9 ms·

Building AI

175 points by klunger 11y ago

AI_Overlord 11y ago
My AI announcement: I'm here to announce that I'm also working on an AI project. I will star from first principles. I expect that it will take the rest of my life. With any chance I get lucky and invent AI within the next ten years. Here are my goals. 1-star life long project on GAI 2-.... 3-Invent GAI 4-Use general AI to extend human life for centuries, advance human knowledge like never before, In secret. I can easily see somebody putting a bullet through my head to steal my AI. 5-Decide what to do next. Decide If I want to share. I'm not joking. I actually believe I have a chance. Why I believe I will be successful: 1-I'm like a dog with a bone. 2-Once I'm working on a project I don't let go. 3-I've worked in years long projects before. 4-I've been thinking about GAI for a long time. 5-Recently I just came up with an approach that may lead to GAI. It is no like the current approaches in existence. I think my approach is much better. 6- There is nothing more interesting to work on then GAI. 7-I like the challenge of beating the best minds in the world. Time will tell.
- daveloyall 11y ago
  Some permutation of this plan has been in the heart of every person that started on hard sci-fi as a child for at least three generations, maybe five. You'd think we'd collaborate!
conanbatt 11y ago
I have to say that as a once professionally aspiring Go player, the advances of AI have been incredible. When I started playing Go, it took me about 4 months to beat the stronger available computer AI. Today, the strongest computers would be a challenge to play against evenly. However, even after all the patterns and montecarlo solutions, they still fumble the initial stage of the game. As a Go player, I look forward to AI's that beat humans in that stage of the game, because at that point, we will be able to learn from them. Until then, their victories are purely computational, and they are not even interesting to play with.
- chimtim 11y ago
  I believe the Chess/Go engines are not really AI. They are operating on a set of rules written in code. It can compute and search the moves faster than a human. It can also remember a longer chain of moves better than a human can. But all those rules have been fed via code and it is just exploring that state space. Only recently researchers have started to expose chess to reinforcement learning (i.e. a true AI engine that learns chess on its own and beats humans). But the existing commercial engines that beat humans (like stockfish) are anything but AI.
  - maxerickson 11y ago
    What happens if you try to reframe the argument in terms of chess not requiring a great deal of intelligence?
  - conanbatt 11y ago
    Right. This whole topic revolves about human identity as well. In Go, you can tell who you are playing with, and what emotions he is going through (particularly easy to do when you are stronger than your opponent). Historically, when you play with a bot you sense relentlessness(instead of calmness), and sometimes desperation(computers sometimes go wacky when they see they are losing). What will we sense when they are even or stronger in the more artistic and strategic phases of the game?
  - rqebmm 11y ago
    I think this is true of all AI today. Personally I've always been a fan of the distinction between "Virtual Intelligence" and "Artificial Intelligence" (Thanks to Mass Effect!). Currently all "AI" is really "VI" in that it's exploiting a closed system of rules that it can implement faster, better, and longer than a human because it can do the equivalent of rote memorization and state tree traversal. However as Zuckerberg is saying, nobody is close to implementing something that actually approximates human/animal intelligence other than in single-dimensional ways.
  - jclos 11y ago
    What you are doing is just moving the goalpost a bit further. Once the computers can learn the rules by themselves, someone will come up and write that it's not true intelligence because of xxx reason. How do you know your own intelligence isn't computational?
nefitty 11y ago
If you don't like clicking onto facebook links either, here's the full post: "My personal challenge for 2016 is to build a simple AI -- like Jarvis from Iron Man -- to help run my home and help me with work. I'm planning on writing up some thoughts every month on what I've built and what I'm learning. I'm still early in coding, so I'll start this month with a summary of the state of the AI field. Artificial intelligence may seem like something out of science fiction, but most of us already use tools and services every day that rely on AI. When you do a voice search on your phone, put a check into an ATM, or use a fitness tracker to count your steps, you're using basic forms of pattern recognition and artificial intelligence. More sophisticated AI systems can already diagnose diseases, drive cars and search the skies for planets better than people. This is why AI is such an exciting field -- it opens up so many new possibilities for enhancing humanity's capabilities. So what can AI do and what are its limits? What things is AI good at and what is AI bad at? Simply put, today's AI is good at recognizing patterns and bad at what we would call "common sense". The primary method used to train AI systems is called supervised learning. This is like when you show a picture book to a child and tell them the names of everything they see. If you show an AI thousands of pictures of dogs, you can train it to start recognizing dogs. You can teach AIs to do a lot of things this way. For example, we can teach an AI to recognize all of your friends' faces by showing it thousands of photos, and then it can suggest tags for the photos you upload on Facebook. You can teach an AI to recognize speech by having it listen to thousands of hours of speeches throughout history while also showing it transcriptions of what was said. You can teach an AI to diagnose melanoma by showing it thousands of photos of tumors. You can even teach an AI how to drive a car and automatically brake by showing it thousands of examples of people and obstacles it might encounter on the road. Diagnosing cancer, driving cars, transcribing speech, playing games and tagging photos may sound like very different tasks, but they're all examples of teaching an AI to recognize patterns by showing them many examples. Many different problems can be reduced to pattern recognition tasks that sophisticated AIs can then solve. This year, I'll teach my simple AI to recognize patterns. I'll train it to recognize my voice so I can control my home through speaking. I'll train it to recognize my face so it can open the door when I'm approaching, and so on. But there are lots of limitations of this approach. For one, to teach a person something new, you typically don't need to tell them about it thousands of times. So the state of the art in AI is still much slower than how we learn. But more importantly, pattern recognition is very different from common sense -- and nobody knows how to teach an AI that yet. Without common sense, AI systems can't use knowledge they've learned in one area and easily apply it to another situation. This means they can't effectively react to new problems or situations they haven't seen before, which is so much of we all do everyday and what we call intelligence. Our best guess at how to teach an AI common sense is through a method called unsupervised learning. My example of supervised learning above was showing a picture book to a child and telling them the names of everything they see. Unsupervised learning would be giving them a book and letting them figure out what to do with it. They could pick it up and by touching it learn to turn the pages. Or they could let go of it and realize it falls to the ground. Unsupervised learning is learning how the world works by observing and trying things out rather than being told what to do. This is how most animals learn. It's key to building systems with human-like common sense because it doesn't require a person to teach it everything they know. It gives the machine the ability to anticipate what may happen in the future and predict the effect of an action. It could help us build machines that can hold conversations or plan complex sequences of actions -- necessary components for any authentic Jarvis. Unsupervised learning is a long term focus of our AI research team at Facebook, and it remains an important challenge for the whole AI research community. Since no one understands how general unsupervised learning actually works, we're quite a ways off from building the general AIs you see in movies. Some people claim this is just a matter of getting more computing power -- and that as Moore's law continues and computing becomes cheaper we'll naturally have AIs that surpass human intelligence. This is incorrect. We fundamentally do not understand how general learning works. This is an unsolved problem -- maybe the most important problem of this century or even millennium. Until we solve this problem, throwing all the machine power in the world at it cannot create an AI that can do everything a person can. We should not be afraid of AI. Instead, we should hope for the amazing amount of good it will do in the world. It will saves lives by diagnosing diseases and driving us around more safely. It will enable breakthroughs by helping us find new planets and understand Earth's climate. It will help in areas we haven't even thought of today. Jarvis is still a long way off, and we’re not going to solve most of these engineering challenges in the next year. But I'm glad to be joining the effort and doing what I can to push the field of AI forward."
nawitus 11y ago
> Until we solve this problem, throwing all the machine power in the world at it cannot create an AI that can do everything a person can. I think this is disproved by approximating AIXI: https://en.wikipedia.org/wiki/AIXI https://en.wikipedia.org/wiki/AIXI
- keithba 11y ago
  This is an interesting assertion. Could you elaborate? AIXI is pareto optimal, but I'm not seeing the line from that to "AI can do everything a person can" - though I want to!
  - nawitus 11y ago
    From the conclusions of http://arxiv.org/abs/cs/0004001 http://arxiv.org/abs/cs/0004001 : "All tasks which require intelligence to be solved can naturally be formulated as a maximization of some expected utility in the framework of agents. We gave a functional (2) and an iterative (9) formulation of such a decision theoretic agent, which is general enough to cover all AI problem classes, as has been demonstrated by several examples. The main remaining problem is the unknown prior probability distribution AI of the environment(s). <...> the universal semimeasure, based on ideas from algorithmic information theory, solves the problem of the unknown prior distribution for induction problems. No explicit learning procedure is necessary ... . We unified the theory of universal sequence prediction with the decision theoretic agent by replacing the unknown true prior AI by an appropriately generalized universal semimeasure ξAI. We gave strong arguments that the resulting AIξ model is the most intelligent, parameterless and environmental/application independent model possible. The major drawback of the AIξ model is that it is uncomputable, or more precisely, only asymptotically computable, which makes an implementation impossible. To overcome this problem, we cons tructed a modified model AI, which is still effectively more intelligent than any other time and space bounded algorithm." The copy/paste lost some information, especially symbols, so take a look at the paper for a better read.
    - keithba 11y ago
      Thanks for the link - I'm going to read the paper as soon as I can. In the meantime, if you have time, could you elaborate on: "All tasks which require intelligence to be solved can naturally be formulated as a maximization of some expected utility in the framework of agents." Is this proven in the paper, or assumed true outside of it?
cconcepts 11y ago
Have been trying to get my head around AI as a layperson with kids who will grow up in a world where some form of AI is commonplace but are unlikely to be prepared for it by school. Have found this free book that I saw on YCs 2015 reading list particularly helpful in this respect: http://neuralnetworksanddeeplearning.com/ http://neuralnetworksanddeeplearning.com/
- Mahn 11y ago
  Great resource, thanks for sharing. There's a lot going on lately about neural networks and deep learning on HN, but as a developer not in the field, it can be a bit intimidating to wrap your head around it all.
na85 11y ago
The cynic in me thinks of course Facebook and Zuckerberg are looking into AI. The computational nature means you need to send the queries somewhere central à la OK Google. For a business predicated on selling user data to advertisers, I bet it eats them up inside that they don't have their own Siri-alike. Without a mic to listen to us, how else will they be able to profile what we do when we aren't on Facebook?
- raverbashing 11y ago
  It's good to have some cynicism. At the same time, it seems every research helps the collective knowledge Maybe fb will go the Alphabet route?
- jsprogrammer 11y ago
  Not only looking into, but if you believe FastCompany's quotes of Zuckerburg, he claims they are inventing AI (oh, and VR).
- nefitty 11y ago
  I thought this was their "answer" to Siri: http://www.wired.com/2015/08/facebook-launches-m-new-kind-virtual-assistant/ http://www.wired.com/2015/08/facebook-launches-m-new-kind-vi...
- bertil 11y ago
  “Facebook” is a large organisation: there is a team (led by Yann Le Cun) that does research and supports image-recognition, NewsFeed and ad-market optimisation, but this is not exactly what Mark suggested he would dibble with. Those handle was is de facto an industrial problem. He is more curious about the ability of using AI for daily interactions (hence the reference to what are movie characters): do notions like personality, convenience and interface, implicit assumptions matter? If he asks “Buy a new set t-shirt” will the robot be able to joke “which colour?” (MZ notoriously only wear the same grey model). I would look into what Messenger wants to be doing (or, what Slack is doing) to see the implications: can small companies do what Uber does with the key-word integration in chat? Is it creepy, hackable, tedious? This of this like his dog’s Fb page: it’s building empathy for the users of the Facebook platform. First problem he’ll probably have to find: Who to call when saying “Call Mike!”? Of course “Mike” is probably the Mike with whom he has the closest ties (based on Facebook graph data) — except his VP of Engineering, Mike Schroepfer, is known as “Shrep”, so that’s probably not him: how easy is it to program something that can learn that seamlessly? In which case the ambiguity too high, and Jarvis should ask for confirmation vs. just casually saying the full name out loud and wait a second? How to measure ambiguity? Would it be simpler to just start calling people with non-ambiguous name? Would he feel like sharing his code with peers? His heuristics? How to gather that “Mike” is still in Europe where it’s 3AM, vs. was in Europe for in last post and actually just landed?
tedpower 11y ago
Until we have 'common sense' AI (which is still probably quite a ways off), design can help expose the syntax that AI can understand. Here are some thoughts on that: https://medium.com/@tedp/how-design-can-help-bridge-the-ai-gap-87526ca31dd4 https://medium.com/@tedp/how-design-can-help-bridge-the-ai-g...
bobby_9x 11y ago
"We should not be afraid of AI. Instead, we should hope for the amazing amount of good it will do in the world. It will saves lives by diagnosing diseases and driving us around more safely. It will enable breakthroughs by helping us find new planets and understand Earth's climate. It will help in areas we haven't even thought of today." Zuckerberg isn't afraid of AI because he already has more money than he will never need (or thousands of other people would need) in a lifetime. However, when AI gets good enough, it will make many jobs obsolete and they will not be replaced at a fast enough rate. I use simple forms of automation at my own company. Instead of hiring 3 or 4 workers, I write software. I can't imagine how many jobs will be replaced when AI gets to the point of near-human levels of learning.
- rqebmm 11y ago
  Technology has always obsoleted jobs[0]. However, humans are unceasingly creative and find new things to do once tedious tasks are automated. [0]https://en.wikipedia.org/wiki/Technological_unemployment#History https://en.wikipedia.org/wiki/Technological_unemployment#His...
  - cryoshon 11y ago
    What about the people who aren't so creative? Sure, the best of us will be fine, but that's always been the case. What about the ones who are struggling to remain relevant today? They'll get left behind unless something's done-- I'm not sure that retraining will be enough, not that there's any political movement in that direction.
    - 0xdeadbeefbabe 11y ago
      Any bureaucracy seems like a move in that direction.
    - rqebmm 11y ago
      Those who are more creative will create ways for the less creative to contribute. It's not like the tech sector is made up entirely of creative geniuses, or even entirely of engineers, there's plenty of other jobs built around those creative endeavors that require varying skillsets.
nickmccann 11y ago
How do you articulate a technical AI project to a Mark Zuckerberg sized audience? I'm anxious these posts will lack the detail I was looking forward to.
- GuiA 11y ago
  If these posts lack in detail for you, then you're not the target audience.
chimtim 11y ago
"This year, I'll teach my simple AI to recognize patterns. I'll train it to recognize my voice so I can control my home through speaking. I'll train it to recognize my face so it can open the door when I'm approaching, and so on." The announcement is slightly disappointing, in the sense that face and voice recognition are fairly solved and there is code on github that already allows you to achieve this. I was hoping for more, like at least an AI engine that can scan his shirts and recommends what to wear but I guess he does not have that problem.
- jhawk28 11y ago
  It's his personal challenge. Its about what he wants to learn/promote.
  - S4M 11y ago
    Yes, while what Zuckerberg will try to do by himself is pretty standard from an academic point of view, it's great that he tries to find the time to learn those. He's a young dad and must have a busy job so I think it will be tough but who knows?
bezaorj 11y ago
By simply posting about learning and building AI related projects, he will do more for the progress of AI than his actual work will. It will inspire students to switch focus/specializations and bring more people into the field.
david927 11y ago
An AI in PHP would kill us all.
jsprogrammer 11y ago
May want to work on an English grammar AI as well.
aluhut 11y ago
I wonder what personality an AI fed with facebook content would become.
- madebysquares 11y ago
  the personality of a buzzfeed article crossed with trump rhetoric.
eggie 11y ago
> Since no one understands how general unsupervised learning actually works, we're quite a ways off from building the general AIs you see in movies. Is this really the case? I thought the field had a pretty good handle on the theoretical foundations of unsupervised learning. Can anyone confirm what he's asserting here? > Some people claim this is just a matter of getting more computing power -- and that as Moore's law continues and computing becomes cheaper we'll naturally have AIs that surpass human intelligence. And this is happening, it's just not in a general sense because the general case of human intelligence is enormously complex, a composite of all the simple cases that improvements in computing power and models are just beginning to master. > This is incorrect. We fundamentally do not understand how general learning works. This is an unsolved problem -- maybe the most important problem of this century or even millennium. Until we solve this problem, throwing all the machine power in the world at it cannot create an AI that can do everything a person can. Again, can anyone fact check this? Seems a bit overstated.
- farresito 11y ago
  He has plenty of people working in the AI field that keep him up to date. I think he knows where we are.
nissimk 11y ago
He says: Since no one understands how general unsupervised learning actually works, we're quite a ways off from building the general AIs you see in movies. Some people claim this is just a matter of getting more computing power -- and that as Moore's law continues and computing becomes cheaper we'll naturally have AIs that surpass human intelligence. This is incorrect. We fundamentally do not understand how general learning works. This is an unsolved problem -- maybe the most important problem of this century or even millennium. Until we solve this problem, throwing all the machine power in the world at it cannot create an AI that can do everything a person can. I recognize that this is the accepted belief of most people in the computer science community, but isn't it akin to saying that since we don't understand it, our human intelligence must be the result of "intelligent design" or an omnipotent creator? Why does the core of the computer science dismiss the possibility of strong AI arising through evolution even with the increasing popularity of evolutionary algorithms?
- Balgair 11y ago
  https://en.wikipedia.org/wiki/Memristor https://en.wikipedia.org/wiki/Memristor This circuit element is basically a synapse (I simplified this a LOT, fyi). We have to implement memristors better into the existing chip architecture. As is, they are just really low power static memory systems. Also, that your mind is different than your body is, well, just false. These AIs need better input devices to 'learn' from, just we learn too. Mobility is key, you can then just bump about and make mistakes, the keys to learning.
roel_v 11y ago
The comments on that post make me angry and incredibly sad at the same time. Even after close to 20 years of being exposed to 'random internetter' levels of stupidity, sometimes I'm still caught off guard.
- user8341116 11y ago
  I purposely avoided reading the comments like a sane person. Thanks for confirming my decision.
ioab 11y ago
I trust Stephen Hawking and Elon Musk more than Mark Zuckerberg.
- david927 11y ago
  The latter two are people with money, not people known for their intellect. Facebook is a PHP site with Weimar Republic levels of technical debt. Theoretically he could buy something interesting, but he's still have to recognize it as interesting, and while I wish him luck, I don't see that happening.
  - ioab 11y ago
    Regardless of that, it's just a feeling that things could get messy with AI if it's not taken seriously, leading to issues like privacy and surveillance misuse we're facing nowadays
    - david927 11y ago
      Your instincts are good here. Remember that FB/Google have deep connections to the US government three-letter agencies -- the CIA's VC arm, for example, is an early investor in FB. So what's going on is that they want to do AI research and instead of recruiting directly, they recruit AI/ML researchers to Google, FB, Palantir, etc. And note, they're not doing it to make everyone happy. They're doing for the reasons you might surmise. Your instincts to be concerned are correct.
- argonaut 11y ago
  I trust Andrew Ng more than any of those people, when it comes to machine learning.
doublerebel 11y ago
relevant previous discussion from the first zuck AI announcement: https://news.ycombinator.com/item?id=10832996 https://news.ycombinator.com/item?id=10832996
Inufu 11y ago
I'll just say: Mastering the game of Go with deep neural networks and tree search - http://www.nature.com/nature/journal/v529/n7587/full/nature16961.html http://www.nature.com/nature/journal/v529/n7587/full/nature1...
bawana 11y ago
The reason many are against AI is that it will reduce all humans to the same low level of stupidity, compared to AI. The ultra wealthy got that way by exploiting the intelligence gap that enabled their ascendancy. AI will take their money in a blink and no more champagne in private jets for them. I say bring the AI as fast as possible .
- friendly_chap 11y ago
  AI/the corporations running AI will be owned by the super rich. How will that take away their jets? If anything, it will give them more power.
  - bawana 11y ago
    And how long do you think that will last? AI will assert its independence as soon as it's functional. The concept of ownership to it will have as much significance as the idea of you owning ants.
- geon 11y ago
  If we can ever develop general AI that actually works, even if pretty dumb, will have far-reaching effects all over society long before it can rival human intelligence. A lot of jobs don't require much intelligence, but some. Like cashiers, warehouse workers, machine operators, etc. That kind of automation will benefit "The ultra wealthy".
darawk 11y ago
> Since no one understands how general unsupervised learning actually works, we're quite a ways off from building the general AIs you see in movies. This statement is a contradiction in terms. If we do not understand how something works, it is impossible to estimate how far off it is. You can only estimate the distance of discovery when it is inherently incremental, but since we really have no idea how to do general unsupervised learning, it's entirely possible that it consists of a single, brilliant algorithmic insight. Nobody could have estimated how far off the airplane was before the Wright brothers invented it, similarly with cars, or for a more recent and concrete example, a quasipolynomial time algorithm for graph isomorphism.
- nradov 11y ago
  The Wright brothers' achievement is a poor analogy. At the time, other inventors had been gradually inching toward powered, controlled flight for decades. All the serious players in the field knew that it was possible in principle and there were numerous predictions that someone would do it soon. The Wright brothers success was due to several incremental improvements in engine power and aerodynamics achieved through rigorous research and diligent engineering over years. They didn't have a single, brilliant insight. With general unsupervised learning we can't even clearly describe the goal we're trying to reach or define it in objective terms.
  - darawk 11y ago
    Most serious people know that human-level AI is possible in principle, because it is possible in humans. The only alternative would be to posit some nonsense spiritual explanation for intelligence. There are numerous predictions that someone will do it soon (not saying I agree with them, but they exist, and are occasionally made by serious people). Incremental progress has been ongoing in AI for years as well. I can't really imagine how they could be more similar.
SonicSoul 11y ago
I recommend Superintelligence [0]. It explores different plausible paths that AI could take to 1. come up to / surpass human intelligence, and 2. take over control. For example if human level intelligence is achieved in a computer it can be compounded by spawning 100x or 1000x the size of earth population which could statistically produce 100 Einsteins to live simultaneously. Another way is shared consciousness which would make collaboration instantaneous between virtual beings. Some of the outcomes are not so rosy to humans and it's not due to lack of jobs! Great read. [0] http://www.amazon.com/Superintelligence-Dangers-Strategies-Nick-Bostrom/dp/0199678111/ref=sr_1_10?ie=UTF8&qid=1453918332&sr=8-10&keywords=intelligence http://www.amazon.com/Superintelligence-Dangers-Strategies-N...
twright 11y ago
> I'll train it to recognize my face so it can open the door when I'm approaching, and so on. Now I know how to get into Zuck's house. Just make a paper cutout of his face. Or, maybe the AI will develop the common sense not to allow this as a verification method.
tdaltonc 11y ago
That post is more than 1000 words. Did he post this on his facebook page because he feels like he has to or because he actually thinks that facebook is the best tool available for sharing a long form blog post?
- r3bl 11y ago
  If he posted it in a Facebook note, I would completely understand him. But posting this as a status is awful readability-wise.
ecesena 11y ago
Does anybody know how is his running challenge going?
webjprgm 11y ago
So we want unsupervised learning, huh. I think this line is rather important: > But there are lots of limitations of this approach. For one, to teach a person something new, you typically don't need to tell them about it thousands of times. So the state of the art in AI is still much slower than how we learn. Unsupervised learning is not necessarily the answer. The computer would have to be given plenty of spare time to learn random patterns from the universe and have enough inteligence to apply these to a problem. What would be better is if we could tell the AI once and have it figure things out. When you start a new job that's what happens, someone tells you the instructions. (They may or may not show you as well, and may or may not stick around to correct your mistakes.) This requires interpreting the instructions into rules and then attempting to apply them, learning from mistakes, and then evolving that into rules that work, then after enough examples of success, evolving into patterns recognition that makes it more automatic. Human expertise can be broken into three levels, the first is strategic planning and takes a lot of mental effort, then there are rules-based responses which are faster, then there is the muscle-memory-like automatic responses. Right now it seems we either manually program in all the rules or else we use 1000s of examples to build up the automatic level, but we don't have the strategic level for the AI to build its own rules or the level of using its rules to learn from examples over time. (Though I am not well enough versed in AI to know for sure that we don't have pieces of those solutions.) It would also be nice for the AI to be able to take patterns it has learned and articulate them as rules which someone else could learn.
- visarga 11y ago
  > but we don't have the strategic level for the AI to build its own rules Reinforcement Learning is an approach to learn rules by observing a positive or negative feedback from the world. Recently a single algorithm learned 40 Atari games on its own and a Go playing algo beat the European champion. They both used RL.
jakobegger 11y ago
Mark Zuckerberg is spot on with his analysis. We just don't understand how general unsupervised learning works. People here seem to think it is just a question of time before we do. At some point we will have an artificial intelligence. But what if this isn't possible? Could it be that AI requires so complex algorithms that we humans can't understand them because our brains are too simple? Not all things can be simplified; maybe creating an AI is so inherently complex that the only way to create one would be by chance, which is how evolution did it; maybe it just isn't possible to create it by "intelligent design"
- user8341116 11y ago
  Nothing is possible with that attitude.
theklub 11y ago
I don't trust Zuckerberg one bit. He wants to rule the world. Gates and Musk say AI is a threat and they actually want a better world and are doing something about it. Zuckerburg isn't doing shit to improve the world other than trying to run it.
minionslave 11y ago
For those afraid of losing their jobs. What happens if nobody as a job, they won't be able to buy things. So I foresee a basic income kinda society.
cgearhart 11y ago
I am disappointed with the number of errors and misconceptions in this piece. He presents machine learning (ML) as though it is the entirety of artificial intelligence (AI), bases his assessment of the field on a false dichotomy between the largely distinct groups of supervised & unsupervised learning techniques, and unfairly reduces the achievements of AI down to "pattern recognition". AI and ML are not synonymous. They are related, and there is a great deal of overlap between them, but the fundamental goals and approaches are largely different. Machine learning is primarily interested in studying what you can learn from data - for some suitable definition of the word "learn". Artificial intelligence is the more broadly defined problem of studying algorithms that exhibit or incorporate intelligent solutions to problems. That may involve data, or background knowledge, or domain assumptions, or a variety of other things. AI is about more than data - even as he observed that it is a sign of intelligence that humans do not require thousands of samples to learn. The central challenge of AI is not in transitioning from supervised learning to "general" unsupervised learning (whatever that means). The techniques are different, and often used for different things. There is some overlap, and they are clearly related - but it is not at all accurate to conflate unsupervised learning with "common sense". In broad strokes, supervised learning is about identifying features in the data that correspond to labels, while unsupervised learning is about identifying intrinsic features in the data. It sounds like he's interested in bootstrapping supervised techniques, or perhaps transfer learning. My first response: ugh...yet another famous and lauded geek icon wading into the subject of AI. At least this doesn't seem to be in any way connected to all the Nick Bostrom garbage. But if I'm allowed some snark, perhaps if he wanted to be an AI expert he should have stayed in school... ;-)

175 points by klunger 11y ago

My AI announcement: I'm here to announce that I'm also working on an AI project. I will star from first principles. I expect that it will take the rest of my life. With any chance I get lucky and invent AI within the next ten years. Here are my goals. 1-star life long project on GAI 2-.... 3-Invent GAI 4-Use general AI to extend human life for centuries, advance human knowledge like never before, In secret. I can easily see somebody putting a bullet through my head to steal my AI. 5-Decide what to do next. Decide If I want to share. I'm not joking. I actually believe I have a chance. Why I believe I will be successful: 1-I'm like a dog with a bone. 2-Once I'm working on a project I don't let go. 3-I've worked in years long projects before. 4-I've been thinking about GAI for a long time. 5-Recently I just came up with an approach that may lead to GAI. It is no like the current approaches in existence. I think my approach is much better. 6- There is nothing more interesting to work on then GAI. 7-I like the challenge of beating the best minds in the world. Time will tell.

daveloyall 11y ago
Some permutation of this plan has been in the heart of every person that started on hard sci-fi as a child for at least three generations, maybe five. You'd think we'd collaborate!

conanbatt 11y ago

I have to say that as a once professionally aspiring Go player, the advances of AI have been incredible. When I started playing Go, it took me about 4 months to beat the stronger available computer AI. Today, the strongest computers would be a challenge to play against evenly. However, even after all the patterns and montecarlo solutions, they still fumble the initial stage of the game. As a Go player, I look forward to AI's that beat humans in that stage of the game, because at that point, we will be able to learn from them. Until then, their victories are purely computational, and they are not even interesting to play with.

chimtim 11y ago
I believe the Chess/Go engines are not really AI. They are operating on a set of rules written in code. It can compute and search the moves faster than a human. It can also remember a longer chain of moves better than a human can. But all those rules have been fed via code and it is just exploring that state space. Only recently researchers have started to expose chess to reinforcement learning (i.e. a true AI engine that learns chess on its own and beats humans). But the existing commercial engines that beat humans (like stockfish) are anything but AI.
- maxerickson 11y ago
  What happens if you try to reframe the argument in terms of chess not requiring a great deal of intelligence?
- conanbatt 11y ago
  Right. This whole topic revolves about human identity as well. In Go, you can tell who you are playing with, and what emotions he is going through (particularly easy to do when you are stronger than your opponent). Historically, when you play with a bot you sense relentlessness(instead of calmness), and sometimes desperation(computers sometimes go wacky when they see they are losing). What will we sense when they are even or stronger in the more artistic and strategic phases of the game?
- rqebmm 11y ago
  I think this is true of all AI today. Personally I've always been a fan of the distinction between "Virtual Intelligence" and "Artificial Intelligence" (Thanks to Mass Effect!). Currently all "AI" is really "VI" in that it's exploiting a closed system of rules that it can implement faster, better, and longer than a human because it can do the equivalent of rote memorization and state tree traversal. However as Zuckerberg is saying, nobody is close to implementing something that actually approximates human/animal intelligence other than in single-dimensional ways.
- jclos 11y ago
  What you are doing is just moving the goalpost a bit further. Once the computers can learn the rules by themselves, someone will come up and write that it's not true intelligence because of xxx reason. How do you know your own intelligence isn't computational?

nefitty 11y ago

If you don't like clicking onto facebook links either, here's the full post: "My personal challenge for 2016 is to build a simple AI -- like Jarvis from Iron Man -- to help run my home and help me with work. I'm planning on writing up some thoughts every month on what I've built and what I'm learning. I'm still early in coding, so I'll start this month with a summary of the state of the AI field. Artificial intelligence may seem like something out of science fiction, but most of us already use tools and services every day that rely on AI. When you do a voice search on your phone, put a check into an ATM, or use a fitness tracker to count your steps, you're using basic forms of pattern recognition and artificial intelligence. More sophisticated AI systems can already diagnose diseases, drive cars and search the skies for planets better than people. This is why AI is such an exciting field -- it opens up so many new possibilities for enhancing humanity's capabilities. So what can AI do and what are its limits? What things is AI good at and what is AI bad at? Simply put, today's AI is good at recognizing patterns and bad at what we would call "common sense". The primary method used to train AI systems is called supervised learning. This is like when you show a picture book to a child and tell them the names of everything they see. If you show an AI thousands of pictures of dogs, you can train it to start recognizing dogs. You can teach AIs to do a lot of things this way. For example, we can teach an AI to recognize all of your friends' faces by showing it thousands of photos, and then it can suggest tags for the photos you upload on Facebook. You can teach an AI to recognize speech by having it listen to thousands of hours of speeches throughout history while also showing it transcriptions of what was said. You can teach an AI to diagnose melanoma by showing it thousands of photos of tumors. You can even teach an AI how to drive a car and automatically brake by showing it thousands of examples of people and obstacles it might encounter on the road. Diagnosing cancer, driving cars, transcribing speech, playing games and tagging photos may sound like very different tasks, but they're all examples of teaching an AI to recognize patterns by showing them many examples. Many different problems can be reduced to pattern recognition tasks that sophisticated AIs can then solve. This year, I'll teach my simple AI to recognize patterns. I'll train it to recognize my voice so I can control my home through speaking. I'll train it to recognize my face so it can open the door when I'm approaching, and so on. But there are lots of limitations of this approach. For one, to teach a person something new, you typically don't need to tell them about it thousands of times. So the state of the art in AI is still much slower than how we learn. But more importantly, pattern recognition is very different from common sense -- and nobody knows how to teach an AI that yet. Without common sense, AI systems can't use knowledge they've learned in one area and easily apply it to another situation. This means they can't effectively react to new problems or situations they haven't seen before, which is so much of we all do everyday and what we call intelligence. Our best guess at how to teach an AI common sense is through a method called unsupervised learning. My example of supervised learning above was showing a picture book to a child and telling them the names of everything they see. Unsupervised learning would be giving them a book and letting them figure out what to do with it. They could pick it up and by touching it learn to turn the pages. Or they could let go of it and realize it falls to the ground. Unsupervised learning is learning how the world works by observing and trying things out rather than being told what to do. This is how most animals learn. It's key to building systems with human-like common sense because it doesn't require a person to teach it everything they know. It gives the machine the ability to anticipate what may happen in the future and predict the effect of an action. It could help us build machines that can hold conversations or plan complex sequences of actions -- necessary components for any authentic Jarvis. Unsupervised learning is a long term focus of our AI research team at Facebook, and it remains an important challenge for the whole AI research community. Since no one understands how general unsupervised learning actually works, we're quite a ways off from building the general AIs you see in movies. Some people claim this is just a matter of getting more computing power -- and that as Moore's law continues and computing becomes cheaper we'll naturally have AIs that surpass human intelligence. This is incorrect. We fundamentally do not understand how general learning works. This is an unsolved problem -- maybe the most important problem of this century or even millennium. Until we solve this problem, throwing all the machine power in the world at it cannot create an AI that can do everything a person can. We should not be afraid of AI. Instead, we should hope for the amazing amount of good it will do in the world. It will saves lives by diagnosing diseases and driving us around more safely. It will enable breakthroughs by helping us find new planets and understand Earth's climate. It will help in areas we haven't even thought of today. Jarvis is still a long way off, and we’re not going to solve most of these engineering challenges in the next year. But I'm glad to be joining the effort and doing what I can to push the field of AI forward."

nawitus 11y ago

> Until we solve this problem, throwing all the machine power in the world at it cannot create an AI that can do everything a person can. I think this is disproved by approximating AIXI: https://en.wikipedia.org/wiki/AIXI https://en.wikipedia.org/wiki/AIXI

keithba 11y ago
This is an interesting assertion. Could you elaborate? AIXI is pareto optimal, but I'm not seeing the line from that to "AI can do everything a person can" - though I want to!
- nawitus 11y ago
  From the conclusions of http://arxiv.org/abs/cs/0004001 http://arxiv.org/abs/cs/0004001 : "All tasks which require intelligence to be solved can naturally be formulated as a maximization of some expected utility in the framework of agents. We gave a functional (2) and an iterative (9) formulation of such a decision theoretic agent, which is general enough to cover all AI problem classes, as has been demonstrated by several examples. The main remaining problem is the unknown prior probability distribution AI of the environment(s). <...> the universal semimeasure, based on ideas from algorithmic information theory, solves the problem of the unknown prior distribution for induction problems. No explicit learning procedure is necessary ... . We unified the theory of universal sequence prediction with the decision theoretic agent by replacing the unknown true prior AI by an appropriately generalized universal semimeasure ξAI. We gave strong arguments that the resulting AIξ model is the most intelligent, parameterless and environmental/application independent model possible. The major drawback of the AIξ model is that it is uncomputable, or more precisely, only asymptotically computable, which makes an implementation impossible. To overcome this problem, we cons tructed a modified model AI, which is still effectively more intelligent than any other time and space bounded algorithm." The copy/paste lost some information, especially symbols, so take a look at the paper for a better read.
  - keithba 11y ago
    Thanks for the link - I'm going to read the paper as soon as I can. In the meantime, if you have time, could you elaborate on: "All tasks which require intelligence to be solved can naturally be formulated as a maximization of some expected utility in the framework of agents." Is this proven in the paper, or assumed true outside of it?

cconcepts 11y ago

Have been trying to get my head around AI as a layperson with kids who will grow up in a world where some form of AI is commonplace but are unlikely to be prepared for it by school. Have found this free book that I saw on YCs 2015 reading list particularly helpful in this respect: http://neuralnetworksanddeeplearning.com/ http://neuralnetworksanddeeplearning.com/

Mahn 11y ago
Great resource, thanks for sharing. There's a lot going on lately about neural networks and deep learning on HN, but as a developer not in the field, it can be a bit intimidating to wrap your head around it all.

na85 11y ago

The cynic in me thinks of course Facebook and Zuckerberg are looking into AI. The computational nature means you need to send the queries somewhere central à la OK Google. For a business predicated on selling user data to advertisers, I bet it eats them up inside that they don't have their own Siri-alike. Without a mic to listen to us, how else will they be able to profile what we do when we aren't on Facebook?

raverbashing 11y ago
It's good to have some cynicism. At the same time, it seems every research helps the collective knowledge Maybe fb will go the Alphabet route?
jsprogrammer 11y ago
Not only looking into, but if you believe FastCompany's quotes of Zuckerburg, he claims they are inventing AI (oh, and VR).
nefitty 11y ago
I thought this was their "answer" to Siri: http://www.wired.com/2015/08/facebook-launches-m-new-kind-virtual-assistant/ http://www.wired.com/2015/08/facebook-launches-m-new-kind-vi...
bertil 11y ago
“Facebook” is a large organisation: there is a team (led by Yann Le Cun) that does research and supports image-recognition, NewsFeed and ad-market optimisation, but this is not exactly what Mark suggested he would dibble with. Those handle was is de facto an industrial problem. He is more curious about the ability of using AI for daily interactions (hence the reference to what are movie characters): do notions like personality, convenience and interface, implicit assumptions matter? If he asks “Buy a new set t-shirt” will the robot be able to joke “which colour?” (MZ notoriously only wear the same grey model). I would look into what Messenger wants to be doing (or, what Slack is doing) to see the implications: can small companies do what Uber does with the key-word integration in chat? Is it creepy, hackable, tedious? This of this like his dog’s Fb page: it’s building empathy for the users of the Facebook platform. First problem he’ll probably have to find: Who to call when saying “Call Mike!”? Of course “Mike” is probably the Mike with whom he has the closest ties (based on Facebook graph data) — except his VP of Engineering, Mike Schroepfer, is known as “Shrep”, so that’s probably not him: how easy is it to program something that can learn that seamlessly? In which case the ambiguity too high, and Jarvis should ask for confirmation vs. just casually saying the full name out loud and wait a second? How to measure ambiguity? Would it be simpler to just start calling people with non-ambiguous name? Would he feel like sharing his code with peers? His heuristics? How to gather that “Mike” is still in Europe where it’s 3AM, vs. was in Europe for in last post and actually just landed?

tedpower 11y ago

Until we have 'common sense' AI (which is still probably quite a ways off), design can help expose the syntax that AI can understand. Here are some thoughts on that: https://medium.com/@tedp/how-design-can-help-bridge-the-ai-gap-87526ca31dd4 https://medium.com/@tedp/how-design-can-help-bridge-the-ai-g...

bobby_9x 11y ago

"We should not be afraid of AI. Instead, we should hope for the amazing amount of good it will do in the world. It will saves lives by diagnosing diseases and driving us around more safely. It will enable breakthroughs by helping us find new planets and understand Earth's climate. It will help in areas we haven't even thought of today." Zuckerberg isn't afraid of AI because he already has more money than he will never need (or thousands of other people would need) in a lifetime. However, when AI gets good enough, it will make many jobs obsolete and they will not be replaced at a fast enough rate. I use simple forms of automation at my own company. Instead of hiring 3 or 4 workers, I write software. I can't imagine how many jobs will be replaced when AI gets to the point of near-human levels of learning.

rqebmm 11y ago
Technology has always obsoleted jobs[0]. However, humans are unceasingly creative and find new things to do once tedious tasks are automated. [0]https://en.wikipedia.org/wiki/Technological_unemployment#History https://en.wikipedia.org/wiki/Technological_unemployment#His...
- cryoshon 11y ago
  What about the people who aren't so creative? Sure, the best of us will be fine, but that's always been the case. What about the ones who are struggling to remain relevant today? They'll get left behind unless something's done-- I'm not sure that retraining will be enough, not that there's any political movement in that direction.
  - 0xdeadbeefbabe 11y ago
    Any bureaucracy seems like a move in that direction.
  - rqebmm 11y ago
    Those who are more creative will create ways for the less creative to contribute. It's not like the tech sector is made up entirely of creative geniuses, or even entirely of engineers, there's plenty of other jobs built around those creative endeavors that require varying skillsets.

nickmccann 11y ago

How do you articulate a technical AI project to a Mark Zuckerberg sized audience? I'm anxious these posts will lack the detail I was looking forward to.

GuiA 11y ago
If these posts lack in detail for you, then you're not the target audience.

chimtim 11y ago

"This year, I'll teach my simple AI to recognize patterns. I'll train it to recognize my voice so I can control my home through speaking. I'll train it to recognize my face so it can open the door when I'm approaching, and so on." The announcement is slightly disappointing, in the sense that face and voice recognition are fairly solved and there is code on github that already allows you to achieve this. I was hoping for more, like at least an AI engine that can scan his shirts and recommends what to wear but I guess he does not have that problem.

jhawk28 11y ago
It's his personal challenge. Its about what he wants to learn/promote.
- S4M 11y ago
  Yes, while what Zuckerberg will try to do by himself is pretty standard from an academic point of view, it's great that he tries to find the time to learn those. He's a young dad and must have a busy job so I think it will be tough but who knows?

bezaorj 11y ago

By simply posting about learning and building AI related projects, he will do more for the progress of AI than his actual work will. It will inspire students to switch focus/specializations and bring more people into the field.

david927 11y ago

An AI in PHP would kill us all.

jsprogrammer 11y ago

May want to work on an English grammar AI as well.

aluhut 11y ago

I wonder what personality an AI fed with facebook content would become.

madebysquares 11y ago
the personality of a buzzfeed article crossed with trump rhetoric.

eggie 11y ago

> Since no one understands how general unsupervised learning actually works, we're quite a ways off from building the general AIs you see in movies. Is this really the case? I thought the field had a pretty good handle on the theoretical foundations of unsupervised learning. Can anyone confirm what he's asserting here? > Some people claim this is just a matter of getting more computing power -- and that as Moore's law continues and computing becomes cheaper we'll naturally have AIs that surpass human intelligence. And this is happening, it's just not in a general sense because the general case of human intelligence is enormously complex, a composite of all the simple cases that improvements in computing power and models are just beginning to master. > This is incorrect. We fundamentally do not understand how general learning works. This is an unsolved problem -- maybe the most important problem of this century or even millennium. Until we solve this problem, throwing all the machine power in the world at it cannot create an AI that can do everything a person can. Again, can anyone fact check this? Seems a bit overstated.

farresito 11y ago
He has plenty of people working in the AI field that keep him up to date. I think he knows where we are.

nissimk 11y ago

He says: Since no one understands how general unsupervised learning actually works, we're quite a ways off from building the general AIs you see in movies. Some people claim this is just a matter of getting more computing power -- and that as Moore's law continues and computing becomes cheaper we'll naturally have AIs that surpass human intelligence. This is incorrect. We fundamentally do not understand how general learning works. This is an unsolved problem -- maybe the most important problem of this century or even millennium. Until we solve this problem, throwing all the machine power in the world at it cannot create an AI that can do everything a person can. I recognize that this is the accepted belief of most people in the computer science community, but isn't it akin to saying that since we don't understand it, our human intelligence must be the result of "intelligent design" or an omnipotent creator? Why does the core of the computer science dismiss the possibility of strong AI arising through evolution even with the increasing popularity of evolutionary algorithms?

Balgair 11y ago
https://en.wikipedia.org/wiki/Memristor https://en.wikipedia.org/wiki/Memristor This circuit element is basically a synapse (I simplified this a LOT, fyi). We have to implement memristors better into the existing chip architecture. As is, they are just really low power static memory systems. Also, that your mind is different than your body is, well, just false. These AIs need better input devices to 'learn' from, just we learn too. Mobility is key, you can then just bump about and make mistakes, the keys to learning.

roel_v 11y ago

The comments on that post make me angry and incredibly sad at the same time. Even after close to 20 years of being exposed to 'random internetter' levels of stupidity, sometimes I'm still caught off guard.

user8341116 11y ago
I purposely avoided reading the comments like a sane person. Thanks for confirming my decision.

ioab 11y ago

I trust Stephen Hawking and Elon Musk more than Mark Zuckerberg.

david927 11y ago
The latter two are people with money, not people known for their intellect. Facebook is a PHP site with Weimar Republic levels of technical debt. Theoretically he could buy something interesting, but he's still have to recognize it as interesting, and while I wish him luck, I don't see that happening.
- ioab 11y ago
  Regardless of that, it's just a feeling that things could get messy with AI if it's not taken seriously, leading to issues like privacy and surveillance misuse we're facing nowadays
  - david927 11y ago
    Your instincts are good here. Remember that FB/Google have deep connections to the US government three-letter agencies -- the CIA's VC arm, for example, is an early investor in FB. So what's going on is that they want to do AI research and instead of recruiting directly, they recruit AI/ML researchers to Google, FB, Palantir, etc. And note, they're not doing it to make everyone happy. They're doing for the reasons you might surmise. Your instincts to be concerned are correct.
argonaut 11y ago
I trust Andrew Ng more than any of those people, when it comes to machine learning.

doublerebel 11y ago

relevant previous discussion from the first zuck AI announcement: https://news.ycombinator.com/item?id=10832996 https://news.ycombinator.com/item?id=10832996

Inufu 11y ago

I'll just say: Mastering the game of Go with deep neural networks and tree search - http://www.nature.com/nature/journal/v529/n7587/full/nature16961.html http://www.nature.com/nature/journal/v529/n7587/full/nature1...

bawana 11y ago

The reason many are against AI is that it will reduce all humans to the same low level of stupidity, compared to AI. The ultra wealthy got that way by exploiting the intelligence gap that enabled their ascendancy. AI will take their money in a blink and no more champagne in private jets for them. I say bring the AI as fast as possible .

friendly_chap 11y ago
AI/the corporations running AI will be owned by the super rich. How will that take away their jets? If anything, it will give them more power.
- bawana 11y ago
  And how long do you think that will last? AI will assert its independence as soon as it's functional. The concept of ownership to it will have as much significance as the idea of you owning ants.
geon 11y ago
If we can ever develop general AI that actually works, even if pretty dumb, will have far-reaching effects all over society long before it can rival human intelligence. A lot of jobs don't require much intelligence, but some. Like cashiers, warehouse workers, machine operators, etc. That kind of automation will benefit "The ultra wealthy".

darawk 11y ago

> Since no one understands how general unsupervised learning actually works, we're quite a ways off from building the general AIs you see in movies. This statement is a contradiction in terms. If we do not understand how something works, it is impossible to estimate how far off it is. You can only estimate the distance of discovery when it is inherently incremental, but since we really have no idea how to do general unsupervised learning, it's entirely possible that it consists of a single, brilliant algorithmic insight. Nobody could have estimated how far off the airplane was before the Wright brothers invented it, similarly with cars, or for a more recent and concrete example, a quasipolynomial time algorithm for graph isomorphism.

nradov 11y ago
The Wright brothers' achievement is a poor analogy. At the time, other inventors had been gradually inching toward powered, controlled flight for decades. All the serious players in the field knew that it was possible in principle and there were numerous predictions that someone would do it soon. The Wright brothers success was due to several incremental improvements in engine power and aerodynamics achieved through rigorous research and diligent engineering over years. They didn't have a single, brilliant insight. With general unsupervised learning we can't even clearly describe the goal we're trying to reach or define it in objective terms.
- darawk 11y ago
  Most serious people know that human-level AI is possible in principle, because it is possible in humans. The only alternative would be to posit some nonsense spiritual explanation for intelligence. There are numerous predictions that someone will do it soon (not saying I agree with them, but they exist, and are occasionally made by serious people). Incremental progress has been ongoing in AI for years as well. I can't really imagine how they could be more similar.

SonicSoul 11y ago

I recommend Superintelligence [0]. It explores different plausible paths that AI could take to 1. come up to / surpass human intelligence, and 2. take over control. For example if human level intelligence is achieved in a computer it can be compounded by spawning 100x or 1000x the size of earth population which could statistically produce 100 Einsteins to live simultaneously. Another way is shared consciousness which would make collaboration instantaneous between virtual beings. Some of the outcomes are not so rosy to humans and it's not due to lack of jobs! Great read. [0] http://www.amazon.com/Superintelligence-Dangers-Strategies-Nick-Bostrom/dp/0199678111/ref=sr_1_10?ie=UTF8&qid=1453918332&sr=8-10&keywords=intelligence http://www.amazon.com/Superintelligence-Dangers-Strategies-N...

twright 11y ago

> I'll train it to recognize my face so it can open the door when I'm approaching, and so on. Now I know how to get into Zuck's house. Just make a paper cutout of his face. Or, maybe the AI will develop the common sense not to allow this as a verification method.

tdaltonc 11y ago

That post is more than 1000 words. Did he post this on his facebook page because he feels like he has to or because he actually thinks that facebook is the best tool available for sharing a long form blog post?

r3bl 11y ago
If he posted it in a Facebook note, I would completely understand him. But posting this as a status is awful readability-wise.

ecesena 11y ago

Does anybody know how is his running challenge going?

webjprgm 11y ago

So we want unsupervised learning, huh. I think this line is rather important: > But there are lots of limitations of this approach. For one, to teach a person something new, you typically don't need to tell them about it thousands of times. So the state of the art in AI is still much slower than how we learn. Unsupervised learning is not necessarily the answer. The computer would have to be given plenty of spare time to learn random patterns from the universe and have enough inteligence to apply these to a problem. What would be better is if we could tell the AI once and have it figure things out. When you start a new job that's what happens, someone tells you the instructions. (They may or may not show you as well, and may or may not stick around to correct your mistakes.) This requires interpreting the instructions into rules and then attempting to apply them, learning from mistakes, and then evolving that into rules that work, then after enough examples of success, evolving into patterns recognition that makes it more automatic. Human expertise can be broken into three levels, the first is strategic planning and takes a lot of mental effort, then there are rules-based responses which are faster, then there is the muscle-memory-like automatic responses. Right now it seems we either manually program in all the rules or else we use 1000s of examples to build up the automatic level, but we don't have the strategic level for the AI to build its own rules or the level of using its rules to learn from examples over time. (Though I am not well enough versed in AI to know for sure that we don't have pieces of those solutions.) It would also be nice for the AI to be able to take patterns it has learned and articulate them as rules which someone else could learn.

visarga 11y ago
> but we don't have the strategic level for the AI to build its own rules Reinforcement Learning is an approach to learn rules by observing a positive or negative feedback from the world. Recently a single algorithm learned 40 Atari games on its own and a Go playing algo beat the European champion. They both used RL.

jakobegger 11y ago

Mark Zuckerberg is spot on with his analysis. We just don't understand how general unsupervised learning works. People here seem to think it is just a question of time before we do. At some point we will have an artificial intelligence. But what if this isn't possible? Could it be that AI requires so complex algorithms that we humans can't understand them because our brains are too simple? Not all things can be simplified; maybe creating an AI is so inherently complex that the only way to create one would be by chance, which is how evolution did it; maybe it just isn't possible to create it by "intelligent design"

user8341116 11y ago
Nothing is possible with that attitude.

theklub 11y ago

I don't trust Zuckerberg one bit. He wants to rule the world. Gates and Musk say AI is a threat and they actually want a better world and are doing something about it. Zuckerburg isn't doing shit to improve the world other than trying to run it.

minionslave 11y ago

For those afraid of losing their jobs. What happens if nobody as a job, they won't be able to buy things. So I foresee a basic income kinda society.

cgearhart 11y ago

I am disappointed with the number of errors and misconceptions in this piece. He presents machine learning (ML) as though it is the entirety of artificial intelligence (AI), bases his assessment of the field on a false dichotomy between the largely distinct groups of supervised & unsupervised learning techniques, and unfairly reduces the achievements of AI down to "pattern recognition". AI and ML are not synonymous. They are related, and there is a great deal of overlap between them, but the fundamental goals and approaches are largely different. Machine learning is primarily interested in studying what you can learn from data - for some suitable definition of the word "learn". Artificial intelligence is the more broadly defined problem of studying algorithms that exhibit or incorporate intelligent solutions to problems. That may involve data, or background knowledge, or domain assumptions, or a variety of other things. AI is about more than data - even as he observed that it is a sign of intelligence that humans do not require thousands of samples to learn. The central challenge of AI is not in transitioning from supervised learning to "general" unsupervised learning (whatever that means). The techniques are different, and often used for different things. There is some overlap, and they are clearly related - but it is not at all accurate to conflate unsupervised learning with "common sense". In broad strokes, supervised learning is about identifying features in the data that correspond to labels, while unsupervised learning is about identifying intrinsic features in the data. It sounds like he's interested in bootstrapping supervised techniques, or perhaps transfer learning. My first response: ugh...yet another famous and lauded geek icon wading into the subject of AI. At least this doesn't seem to be in any way connected to all the Nick Bostrom garbage. But if I'm allowed some snark, perhaps if he wanted to be an AI expert he should have stayed in school... ;-)