7 ms·

This is about 100 years too early. Seriously why do people think neural networks are the answer to AI? They are proven to be stupid outside of their training da

• ceejayoz 11y ago
  The linked site says nothing about neural networks.
  • argonaut 11y ago
    The site straight up says "deep learning." Which is neural networks.
    • ceejayoz 11y ago
      There's a paragraph basically saying "there's been some cool stuff happening (you may have even heard about) in this particular field". Extrapolating that to the entire organization thinking that "neural networks are the answer to AI" as OP claimed is silly.
      • argonaut 11y ago
        Of the researchers they hired (some of them don't appear to be active researchers right now, like Trevor Blackwell), they're all are deep learning researchers...
  • hacker_9 11y ago
    "we've also started to see what it might be like for computers to be [creative], to [dream], and to [experience the world]." All three of those links are about neural networks.
    • ceejayoz 11y ago
      So you've turned "what it might be like" with a couple examples of mild AI-ish tasks that caught the public's attention this year into "the answer"?
• rboyd 11y ago
  What does it feel like to be so confident in an opinion while so many brilliant scientists disagree with you?
  • dang 11y ago
    Please let's resist taking this thread flameward. The GP contains both a substantive point and provocation, which isn't great. In such cases, the helpful way to respond is to de-escalate, by addressing the substantive point and ignoring the provocation.
  • paxcoder 11y ago
    I'm not the same guy, but I'd like to answer: Familiar, that's how it feels. I'm confident that I'm right about the other matter, and subjects are related, so I'm not bothered.
    • rboyd 11y ago
      I don't think openai was formed to concentrate on neural networks, and I think we can assume the members are well aware of the limitations of neural nets. I just don't understand the folks that are so confident that strong AI is either not possible, or not achievable within our lifetimes. If you're in the camp that thinks it's not possible, then you must ascribe some sort of magical or spiritual significance to the human brain. If you don't think it's possible inside of 100 years, then you're probably just extrapolating on history. The thing about breakthroughs is they never look like they're coming. Until they do.
      • paxcoder 11y ago
        I ascribe spiritual significance to the mind (not the brain). If consciousness is more than a mere product of brain's functioning, Strong AI does not have to be beyond the horizon.
• detaro 11y ago
  I don't see any "fear-mongering" in this announcement?
  • hacker_9 11y ago
    The creation of what is essentially an ethics committee for a technology that doesn't even exist yet? With people such as Elon Musk on board who have publicly said 'AI is our biggest existential threat' ? Additionally the second paragraph: We believe AI should be an extension of individual human wills and, in the spirit of liberty, as broadly and evenly distributed as is possible safely. This infers they think AI will be used for hostile means. Such as wiping out the human race maybe? It is just un-informed people making un-informed decisions and then informing other un-informed people of said decisions as if they were informed.
    • detaro 11y ago
      I doubt they are strictly targeting "strong AI", and a lot of the things we use and call AI right now also benefit from open work and discussion. Just because it is just "Machine learning" doesn't mean it isn't used for questionable or bad purposes. EDIT: I have to agree with _delirium's skepticism towards them doing much in that regard though.
    • johann28 11y ago
      Sutskever, Schulman, Karpathy and Kingma are experts in machine learning. And yes, AI will definitely be used for all sorts of purposes including hostile means. Just like anything else, really. Financial manipulation, spying, intelligent military devices, cracking infrastructure security, etc. These are realistic concerns, we shouldn't fall for the Skynet red herring. We can have problems with ethical AI use, even if it's not a self-aware super-human superintelligence.
      • _delirium 11y ago
        I hope I'm wrong, but given the composition of the donors I'd be surprised if they really put much scrutiny on near-term corporate/government misuse of AI, apart perhaps from military robots. There are definitely interesting ethics questions already arising today around how large tech companies, law enforcement, etc. are starting to use AI, whether it's Palantir, the FBI, Google, or Facebook, so no argument that it's a timely subject at least in some of its forms. It'll be interesting to see if they get into that. I'd guess they probably want to avoid the parts that overlap too much with data-privacy concerns, partly because a number of their sponsors are not exactly interested in data privacy, and partly because the ethical debate then becomes more complex (it's not purely an "ethics of AI" debate, but has multiple axes).
• sp332 11y ago
  So throw more data at it then.
• orthoganol 11y ago
  In terms of artificial general intelligence, the kind of stuff that gets associated with 'the singularity' etc. - I agree - there is seemingly nothing at all out there that appears to even be on a trajectory, I mean even theoretically, to coming close. But sure, for more narrow specializations, disrupting certain industries, there is a lot that could be advanced on a short time scale. I don't think the big breakthroughs in artificial general intelligence are going to come from well funded scientific researchers anyways, they are going to come out of left field from where you least expect it.
  • jmatthews 11y ago
    That's the thing. It's not necessarily about an evolution. If I "accidentally" make a break though right now. The AI could evolve into a super intelligence before dinner time. Simply stated, an AI that writes AI.(Forget the halting problem for a moment) How many iterations can it create in 3 hours?
    • KnightHawk3 11y ago
      Probably dependent on your computer ;)
    • argonaut 11y ago
      Think about how long it takes a baby to learn (a few years). There is no reason an AI would self-improve multiplicatively in hours or days or even weeks.
      • Fricken 11y ago
        With a powerful enough computer the learning curve of a simulated baby could hypothetically be condensed to minutes, or seconds. Which would appear to us in normal time to be an intelligence explosion.
        • argonaut 11y ago
          The simulated baby would extremely tax to the limit the entire resources of whatever supercomputer trained it. People have to run deep learning programs on multiple GPUs right now, and performance is constrained by memory bandwidth, which does not follow Moore's law.
• jonknee 11y ago
  Humans are really stupid without training too.
  • hacker_9 11y ago
    Not true. Humans can adapt to many environments by pulling in training from other related environments and applying it to the new data. Some call this generalised learning, but I think it points more to our ability to shape everything we know to any given problem - something 'beyond' just generalising.
    • johann28 11y ago
      You're over-glorifying humans. We're still just a savannah ape and our skills reflect that.
      • hacker_9 11y ago
        What? The brain has not only solved the vision problem (reconstructing depth from still images, recognising the objects in the scene, and filling in the occluded parts), it has also solved the motion problem of coordinated the movement of our ~300 muscles (given constraints, how do I move from A to B, or pickup the cup, or do a handstand), as well as solved the memory problem (basically infinite memory, with some sort of priority system for removing unused/old memories so we can always learn more). Additionally it solved the communication problem with language that computers still can't parse properly. It is so smart it is even conscious, and self-aware as well as death-aware. This is not over-glorifying. That is fact.
        • iopq 11y ago
          If you have to forget, your memory is not infinite. My computer's HD is infinite, but you have to remove programs that you don't use.
          • hacker_9 11y ago
• johann28 11y ago
  It's not necessarily the answer to AI, but it works remarkably well. Is it Skynet or the Terminator yet? No. There are different ideas for what constitutes AI. Expert systems and knowledge-based reasoners? Pattern-recognizer black boxes? Chatbots? AGI? Over the years the concept of AI shifted. Until recent years "AI" was mostly used for things like A* search, creating algorithms that play turn-based table games for example (see the Russell-Norvig book), symbolic manipulation, ontologies etc., a few years ago it began to also refer to machine learning like neural networks again. Neural networks are good at what they are designed for. Whether they will lead to the path to human-like artificial intelligence is a speculative question. But symbolic manipulation alone won't be able to handle the messiness of sensory data for sure. I think neural nets are much better suited for open-ended development than hand engineered pipelines that were state of the art until recently (like extracting corner points, describing them with something like SIFT, clustering the descriptors and using an SVM over bag-of-words histograms). Hand engineering seems too restrictive.
  • _delirium 11y ago
    Quibble with the timeline: AI as a field has included a big chunk devoted to machine learning research pretty much continuously, especially since the '80s or so. The specific methods in vogue do change: decision trees, neural networks, SVMs, boosting, association-rule learning, genetic algorithms, Bayesian networks, etc. go through periods of waxing and waning in popularity. A few years ago boosting/bagging and other ensemble methods were very hot and neural networks were out of fashion; now neural networks are hot and the boosting hype has quieted down a bit. But ML is pretty much always there in some form, since learning from data is an important component of AI.
    • johann28 11y ago
      ML was there but at least when I started learning about these things around 8 years ago, the label "AI" was mostly used for symbolic stuff. Courses named "AI" taught from the Russell-Norvig book. Things like resolution, planning in the block world, heuristic graph search, min-max trees, etc. ML existed but it wasn't really under the label of "AI" as far as I can remember. I think it's something of a marketing term that big companies like Google and Facebook reintroduced due to the scifi connotations. But that's just my guess.
• strong_ai 11y ago
  What do you see as the downside of creating this organization now, as opposed to in 100 years? Artificial Intelligence in its current state has shown itself to be incredibly useful and effective at small tasks. I see no harm in researching and expanding this field (besides opportunity cost). Also, I see a distinct lack of "fear-mongering" in this post.
• kamaal 11y ago
  >>This is about 100 years too early. More fundamentally, we are trying to achieve what we can't even define. Define AI, and implementing it should be quite easy. "Human level AI" seems like trying to define problems through observed characteristics. I think it was Douglas Hofstadter who had said something to the order that we don't even exactly understand what 'intelligence' means, let alone a clear definition reducible to a mathematical equation or a implementable program. Your chess programs, are really not 'thinking' in pure sense, there are trying to replace 'thinking' with an algorithm that resembles the outcome of 'thinking'.