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The impossibility of intelligence explosion
- SlipperySlope 8y agoHis point was refuted long ago by Kurzweil who observed that only with the aid of computers can humans improve on current computing.
- baq 8y agothe meat computer hidden in your head running on ~20W of power does it. why wouldn't an electronic computer be incapable of the same feat is beyond me. make it 20kW or 20MW if 20W sounds unreasonably low.
- ravitation 8y agoDiscussion of the original article on HN: https://news.ycombinator.com/item?id=15788807 https://news.ycombinator.com/item?id=15788807
- whyonearth 8y agoWhat's wrong with the website's editor, posting blogspam of a year-old post as current news? Should be flagged.
- dang 8y agoWe changed the url from https://mindmatters.today/2018/11/software-pioneer-says-general-superhuman-artificial-intelligence-is-very-unlikely/ https://mindmatters.today/2018/11/software-pioneer-says-gene..., which simply copies excerpts from this.
- yters 8y agoIf the original article is a year old, why was this killed as dupe? I've seen old articles reposted on HN before. This repost seemed to be pretty popular. Also, why is it considered blogspam for having excerpts from an original article? I also see this occur frequently on HN. The article not only has excerpts, but comments on the excerpts and links to related material. This appears useful to an interested reader.
- gameswithgo 8y agoOur brains already do it, likelihood is 100%. Nothing would stop transistor based computers from doing it, though they might be very much slower at it.
- yters 8y agoHow do we know our brain creates our mind? That is a materialist assumption, which is just an assumption.
- Sharlin 8y agoIf we can’t assume physicalism, we can’t assume anything. The sun might not rise tomorrow because it might be magicked away.
- yters 8y agoCan you explain why prediction is predicated on physicalism? For example, Hume argues the opposite, and his argument is furthered by Wolpert's No Free Lunch Theorem. It seems like if prediction is possible it is only because physicalism is false.
- deleted 8y ago[deleted]
- yorwba 8y agoIt's an assumption that has been tested many times. Humans can survive losing parts of their brain, but it causes observable changes in their mind. That's were those colorful maps of brain regions and their functions come from: by recording what kind of brain damage caused what kind of function to deteriorate. Don't forget that people used to believe that the heart contained the mind and the brain was just a cooler. There was real evidence that caused scientific consensus to change.
- yters 8y agoThere are some interesting examples of very highly functioning individuals with very little brain. At any rate, correlation does not imply causation.
- fizx 8y ago"When a distinguished but elderly scientist states that something is possible, he is almost certainly right. When he states that something is impossible, he is very probably wrong." ~Arthur C. Clarke
- coldtea 8y agoYeah. Here we are in those rare cases when he is right (though not necessarily for the arguments he makes)
- worldsayshi 8y agoSo what are the right arguments?
- coldtea 8y ago1) That the rise of AI has been predicted again as "coming soon" in the 60s and 70s and nothing came out of it once already. 2) That current AI is just very primitive NNs, and all the hoopla is mostly hype (like Big Data, Grid Computing, Biotechnology, Nanotechnology, Virtual Reality, 3D Printing, and several other previous fads served as revolutionary and the cure for everything) 3) That they are several orders of magnitude more primitive than a human brain. 4) That we haven't had Moore-law style increases in CPU power for quite some time. 5) That, never mind AI, we can't even make a good email app... 6) That all kind of peddler make good money by tooting AI (e.g. IBM selling BS tech as "Watson")
- wild_preference 8y agoIf you can agree that intelligence is just an information processing challenge instead of a magical god-given treasure, then general AI is inevitable. Though note that you couldn't come up with an argument against the future of AI development in six points. They were all independently irrelevant, like denying future medical breakthroughs because doctors didn't wash their hands 100 years ago. Your points are all distracted, like suggesting Elon Musk's tweeting habits today doom all future humans from ever reaching Mars.
- Rallerbabs 8y agoQuote: "An overwhelming amount of evidence points to this simple fact: a single human brain, on its own, is not capable of designing a greater intelligence than itself. This is a purely empirical statement: out of billions of human brains that have come and gone, none has done so. Clearly, the intelligence of a single human, over a single lifetime, cannot design intelligence, or else, over billions of trials, it would have already occurred." What an incredibly inadequate argument. Obviously, none could have done so in the past. Because the required resources simply weren't available. Breakthroughs are being made right here in this era, with Jeff Hawkins' being one of the latest. This guy reminds me of Richard Smalley, who, against better judgment, attempted to make irrational arguments against molecular nanotechnology, as envisioned by Drexler. Also, he can't be a software pioneer. He's too damn young.
- Sharlin 8y agoWow. That argument can be applied to any invention or creation. There are bad arguments and then there are ridiculous ones.
- antt 8y agoHe is merely attacking the lone inventor myth. While it is good for putting names in the history books it is completely inadequate for actually deciding who invented something. Mathematics has the rule of thumb that anything named after someone was not discovered by them. It should equally well apply to all fields of human endeavour. Until we get rid of that myth we will never figure out how creativity actually works.
- baddox 8y agoYes. The argument is logically equivalent to "nothing can ever happen for the first time."
- Upvoter33 8y agoThis quote stuck out for me too, and is clearly, as you say, "inadequate". Also, no invention comes from a single brain; the biggest software systems we build, for example, are designed by many, many people. No one person can even understand something as complex as some of our large-scale software systems. And yet, we build them and they work.
- xutopia 8y agoI too have some resistance to the notion that we will see AGI at a higher level than humans within 50 years. I don't think the arguments he has make any sense. The technology simply did not exist and we're improving on so many fronts mostly because we're now capable of yielding huge neural networks we couldn't fathom having access to just a few years ago. I don't think the technology required to build superhuman AGI exists yet at least at a reasonable cost to humanity. I don't think we will reach this level of massively parallel computing required for Superhuman AGI until maybe 2070 and that's only if we bring together all the world's supercomputers together in one giant artificial brain.
- ansible 8y agoI think we've seen the cross-over point for AGI in the last few years. Just recently, within the last decade, we've seen incredible advances of the usefulness of existing ML/NN based approaches. We have phones and smart speakers which have sufficiently reliable speech recognition. Ditto for vision tasks. What's different now compared to decades past is that businesses can see the benefit of incremental improvements in existing systems. If Siri can easily be demonstrated to be more useful than Cortana, that is a significant competitive advantage, which will sell products and services. The tech giants (and others) see this, so they will continue to invest. This isn't like in past where we tried things here and there, they didn't work as well as we had hoped, and then we stopped investing. The pressure is on all the tech giants to keep investing, and applying that research to more and more of their own businesses (like using ML to manage power and cooling at a data center). We're on a roller-coaster ride into the future, and nothing short of worldwide disaster will stop it. For good or for bad.
- worldsayshi 8y ago> Superhuman AGI The only reasonable definition I can come up with for this would be "More intelectually capable than all of human society. So, yeah. (Any other definition would still allow humanity to outsmart it.)
- josquindesprez 8y ago> There is no evidence that a person with an IQ of 170 is in any way more likely to achieve a greater impact in their field than a person with an IQ of 130. This feels disingenuous. If other things are bottlenecking human success than intelligence (which isn't even entirely true), computers are generally better at these things, especially in an era of massive low-cost computing resources.
- thrwaway22 8y ago"Feynman reported 126, James Watson, co-discoverer of DNA, 124 — which is exactly the same range as legions of mediocre scientists." Can we stop the Feynman had an IQ of 126 narrative? Many people doubt his IQ was in the 120 range. IQ scores, despite what people thing, are not always accurate. Feynman is an example of such a case. Plus, you'd typically report a range on IQ exams. Given a 5+/- point range that could place him in the 131 category, which still feels too low for someone as brilliant as he was. >"Feynman received the highest score in the country by a large margin on the notoriously difficult Putnam mathematics competition exam, although he joined the MIT team on short notice and did not prepare for the test." [0] Someone that does that, most likely does not have a 126 IQ. Given his accomplishments in Physics, it is likely he is more intelligent than any IQ test gave him credit for. [0] https://www.psychologytoday.com/us/blog/finding-the-next-einstein/201112/polymath-physicist-richard-feynmans-low-iq-and-finding-another https://www.psychologytoday.com/us/blog/finding-the-next-ein...
- mar77i 8y agoWe keep trying to teach machines this intelligence thing, while we're still measuring the real thing using IQ tests? We're not even close to having a halfway decent metric for this catchall intelligence term - and these engineers keep failing to model it in a computer program. I see kind of a pattern here.
- leesec 8y agoCan we stop caring what people's IQ is? I've never encountered a scenario where it mattered.
- axus 8y agoIQ is just a number determined by a test, by definition. I don't think it's possible for a person's IQ number to be independent from the IQ test. Certainly he had more intelligent contributions to physics than expected from 126 IQ.
- aetherson 8y agoIQ is valuable insofar as it is a proxy for g. I think that your parent poster was suggesting that while IQ is in general correlated with g, there are cases where it is not.
- iotb 8y agoTo make an accurate projection or statement about something, it is generally necessary that you have a sound understanding of it. This is just my general intelligence speaking here. I see nothing of note that reflects that this person has a fundamental understanding of General Intelligence or has even been in the pursuit of it. Authoring an optimization algorithm suite doesn't mean you have an understanding of General Intelligence. A non-read before even clicking on the link. Two posts today about AGI. Seems the next hype train is arriving right on schedule and its banner will be (AGI).
- commandlinefan 8y agoI don't have the exact quote in front of me, but in 1979, Douglas Hofstadter wrote in his book "Godel, Escher and Bach" something to the effect of: "It may be that some day a computer can beat a human at chess, but when it happens, it will be by the sort of computer that will say, 'no, I'm bored with chess, I would rather talk about poetry'". If Hofstadter can be wrong about anything, anybody can be wrong about anything.
- the_af 8y agoNice quote! Wasn't there an assertion, mentioned several times here on HN, that researchers have found that with AI the seemingly hard becomes easy (e.g. playing chess) and the seemingly easy becomes hard (e.g. walking or... becoming bored with chess)? It now seems qualitatively harder to design a program capable of boredom than one capable of being a chess master.
- baddox 8y agoThat sounds like https://en.wikipedia.org/wiki/Moravec%27s_paradox https://en.wikipedia.org/wiki/Moravec%27s_paradox
- dicroce 8y agoThere is an estimated 100 billion nuerons in the human brain. We know from information theory that DNA is not nearly long enough to describe all of those connections. This means that most of the complexity of the brain is emergent. I envision bundles of neurons that begin their existence mostly disconnected... These bundles are described somewhere in DNA (but not their ultimate learned configuration) and so is whatever learning algorithm drives this process. We will have AGI when we understand the underlying learning algorithm our brain uses... Personally, I believe that algorithm involves fantasizing future scenarios and learning from the fantasies.
- onemoresoop 8y agoFantasy is a mental computation as well. Fantasy AI ftw!
- ravenstine 8y agoAnd yet general biological intelligence arose from unintelligent forces? Hm, interesting. I don't know enough about general artificial intelligence, but his claim seems to hinge a lot on what we already know. There are things we may not know yet that will lead to us generating general artificial intelligence. Although I don't think it'd be required, it may turn out that the experience of consciousness isn't something we can mechanically produce but is a property of matter itself. Now, I can't prove that is so but it's a fun little hypothesis I enjoy thinking about. None the less, there's no particular reason to disbelieve why humans couldn't figure out similar knowledge and apply it to creating better artificial intelligence. Some of his reasoning is just flat out fallacious: > An overwhelming amount of evidence points to this simple fact: a single human brain, on its own, is not capable of designing a greater intelligence than itself. This is a purely empirical statement: out of billions of human brains that have come and gone, none has done so. Yet out of all those billions of brains, how many of them have tried developing general artificial intelligence, let alone the "AI" of an if-then-else statement? Probably 0.00001% of those billions of brains. Yes, I made that number up, but it wouldn't be surprising for that number to be minuscule, below a fraction of a fraction of a percent. Evolution has had billions of years. We've only had computers for less than a century. In that respect, it's not at all surprising that humans haven't mastered what nature unintelligently developed for much longer. > In particular, there is no such thing as “general” intelligence. On an abstract level, we know this for a fact via the “no free lunch” theorem — stating that no problem-solving algorithm can outperform random chance across all possible problems. That depends on how you define the word "general". I don't think that scientists and engineers working on intelligence are actually using the word "general artificial intelligence" in the sense that such intelligence could solve literally any problem. Humans are generally intelligent within a set of fixed domains, but that doesn't mean they don't have general intelligence within certain constraints.
- overlords 8y agoWe have an example AGI - the human brain. We have an example superintelligence - humans working together in groups such as corporations are a superintellgence. So from that, the invention of a human-level AGI naturally leads to superintelligence - lots of the AGIs cooperating. The question then becomes of whether we're going to get to AGI. Evidence points to yes. AGI (human intelligence) is a collection of abilities and the machine learning community is steadily making progress on them. Speech, vision, machine translation, question answering, summarization etc. are all being worked on and steady progress, or in many cases - rapid progress, is being made. Unsupervised learning and reinforcement learning are the frontiers and both have advancements in just the past couple of years (GANs, predictive learning, inverse reinforcement learning, imitation learning, domain randomization). Unsupervised learning in particular is likely the key to AGI and only recently has significant progress been made on it - predictive learning (as Yann Lecun calls it). (Personal conjecture - the next couple of years when a larger number of people investigate predictive learning might lead to AGI - in maybe just 2 years).
- throw2016 8y agoIt seems more likely more fundamental innovations are going to come from academia with a culture of seriousness and decades of work without returns. On this side there is a strong tendency to be blinded by hype, underestimate problems or wish them away with naive desperation that things will just happen based more on hope than reality. We saw that with the self driving crowd underestimating the problems and overestimating the existing technology, and now with the AI folks, who are already guilty of perpetuating hype knowing fully well that their extremely limited definition of 'AI' is nothing like what the world understands by AI. All the privacy shenanigans, crypto disaster, self driving cars and AI leave the reputation of tech community in a very bad place.