just continue to improve to the point that they're better than humans at a lot of things humans typically do. Moore's law says that computing power doubles about every two years which has been the case for a long time...factor what we have today and keep doubling that every few years.

Here's some interesting thoughts.

Medical field - in the US there is a push towards meaningful use with computing in healthcare, meaning that computers should help with diagnosis and suggest the best treatment based on the patient's entire medical history and histories of comparable patients






Cars - how long before a self driving car is better than a human driver? At what point do people start saying human drivers have 2x or 3x more crashes than computer driven cars so maybe that should be eliminated for safety purposes?


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## Amine (Feb 23, 2014)

@bluekitdon

Good points. That is going to be some world-changing stuff in a few years, and few people seem to realize it or care. Watson is doing incredible things in the field of medicine. Apparently he is, IIRC, better at diagnosing cancer than doctors now... they've also developed something called "Discovery Adviser" which can read tens of thousands of research papers in a day and come up with actionable hypotheses which would have taken humans years or decades to do.

That's nothing short of mindblowing.

As for self driving cars, my guess is that by 2018 we will start to see them on highways but not city streets. Cadillac just broadcasted that they have plans to make this happen in their 2017 models. The consensus on city driving seems to be a couple years after that. Probably be seeing a few of them in 2020, a lot in 2025. Which is awesome, because in the US 35k people die in accidents every year, 90% of which are due to human error. Humans are actually terrible drivers.


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## bluekitdon (Dec 19, 2012)

This is pretty neat. Give a little blood for DNA, get a customized plan for whatever ails you. Just a matter of time before we have the medical tricorders from Star Trek.





Speaking of tricorders...





It's a pretty amazing time to be alive. I can't imagine what we'll see in our lifetimes. Just look around and realize there are people still alive that never had cars when they were kids because they just weren't widely available, they saw the invention of TV, radio, telephones, computers. I am actually old enough to have lived in a rural area with party lines where we shared the same phone line with our neighbors so you had to take turns with your family and the neighbors if you wanted to use the phone. That's pretty insane compared to the cell phones of today.


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## Amine (Feb 23, 2014)

^This guy gets it.


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## orni (Sep 19, 2012)

Oh ok I thought you were talking about deep learning, not the 'future of AI' and look how far we've come


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## Amine (Feb 23, 2014)

This just came out and is very! impressive. It is one thing for computers to recognize objects in pictures, which they can do pretty well now. What we see here is the beginning of contextual understanding. Not just nouns but verbs and adjectives as well. 

Keep in mind, progress in this field is doubling every year. That means big things. Soon computers will be able to, say, watch videos and explain what is happening. And then they will be able to do it better than humans. Say it is watching a large crowd of people all doing different things at a festival. It could achieve near omniscience about that event, as it isn't limited by a narrowing of attention like humans. It could simultaneously be understanding what every single person in the crowd is doing. It could perhaps even figure out emergent patterns humans are incapable of seeing.


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## RobynC (Jun 10, 2011)

@_Amine_



> What does this mean? Basically, machines now "see" and recognize objects almost as well as humans--and the rate of improvement seems to be increasing _very_ quickly. Performance basically doubled from 2013 to 2014. That means that in a year or two, machines will see much _better_ than humans.


I'm aware of this...



> The next step, of course, is recognizing the context the objects are in. That's the kind of technology that could lead to something like machines recognizing when a crime is being committed. Sounds an awful lot like human level AI.


Actually there already are computers that can recognize suspicious activity. 

However what you describe does sound valid. Of course, people like you fail to listen to people, even smart people like Elon Musk, Stephen Hawking, and Bill Joy all talking about the dangerous of runaway A.I....



> We shouldn't forget to mention natural language processing


You mean like speech recognition? This has actually been around for a long time



> Sooner or later someone is going to have the bright idea of training a deep learning system with deep learning research. Then it's going to get weird, really quickly... think: metacognition. Uh oh.


1. What's deep-learning

2. What's metacognition?



> Cars - how long before a self driving car is better than a human driver? At what point do people start saying human drivers have 2x or 3x more crashes than computer driven cars so maybe that should be eliminated for safety purposes?


Probably very soon: I don't consider this to be a good thing though you'll probably think it's the best thing since sliced bread.

Google's developed an automated car without a steering-wheel. I figured they'd go at least two to three years before removing driver control from the equation.


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## an absurd man (Jul 22, 2012)

@RobynC This will interest you:
https://medium.com/the-physics-arxi...y-decide-whether-to-kill-a-human-7c014623c13f


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## marbleous (Feb 21, 2014)

So here is some research going on at my uni. It's basically virtual reality project that tracks the position of people in the room which is surrounded by cameras, projectors, and speakers, and can change the acoustics and projected images to simulate you are actually in that environment, with the correct depth perceptions! To begin with, tracking people can mean turning on/off appliances when you leave, making an interactive computer screen from a projected image, virtual reality movie theaters. It's pretty awesome.

CRAIVE-Lab | [email protected]

Now before all the cynics jump on me saying "this has been done before, nothing new, blah blah blah," obviously it's been done before, but the point is that it is growing in prominence. Computer vision is becoming an extremely hot area of research which makes sense because high precision sensors are becoming cheaper and cheaper. We have all the information we need, it is now the challenge of figuring out how to interpret that data. OP, I share your sentiments and have been thinking about it a lot. Sensors are now better than our eyes at seeing, our ears at hearing, etc. But they are not yet as good as recognizing things as we are! But they will be because people are smart and can figure these things out!

OP you are right, it is growing more now than it has ever before and it is an amazing thing! Now more than ever, we need the smartness of people to figure out intelligent ways to use all of this sensory data. I love how many opportunities for smartness this opens up. Despite being more "reliant on technology," this generation is being challenged to do things that computers cannot do, teaching computers how to be human.

I personally am a fan of autonomous cars. Hours of wasted time commuting back and forth to work can be converted into productive hours, like sleeping!


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## RobynC (Jun 10, 2011)

an absurd man said:


> @_RobynC_ This will interest you:
> https://medium.com/the-physics-arxi...y-decide-whether-to-kill-a-human-7c014623c13f


1. I agree that one should not create a weapons system to kill people that is autonomus

2. The halting problem has some flaws: In the event of two horrible situations there could be one less bad than the other; in the event that both are equally bad, it's possible to include a program that would automatically select one based on some kind of algorithmic sequence much like a person rolling dice.

3. In the event that a self-directed machine makes a bad decision and kills, provided it is sufficiently advanced and adaptable: It would bear the blame for the action as a person does with some exceptions as in the criminal justice system


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## nichya (Jul 12, 2014)

Stanford University CS231n: Convolutional Neural Networks for Visual Recognition

I have been studying deep neural networks all day :bored:

Well the interesting thing here is neural networks are inspired by human brain and you don't need to make too much hard information training unlike older models, say a human is able to recognize an eye of a whale and an eye of a human. Older methods vary but they try to solve the problem with ridiculous low level features, in the simplest form: pixels. Which makes not much sense to human perception.

Anywho, also notice how smooth the sentences are generated?


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## Tezcatlipoca (Jun 6, 2014)

@Amine

How Google "Translates" Pictures Into Words Using Vector Space Mathematics | MIT Technology Review

They use the same technique that they were using for language transcription

How Google Converted Language Translation Into a Problem of Vector Space Mathematics | MIT Technology Review

Wolf ram's mathematica can also identify voices

http://m.phys.org/news/2014-12-voice-mathematica-impersonations.html


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## RobynC (Jun 10, 2011)

@Tezcatlipoca

We already have technology that can identify voices


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## Primeval (Dec 4, 2011)

RobynC said:


> @Tezcatlipoca
> 
> We already have technology that can identify voices


So because the technology already exists, examples of it are inherently boring? 

I think this stuff is awesome.


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## RobynC (Jun 10, 2011)

@Primeval

No, I'm just saying that it isn't a new development


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## nichya (Jul 12, 2014)

It is about doing it better, more natural, more humane


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## Amine (Feb 23, 2014)

Speech recognition has a long way to go. I'd give it a C- right now. When it can understand my friend with a speech impediment as well as I can as he is talking as he normally talks in conversation, I'll give it an A. When it can pick out the separate conversations of every person in a crowded room simultaneously, I'll give it an A+.


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## Tezcatlipoca (Jun 6, 2014)

Neural Network Rates Images for Happiness Levels | MIT Technology Review

Machine vision has been exploding the last month



Amine said:


> Speech recognition has a long way to go. I'd give it a C- right now. When it can understand my friend with a speech impediment as well as I can as he is talking as he normally talks in conversation, I'll give it an A. When it can pick out the separate conversations of every person in a crowded room simultaneously, I'll give it an A+.


Name that voice: Mathematica catches impersonations


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## Amine (Feb 23, 2014)

https://gigaom.com/2015/02/13/micro...er-vision-system-can-outperform-humans_914914

Progress in the last few months. Microsoft just released a machine vision report claiming to get an error rate safely below humans... which isn't surprising considering it can not only name common objects but also identify species of fauna and flora virtually no untrained person could. 

I figured that was coming, maybe not so soon. It's amazing they've made this amount of progress in just a few months. By the end of the year these things will be pretty incredible, and then further into the future we will have things like context recognition in videos. You might be able to take a walk with AR glasses and easily identify plant life species, or search youtube videos based on spoken text within the video. For example.


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## Cesspool (Aug 8, 2014)

RobynC said:


> 1. I agree that one should not create a weapons system to kill people that is autonomus
> 
> 2. The halting problem has some flaws: In the event of two horrible situations there could be one less bad than the other; in the event that both are equally bad, it's possible to include a program that would automatically select one based on some kind of algorithmic sequence much like a person rolling dice.
> 
> 3. In the event that a self-directed machine makes a bad decision and kills, provided it is sufficiently advanced and adaptable: It would bear the blame for the action as a person does with some exceptions as in the criminal justice system


Sometimes you need to sacrifice the few, for the many.


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## RobynC (Jun 10, 2011)

@Cesspool

What are you talking about?


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## Cesspool (Aug 8, 2014)

RobynC said:


> @Cesspool
> 
> What are you talking about?


A machine choosing who dies based on a logical process every once in a blue moon is better than humans being in control and people dying by accident far more often.

EDIT: I think I misunderstood your initial post that I responded to.


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## RobynC (Jun 10, 2011)

@Cesspool



> A machine choosing who dies based on a logical process every once in a blue moon is better than humans being in control and people dying by accident far more often.


I disagree: We are a society of humans; we should be led by humans.

Plus, your premise could easily be flawed: An intelligent entity could easily decide that it would better for the whole human race to die off and decide we should all be killed.


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## CaptSwan (Mar 31, 2013)

Cesspool said:


> A machine choosing who dies based on a logical process every once in a blue moon is better than humans being in control and people dying by accident far more often.
> 
> EDIT: I think I misunderstood your initial post that I responded to.


You do realize even machines can't predict the randomness of the universe as a whole, right? Also, it's rather silly to make the assumption that a machine would make a better choice. By your logic, individuals who made great contributions to the human race would be eliminated before they even did anything; because they "wouldn't fit criteria". Your option may appear to make sense at plain sight; but, you have to see that, if led to efficiency; machine ruling would inevitably lead to the anhilation of all organic species, especially humans because of aspects like "design efficiency" or some other computer-themed reason.


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## Word Dispenser (May 18, 2012)

Cesspool said:


> Sometimes you need to sacrifice the few, for the many.


Yeah, like.. Let's sacrifice, and cut out the organs of this perfectly healthy kid so he can give his organs to 10 people who need them. :kitteh:


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## nichya (Jul 12, 2014)

This is a good read really, although I love the hype and can't lie, I also like the cult science and kurzweil, that is an INFP for you in science )) I am aware of the impossibility but I just want to believe and pretend we will be there soon enough in my lifetime. LeCun is the real deal though, he knows what he is talking about, although as you will notice fails miserably at being a cult leader 

Facebook AI Director Yann LeCun on His Quest to Unleash Deep Learning and Make Machines Smarter - IEEE Spectrum


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