12 ms·

The AI Revolution Hasn’t Happened Yet

270 points by wei_jok 8y ago

mexus 8y ago
A related talk that Michael Jordan gave at a machine learning conference called Sys ML last month. https://youtu.be/4inIBmY8dQI https://youtu.be/4inIBmY8dQI
- cbHXBY1D 8y ago
  To anyone upset by MJ's Medium post, please watch the video. It's a much better representation of his thoughts on the current state of machine learning than the blog post.
- johnx123-up 8y ago
  Thanks for sharing. I'm also glad that I met this guy http://rajeshanbiah.blogspot.co.uk/2018/01/technology-prediction-for-2018.html http://rajeshanbiah.blogspot.co.uk/2018/01/technology-predic... who is having profound knowledge in predicting technologies and bubbles
eanzenberg 8y ago
I saw Prof. Jordan give this talk in person, and the 2nd paragraph resonated with me. I wish there was more critical thinking involved in science/research/higher ed/industry but unfortunately most there's a lot of cheap money floating around with "experts" slurping it up without care for outcome. "But the episode troubled me, particularly after a back-of-the-envelope calculation convinced me that many thousands of people had gotten that diagnosis that same day worldwide, that many of them had opted for amniocentesis, and that a number of babies had died needlessly."
- tlarkworthy 8y ago
  Like we have defensive programming: assert this field is not a stupidly large number. Perhaps we can encode our assumption as probabalisic asserts, and defensively encode that our assumptions are not violated. E.g. the current distribution looks like my training data.
visarga 8y ago
Well said: > Thus, just as humans built buildings and bridges before there was civil engineering, humans are proceeding with the building of societal-scale, inference and decision making systems that involve machines, humans and the environment. Just as early buildings and bridges sometimes fell to the ground — in unforeseen ways and with tragic consequences — many of our early societal scale inference and decision making systems are already exposing serious conceptual flaws.
- return1 8y ago
  that's a trivial statement, unless he can suggest a different way to do things. Should people have held off building any bridges, until the 20th century arrived ? Building things and science have always evolved side-by-side in a feedback loop.
  - blacksmith_tb 8y ago
    I'm not sure it was intended to be read "Can't win? Don't try." An interesting corollary to that analogy is that some of the things humans built thousands of years ago are still standing... so it's possible some of our systems could also pass the test of time (they can be optimized more easily than a bridge).
    - return1 8y ago
      he does point elsewhere that machine learning solutions must account for "long tail" data , so it seems to me he 's looking for perfect solutions that will never exist.
  - rdlecler1 8y ago
    Actually it’s not a trivial statement. He’s saying that we don’t have enough theory guiding us and instead we just spin up a tensorflow library without having any clue what’s going on underneath the hood. And I don’t mean understanding linear algebra in neural networks, I mean we don’t have a good theory of computation for Artificial neural networks like we do for Boolean electronic circuits. There is a little bit of work out there, but no one seems to be interested in the theory and why these work. The fact that we still represent networks as fully connected when many many of those weights w_ij are completely spurious tells me that we don’t spend enough time figuring out what’s going on and instead focus on the result. And this lack of attention will be why we’ll hit another wall. We should be reverse engineering intelligence and comparing that to AI so that we can build up the theoretical equivalent of aerodynamics.
deft 8y ago
I'm not an AI researcher (although from my internet reading that's not a hard title to claim ;)) but I feel that ML/DL can't go much farther than they already have. The concept of "we just need more power" is an obvious fallacy to me.
- pretendscholar 8y ago
  Why don't you think it will continue to progress?
  - shoguning 8y ago
    I am of a similar opinion. There was a real revolution in ~2011-2013 with deep learning. These have achieved much better results in image/speech tasks. These gains have leveled off, and we're seeing some limitations. At current trajectory, we're not headed towards a general intelligence. Progress has been made, but there are big gaps. Smart home devices are a great case in point. They are somewhat flexible in the voice commands they accept. Specific phrasing and pronunciation are not necessarily required. Their responses and speech, however, are all pre-programmed and templated by humans. Edit: There is potential for more breakthroughs in the future, but I am not seeing them on the horizon at the moment.
    - placebo 8y ago
      Well, reinforcement learning should also be given a mention and revolutions there (e.g AlphaGo to AlphaZero) were much more recent
    - riyadparvez 8y ago
      Post-2013 breakthroughs off top of my head are: * Wavenet, now productionized at Google as text to speech * Alpha[Go]Zero * Neural Machine Translation, on production at Google
      - shoguning 8y ago
        AFAIK, these are all implementations of deep learning or similar, not a fundamentally new architecture. We'll continue to see these as DL matures, but it doesn't address the shortcomings of the technique. For more perspective: https://arxiv.org/abs/1801.00631 https://arxiv.org/abs/1801.00631
Talyen42 8y ago
The biggest challenge yet unconquered is getting your "average" business ($1-100m revenue, zero AI knowledge) using ML to help with literally anything they do. I'd wager less than 1% of businesses outside of SV even have a clue where to begin, or what to use it for, my employer included. "Do we hire some AI guys?" We'll need to crack the 1%-using-it mark for me to consider the revolution "begun"...
- zapita 8y ago
  Considering that the average business is unlikely to be writing any sort of software, other than perhaps basic Excel formulas... I wouldn't hold my breath waiting for them to use advanced software development techniques such as ML.
  - lifeisstillgood 8y ago
    I would suggest that not writing any sort of software is a good proxy for going out of business soon. I also think you would be surprised at how many businesses both do, and really want and value, software - but don't have anyone convincing to do it for them
    - TeMPOraL 8y ago
      I increasingly feel that almost every business would benefit from having someone with programming experience on-board. This comes from observing that businesses tend to have a lot of ad-hoc processes and unique requirements, for which there is no software package to buy - not without throwing away huge parts of the processes and rebuilding them in a "standard" way. However, a lot of those unique areas could be improved with a help of someone who's capable of writing small programs and scripts to glue things together. A random example: my SO often works with high-res photos of their products, and sometimes this involves modifying them to suit the random requirements of other businesses. Something I currently solve for her by running ImageMagick one-liners if she needs more than a few photos modified. A person with basic familiarity of shell scripting and CLI tools could improve their workflow and keep improving it on-demand, as the requirements change.
deleted 8y ago
[deleted]
nicodjimenez 8y ago
Michael Jordan is just mad he missed the boat on deep learning. Must be tough being that brilliant and at the same time get left in the dust by algorithms from the 90's and just sheer brute force. The AI revolution is here, from Google search to Uber pool to auto correct to recommendation engines, it is just a slow process.
- Ar-Curunir 8y ago
  Lol Michael Jordan is at the forefront of ML, Stats, and yes, deep learning. He's not missed any boat.
  - nicodjimenez 8y ago
    Michael Jordan is a mathematician far more than an engineer. I've never heard of any deep learning papers or open source software coming from his lab. Like a lot of mathematicians though working in stats and ML, he's been forced to adapt. There is lots of resentment amongst mathematicians about the current AI revolution, to me this reeks of that. I could be wrong!
  - nicodjimenez 8y ago
    And also Michael Jordan is definitely _not_ at the forefront of deep learning or deep learning research (he definitely is in stats, no question). His lab is not even in the top 20 labs in the country for deep learning research. Also IMO nearly all the people at the forefront of deep learning are in industry right now.
- AndrewKemendo 8y ago
  I have to assume you're not familiar with his lab at all then: http://bair.berkeley.edu/blog/?refresh=1 http://bair.berkeley.edu/blog/?refresh=1 I mean one of their papers on the stuntmen was on the front page of HN recently. They are most certainly on the forefront.
  - nicodjimenez 8y ago
    ??? that's not his lab, it's a blog site whose sole faculty advisor is Sergey Levine. I don't want to be a hater here, I'm just stating facts that M.J. is first and foremost a mathematician, and that deep learning has been tough for mathematicians in ML / stats.
John_KZ 8y ago
The AI Revolution is happening right now. There's enormous proven potential which is materializing in ever increasing rates. The first generations of hardware accelerators are slowly coming out and they're going to leave everyone astounded. It's a bit like the early days of the internet, it's not always the most practical solution, but it definitely works.
- taurath 8y ago
  Do you have any examples?
- deft 8y ago
  This exact tired old argument is being applied to: blockchain / DLT AI VR CRISPR in some senses Unless you have a reason to compare it to the "early days of the internet", don't. A technology being new and unknown doesn't make it like the internet.
- crististm 8y ago
  If it were there would be no one denying it. I don't see _that_ though so my conclusion is that, no, there is no revolution yet.
taurath 8y ago
I’ve been finding it difficult to find concrete examples of where AI is useful. Suggestion engines? Alg optimization? What would be something my parents would recognize that is being helped by AI?
- zeofig 8y ago
  The key is to not think about it too much. Your "logic" has no place here. Anyway, once the revolution hits your parents are gonna have those autonomous microwaves and self-cooling doctorbots they've been craving. The future is very, very, very bright.
- mathgenius 8y ago
  The Google search engine.
- fvdessen 8y ago
  - Self-driving cars - Camera that make better looking pictures - Better looking movies / videogames - Better medical diagnostics. - Face recognition - City surveillance; finding criminals, lost children.
- Ar-Curunir 8y ago
  Voice assistants like Alexa, Siri, etc.
- choxi 8y ago
  I like the category of "augmenting human skills". Google's Quick Draw is an example of augmented drawing, but you could use the same concept for writing, creating music, even programming. DeepFakes are basically the beginning of augmented video production. Imagine if you didn't need a green screen and body tracking suits to replace any person or scene in a movie with whatever you want. The whole field of generative deep learning is interesting and, to me, a really unexpected result of AI research.
prolikewhoa 8y ago
What are we defining as AI now? It seems like AI has had a lot of hype in the past few years, but I really don't think we're even close unless it's created by mistake. We don't understand the brain fully, we don't understand consciousness, we just know so little in the grand scheme of things. Do we have the computing power to come anywhere close to what we need, will we have that computing power any time soon without a major breakthrough?
- Ar-Curunir 8y ago
  Did you read the article? Some of your questions would have been answered
msteffen 8y ago
> The problem had to do not just with data analysis per se, but with what database researchers call “provenance” — broadly, where did data arise, what inferences were drawn from the data, and how relevant are those inferences to the present situation? Plug: I work at a company (https://www.pachyderm.com https://www.pachyderm.com) whose product is designed precisely to track data provenance across pipelines and through a company's larger data-processing operation for this reason
- TTPrograms 8y ago
  You all should really play that up more in your messaging - "provenance" is one of the hardest and least-addressed components of building AI/ML/data science systems that actually have measurable impact (rather than analysts making plots and speculating). In general having a structured, centralized representation of business processes is super valuable I'm sure. If you write a blog post describing how critical that is to practical data science efficacy with some examples I bet you'll end up in a bunch of VP inboxes.
  - msteffen 8y ago
    It may be time for a refresh, but our CEO has such a blog post from about a year ago: https://medium.com/pachyderm-data/provenance-the-missing-feature-for-good-data-science-now-in-pachyderm-1-1-2bd9d376a7eb https://medium.com/pachyderm-data/provenance-the-missing-fea...
    - TTPrograms 8y ago
      Nice - I went to the blog page on your site and this wasn't there. Good stuff.
laythea 8y ago
Where is the end game? The problem with this kind of AI revolution is that it relies on data about us. And this is responsible for the feverish attitude towards collecting or scraping data, sometimes from the public domain, but more than usually, from us. I for one, am having none of it.
- paganel 8y ago
  It will probably not end very soon. The author did mention some concerns about privacy, but only once, and then moved forward with his reasoning like nothing had happened. Also, it’s disheartening to see that his reaction to a piece of technology that could have probably killed his unborn kid (the medical device at the beginning which was fed bad data) was to say “we should use more technology!”, he was not questioning the underlying premises behind the whole operation at all: like, is it ok to “let” a machine help decide a technological untrained person (the doctor) if my unborn kid should support a life-threatening intervention or not?
aaronsnoswell 8y ago
Can someone with more karma modify the title to be less click-bait-ey?
Bye_Felicia 8y ago
...AND IT WON'T for a VERY LONG TIME. Those of us who know the origins of Ray Kurzweil, knew back then he was nothing special, and his ideas were derived from much smarter people around him. As I recall, the article in WIRED from like 20 years ago, talked about how he missed his dad, and how in the future you would be able to take a room full of all his dad's old crap, and AI would be able to recompile his dad into dad 2.0 in the cloud! (he didn't use these terms but that was the gist of the ridiculous and absurd WIRED article interview with him.) Why do I bring up Ray? It's because circus acts like Ray and the Singularity University, sold a bunch of people certain goods, which were VASTLY overestimated in terms of delivery times, and in terms of the good themselves. First of all, many folks don't want to admit this, but WE MAY NEVER BE ABLE TO CREATE A SYNTHETIC CONSCIOUSNESS! I think we will eventually, but it's definitely not a certainty. It just may not be possible for a completely synthetic 'consciousness' to exist. This type of hype has become almost religious in nature, just like the folks who really think Moore's Law is an actual scientific law and not just an observation and prediction based on very limited data. In conclusion, you'll get your AI just like those folks in the 50's, or was it 60's? ...well anyway, back when they had those world's fairs and predicted flying cars. We're just not there yet. We don't even have basic foundations to build this yet. There is always a possibility of a brilliant individual, who may leapfrog humanity, but for right now, it's just vaporware. AND YES. Even IBM's Watson and Google's GO winning "AI" are just vaporware machine learning and big data sets, it's not AI even a little bit. Sorry folks, I love futurizing, and inventing words ;) , just like everyone else, but... if AI is in the stadium, we aren't even in the parking lot. --- And now, after my rant, I shall read this article since it looks really interesting. I'm surprised it's on Medium.
- crististm 8y ago
  I've discovered recently the lectures of Prof. Jordan Peterson. You can infer a lot of links between human behavior and shortcomings of AI. In some lectures he even touches the actual problems although on a tangent (e.g. what is relevant in the infinite complexity of the world and on the infinite levels on which you can analyze the world). Long story short, my claim is that the AI revolution will happen when the AI agent will be able to abstract on a task experience and transfer that to a different task AND abstract away that and transfer that to the set of tasks and so on. Sort of like the Alpha Zero would next be able to fly helicopters or wash dishes or cook a meal or whatever. Not anytime soon.
deepaks4077 8y ago
Does anyone who's working/worked in the Healthcare "Intelligence Augmentation" have something to say about the challenges they've faced in setting up an "Intelligent Infrastructure"? Maybe someone who's worked with the DeepMind Streams application?
- dontreact 8y ago
  A lot of people don't think about how hard validation can be. You need a lot of high quality labeled data to confidently say that your algorithm works. I don't see a way around this even if learning algorithms become very data-efficient.
throwaway84742 8y ago
The main problem with “AI revolution” today is that 95% of things that practitioners tell you it can do are just nowhere close to sufficient accuracy under the range of conditions they’d need to work in in the real world. Easily more than a half of them don’t even work at all outside a demo with hand picked examples. And nobody seems to care. This narrows down the scope of applicability to a tiny sliver where you can tolerate high error rates, and even there it’s a hard slog to get anything done, and AI is relegated to the role of the “cherry on top”, rather than baked into the pie. There are a few areas where performance is good enough to be practically useful. One of those (facial recognition and tracking) is currently causing a “revolution” in China. I’m just not sure it’s the kind of revolution we want.
- 8bitsrule 8y ago
  It has to evolve, not revolve. Like cars did (and they're still -far- from perfect). Our remarkable bodies weren't designed by engineers, they survive now because, earlier, so many didn't. Are we smarter than evolution, because we like to think we are? Time will tell.
  - throwaway84742 8y ago
    Cars (assuming you mean level 5 autonomous ones) are another one of those things which we won’t really be getting for at least 20 more years. 90% of the problem is solved, the remaining 10% are exponentially harder, so no one has a foggiest clue how to solve them, let alone solve economically enough to make the cars viable on the market.
    - ergothus 8y ago
      I grew up hearing "we will eventually get computers that can play chess, but go is exponentially more complicated." People wee talking a century. I don't know that cars will happen soon(5-10 years), but I wouldn't want to bet one way or the other past that. We don't need perfection, we just need to equal humans, and humans are actually pretty bad, we are just used to it.
xvilka 8y ago
Most certainly we will see the comeback of "logical" AI too, including systems built on Prolog.
- skjerns 8y ago
  Prolog horror intensifies
stevehiehn 8y ago
An A.I revolution may not be happening but an 'Augmented Intelligence' revolution is
mgeorgoulo 8y ago
This sort of distraction arises whenever we try to adjust logic to words and not the other way around. It is said that this kind of distinction is only relevant to scientists. The article is very convincing though, that in the case of AI, the general public must be able to make those distinctions.
deleted 8y ago
[deleted]

270 points by wei_jok 8y ago

A related talk that Michael Jordan gave at a machine learning conference called Sys ML last month. https://youtu.be/4inIBmY8dQI https://youtu.be/4inIBmY8dQI

cbHXBY1D 8y ago
To anyone upset by MJ's Medium post, please watch the video. It's a much better representation of his thoughts on the current state of machine learning than the blog post.
johnx123-up 8y ago
Thanks for sharing. I'm also glad that I met this guy http://rajeshanbiah.blogspot.co.uk/2018/01/technology-prediction-for-2018.html http://rajeshanbiah.blogspot.co.uk/2018/01/technology-predic... who is having profound knowledge in predicting technologies and bubbles

eanzenberg 8y ago

I saw Prof. Jordan give this talk in person, and the 2nd paragraph resonated with me. I wish there was more critical thinking involved in science/research/higher ed/industry but unfortunately most there's a lot of cheap money floating around with "experts" slurping it up without care for outcome. "But the episode troubled me, particularly after a back-of-the-envelope calculation convinced me that many thousands of people had gotten that diagnosis that same day worldwide, that many of them had opted for amniocentesis, and that a number of babies had died needlessly."

tlarkworthy 8y ago
Like we have defensive programming: assert this field is not a stupidly large number. Perhaps we can encode our assumption as probabalisic asserts, and defensively encode that our assumptions are not violated. E.g. the current distribution looks like my training data.

visarga 8y ago

Well said: > Thus, just as humans built buildings and bridges before there was civil engineering, humans are proceeding with the building of societal-scale, inference and decision making systems that involve machines, humans and the environment. Just as early buildings and bridges sometimes fell to the ground — in unforeseen ways and with tragic consequences — many of our early societal scale inference and decision making systems are already exposing serious conceptual flaws.

return1 8y ago
that's a trivial statement, unless he can suggest a different way to do things. Should people have held off building any bridges, until the 20th century arrived ? Building things and science have always evolved side-by-side in a feedback loop.
- blacksmith_tb 8y ago
  I'm not sure it was intended to be read "Can't win? Don't try." An interesting corollary to that analogy is that some of the things humans built thousands of years ago are still standing... so it's possible some of our systems could also pass the test of time (they can be optimized more easily than a bridge).
  - return1 8y ago
    he does point elsewhere that machine learning solutions must account for "long tail" data , so it seems to me he 's looking for perfect solutions that will never exist.
- rdlecler1 8y ago
  Actually it’s not a trivial statement. He’s saying that we don’t have enough theory guiding us and instead we just spin up a tensorflow library without having any clue what’s going on underneath the hood. And I don’t mean understanding linear algebra in neural networks, I mean we don’t have a good theory of computation for Artificial neural networks like we do for Boolean electronic circuits. There is a little bit of work out there, but no one seems to be interested in the theory and why these work. The fact that we still represent networks as fully connected when many many of those weights w_ij are completely spurious tells me that we don’t spend enough time figuring out what’s going on and instead focus on the result. And this lack of attention will be why we’ll hit another wall. We should be reverse engineering intelligence and comparing that to AI so that we can build up the theoretical equivalent of aerodynamics.

deft 8y ago

I'm not an AI researcher (although from my internet reading that's not a hard title to claim ;)) but I feel that ML/DL can't go much farther than they already have. The concept of "we just need more power" is an obvious fallacy to me.

pretendscholar 8y ago
Why don't you think it will continue to progress?
- shoguning 8y ago
  I am of a similar opinion. There was a real revolution in ~2011-2013 with deep learning. These have achieved much better results in image/speech tasks. These gains have leveled off, and we're seeing some limitations. At current trajectory, we're not headed towards a general intelligence. Progress has been made, but there are big gaps. Smart home devices are a great case in point. They are somewhat flexible in the voice commands they accept. Specific phrasing and pronunciation are not necessarily required. Their responses and speech, however, are all pre-programmed and templated by humans. Edit: There is potential for more breakthroughs in the future, but I am not seeing them on the horizon at the moment.
  - placebo 8y ago
    Well, reinforcement learning should also be given a mention and revolutions there (e.g AlphaGo to AlphaZero) were much more recent
  - riyadparvez 8y ago
    Post-2013 breakthroughs off top of my head are: * Wavenet, now productionized at Google as text to speech * Alpha[Go]Zero * Neural Machine Translation, on production at Google
    - shoguning 8y ago
      AFAIK, these are all implementations of deep learning or similar, not a fundamentally new architecture. We'll continue to see these as DL matures, but it doesn't address the shortcomings of the technique. For more perspective: https://arxiv.org/abs/1801.00631 https://arxiv.org/abs/1801.00631

Talyen42 8y ago

The biggest challenge yet unconquered is getting your "average" business ($1-100m revenue, zero AI knowledge) using ML to help with literally anything they do. I'd wager less than 1% of businesses outside of SV even have a clue where to begin, or what to use it for, my employer included. "Do we hire some AI guys?" We'll need to crack the 1%-using-it mark for me to consider the revolution "begun"...

zapita 8y ago
Considering that the average business is unlikely to be writing any sort of software, other than perhaps basic Excel formulas... I wouldn't hold my breath waiting for them to use advanced software development techniques such as ML.
- lifeisstillgood 8y ago
  I would suggest that not writing any sort of software is a good proxy for going out of business soon. I also think you would be surprised at how many businesses both do, and really want and value, software - but don't have anyone convincing to do it for them
  - TeMPOraL 8y ago
    I increasingly feel that almost every business would benefit from having someone with programming experience on-board. This comes from observing that businesses tend to have a lot of ad-hoc processes and unique requirements, for which there is no software package to buy - not without throwing away huge parts of the processes and rebuilding them in a "standard" way. However, a lot of those unique areas could be improved with a help of someone who's capable of writing small programs and scripts to glue things together. A random example: my SO often works with high-res photos of their products, and sometimes this involves modifying them to suit the random requirements of other businesses. Something I currently solve for her by running ImageMagick one-liners if she needs more than a few photos modified. A person with basic familiarity of shell scripting and CLI tools could improve their workflow and keep improving it on-demand, as the requirements change.

deleted 8y ago

[deleted]

nicodjimenez 8y ago

Michael Jordan is just mad he missed the boat on deep learning. Must be tough being that brilliant and at the same time get left in the dust by algorithms from the 90's and just sheer brute force. The AI revolution is here, from Google search to Uber pool to auto correct to recommendation engines, it is just a slow process.

Ar-Curunir 8y ago
Lol Michael Jordan is at the forefront of ML, Stats, and yes, deep learning. He's not missed any boat.
- nicodjimenez 8y ago
  Michael Jordan is a mathematician far more than an engineer. I've never heard of any deep learning papers or open source software coming from his lab. Like a lot of mathematicians though working in stats and ML, he's been forced to adapt. There is lots of resentment amongst mathematicians about the current AI revolution, to me this reeks of that. I could be wrong!
- nicodjimenez 8y ago
  And also Michael Jordan is definitely _not_ at the forefront of deep learning or deep learning research (he definitely is in stats, no question). His lab is not even in the top 20 labs in the country for deep learning research. Also IMO nearly all the people at the forefront of deep learning are in industry right now.
AndrewKemendo 8y ago
I have to assume you're not familiar with his lab at all then: http://bair.berkeley.edu/blog/?refresh=1 http://bair.berkeley.edu/blog/?refresh=1 I mean one of their papers on the stuntmen was on the front page of HN recently. They are most certainly on the forefront.
- nicodjimenez 8y ago
  ??? that's not his lab, it's a blog site whose sole faculty advisor is Sergey Levine. I don't want to be a hater here, I'm just stating facts that M.J. is first and foremost a mathematician, and that deep learning has been tough for mathematicians in ML / stats.

John_KZ 8y ago

The AI Revolution is happening right now. There's enormous proven potential which is materializing in ever increasing rates. The first generations of hardware accelerators are slowly coming out and they're going to leave everyone astounded. It's a bit like the early days of the internet, it's not always the most practical solution, but it definitely works.

taurath 8y ago
Do you have any examples?
deft 8y ago
This exact tired old argument is being applied to: blockchain / DLT AI VR CRISPR in some senses Unless you have a reason to compare it to the "early days of the internet", don't. A technology being new and unknown doesn't make it like the internet.
crististm 8y ago
If it were there would be no one denying it. I don't see _that_ though so my conclusion is that, no, there is no revolution yet.

taurath 8y ago

I’ve been finding it difficult to find concrete examples of where AI is useful. Suggestion engines? Alg optimization? What would be something my parents would recognize that is being helped by AI?

zeofig 8y ago
The key is to not think about it too much. Your "logic" has no place here. Anyway, once the revolution hits your parents are gonna have those autonomous microwaves and self-cooling doctorbots they've been craving. The future is very, very, very bright.
mathgenius 8y ago
The Google search engine.
fvdessen 8y ago
- Self-driving cars - Camera that make better looking pictures - Better looking movies / videogames - Better medical diagnostics. - Face recognition - City surveillance; finding criminals, lost children.
Ar-Curunir 8y ago
Voice assistants like Alexa, Siri, etc.
choxi 8y ago
I like the category of "augmenting human skills". Google's Quick Draw is an example of augmented drawing, but you could use the same concept for writing, creating music, even programming. DeepFakes are basically the beginning of augmented video production. Imagine if you didn't need a green screen and body tracking suits to replace any person or scene in a movie with whatever you want. The whole field of generative deep learning is interesting and, to me, a really unexpected result of AI research.

prolikewhoa 8y ago

What are we defining as AI now? It seems like AI has had a lot of hype in the past few years, but I really don't think we're even close unless it's created by mistake. We don't understand the brain fully, we don't understand consciousness, we just know so little in the grand scheme of things. Do we have the computing power to come anywhere close to what we need, will we have that computing power any time soon without a major breakthrough?

Ar-Curunir 8y ago
Did you read the article? Some of your questions would have been answered

msteffen 8y ago

> The problem had to do not just with data analysis per se, but with what database researchers call “provenance” — broadly, where did data arise, what inferences were drawn from the data, and how relevant are those inferences to the present situation? Plug: I work at a company (https://www.pachyderm.com https://www.pachyderm.com) whose product is designed precisely to track data provenance across pipelines and through a company's larger data-processing operation for this reason

TTPrograms 8y ago
You all should really play that up more in your messaging - "provenance" is one of the hardest and least-addressed components of building AI/ML/data science systems that actually have measurable impact (rather than analysts making plots and speculating). In general having a structured, centralized representation of business processes is super valuable I'm sure. If you write a blog post describing how critical that is to practical data science efficacy with some examples I bet you'll end up in a bunch of VP inboxes.
- msteffen 8y ago
  It may be time for a refresh, but our CEO has such a blog post from about a year ago: https://medium.com/pachyderm-data/provenance-the-missing-feature-for-good-data-science-now-in-pachyderm-1-1-2bd9d376a7eb https://medium.com/pachyderm-data/provenance-the-missing-fea...
  - TTPrograms 8y ago
    Nice - I went to the blog page on your site and this wasn't there. Good stuff.

laythea 8y ago

Where is the end game? The problem with this kind of AI revolution is that it relies on data about us. And this is responsible for the feverish attitude towards collecting or scraping data, sometimes from the public domain, but more than usually, from us. I for one, am having none of it.

paganel 8y ago
It will probably not end very soon. The author did mention some concerns about privacy, but only once, and then moved forward with his reasoning like nothing had happened. Also, it’s disheartening to see that his reaction to a piece of technology that could have probably killed his unborn kid (the medical device at the beginning which was fed bad data) was to say “we should use more technology!”, he was not questioning the underlying premises behind the whole operation at all: like, is it ok to “let” a machine help decide a technological untrained person (the doctor) if my unborn kid should support a life-threatening intervention or not?

aaronsnoswell 8y ago

Can someone with more karma modify the title to be less click-bait-ey?

Bye_Felicia 8y ago

...AND IT WON'T for a VERY LONG TIME. Those of us who know the origins of Ray Kurzweil, knew back then he was nothing special, and his ideas were derived from much smarter people around him. As I recall, the article in WIRED from like 20 years ago, talked about how he missed his dad, and how in the future you would be able to take a room full of all his dad's old crap, and AI would be able to recompile his dad into dad 2.0 in the cloud! (he didn't use these terms but that was the gist of the ridiculous and absurd WIRED article interview with him.) Why do I bring up Ray? It's because circus acts like Ray and the Singularity University, sold a bunch of people certain goods, which were VASTLY overestimated in terms of delivery times, and in terms of the good themselves. First of all, many folks don't want to admit this, but WE MAY NEVER BE ABLE TO CREATE A SYNTHETIC CONSCIOUSNESS! I think we will eventually, but it's definitely not a certainty. It just may not be possible for a completely synthetic 'consciousness' to exist. This type of hype has become almost religious in nature, just like the folks who really think Moore's Law is an actual scientific law and not just an observation and prediction based on very limited data. In conclusion, you'll get your AI just like those folks in the 50's, or was it 60's? ...well anyway, back when they had those world's fairs and predicted flying cars. We're just not there yet. We don't even have basic foundations to build this yet. There is always a possibility of a brilliant individual, who may leapfrog humanity, but for right now, it's just vaporware. AND YES. Even IBM's Watson and Google's GO winning "AI" are just vaporware machine learning and big data sets, it's not AI even a little bit. Sorry folks, I love futurizing, and inventing words ;) , just like everyone else, but... if AI is in the stadium, we aren't even in the parking lot. --- And now, after my rant, I shall read this article since it looks really interesting. I'm surprised it's on Medium.

crististm 8y ago
I've discovered recently the lectures of Prof. Jordan Peterson. You can infer a lot of links between human behavior and shortcomings of AI. In some lectures he even touches the actual problems although on a tangent (e.g. what is relevant in the infinite complexity of the world and on the infinite levels on which you can analyze the world). Long story short, my claim is that the AI revolution will happen when the AI agent will be able to abstract on a task experience and transfer that to a different task AND abstract away that and transfer that to the set of tasks and so on. Sort of like the Alpha Zero would next be able to fly helicopters or wash dishes or cook a meal or whatever. Not anytime soon.

deepaks4077 8y ago

Does anyone who's working/worked in the Healthcare "Intelligence Augmentation" have something to say about the challenges they've faced in setting up an "Intelligent Infrastructure"? Maybe someone who's worked with the DeepMind Streams application?

dontreact 8y ago
A lot of people don't think about how hard validation can be. You need a lot of high quality labeled data to confidently say that your algorithm works. I don't see a way around this even if learning algorithms become very data-efficient.

throwaway84742 8y ago

The main problem with “AI revolution” today is that 95% of things that practitioners tell you it can do are just nowhere close to sufficient accuracy under the range of conditions they’d need to work in in the real world. Easily more than a half of them don’t even work at all outside a demo with hand picked examples. And nobody seems to care. This narrows down the scope of applicability to a tiny sliver where you can tolerate high error rates, and even there it’s a hard slog to get anything done, and AI is relegated to the role of the “cherry on top”, rather than baked into the pie. There are a few areas where performance is good enough to be practically useful. One of those (facial recognition and tracking) is currently causing a “revolution” in China. I’m just not sure it’s the kind of revolution we want.

8bitsrule 8y ago
It has to evolve, not revolve. Like cars did (and they're still -far- from perfect). Our remarkable bodies weren't designed by engineers, they survive now because, earlier, so many didn't. Are we smarter than evolution, because we like to think we are? Time will tell.
- throwaway84742 8y ago
  Cars (assuming you mean level 5 autonomous ones) are another one of those things which we won’t really be getting for at least 20 more years. 90% of the problem is solved, the remaining 10% are exponentially harder, so no one has a foggiest clue how to solve them, let alone solve economically enough to make the cars viable on the market.
  - ergothus 8y ago
    I grew up hearing "we will eventually get computers that can play chess, but go is exponentially more complicated." People wee talking a century. I don't know that cars will happen soon(5-10 years), but I wouldn't want to bet one way or the other past that. We don't need perfection, we just need to equal humans, and humans are actually pretty bad, we are just used to it.

xvilka 8y ago

Most certainly we will see the comeback of "logical" AI too, including systems built on Prolog.

skjerns 8y ago
Prolog horror intensifies

stevehiehn 8y ago

An A.I revolution may not be happening but an 'Augmented Intelligence' revolution is

mgeorgoulo 8y ago

This sort of distraction arises whenever we try to adjust logic to words and not the other way around. It is said that this kind of distinction is only relevant to scientists. The article is very convincing though, that in the case of AI, the general public must be able to make those distinctions.

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