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Complexity No Bar to AI
- dwohnitmok 6y agoI think the reasoning presented in this article generalizes pretty well to a refutation of most arguments involving proving the impossibility of some complex, ill-defined, "I'll know it when I see it" kind of phenomenon via a tidy, small logical proof. There's a lot of ways that those kinds of complex phenomenon can be functionally equivalent to human observers, but can have different underlying mechanisms. These tidy logical proofs only ever cut off one extremely specific incarnation of that complex phenomenon rather than the entire equivalence class.
- gwern 6y agoYep. Even assuming the proof is formally valid, often, what an impossibility or no-go result means is just that one of the premises is wrong. (In this case, I think all the premises are wrong in any fixed-up formalized version of the argument from computational complexity, but it's usually not that bad.) Similarly, all of the Godelian or Penrose-style uncomputability arguments tend to rely on some premise like "humans never make mistakes" or "humans never contradict themselves" or "humans can prove any theorem" (or inverse computer versions thereof), which is the sort of premise which once you highlight it and make it explicit, you instantly lose all faith in any conclusion which supposedly follows from it. The relevant saying there is "one man's modus ponens is another man's modus tollens". I have another page on that particular interpretation or argument pattern: https://www.gwern.net/Modus https://www.gwern.net/Modus
- deleted 6y ago[deleted]
- zxcvbn4038 6y agoWhat if AI just wants to watch Star Trek reruns and browse Porn Hub? As is so often the case when humanity creates intelligences.
- mStreamTeam 6y agoThat would be an improvement from previous AIs which have become racist. https://spectrum.ieee.org/tech-talk/artificial-intelligence/machine-learning/in-2016-microsofts-racist-chatbot-revealed-the-dangers-of-online-conversation https://spectrum.ieee.org/tech-talk/artificial-intelligence/...
- superbcarrot 6y agoThey trained a language model on twitter data and extracted some of the sentiment from the training set. The antropomorphic language of "AIs which have become" is misleading.
- chromanoid 6y agoYeah, the developers made the algorithm racist by incorporating racist texts in the training phase. Shit in shit out...
- LesZedCB 6y agotraining data will always reflect the culture which generated it
- sitkack 6y agoAIs most powerful feature might be a lens into human behavior and psyche. Who knows how it will turn out. I think an AI might run meetings better than humans, it might even make a better manager.
- LesZedCB 6y agophilosophers have been doing that for millenia. some have made material changes to society, and others haven't. some have questioned the validity of "material change" being a good metric in the first place. personally, i believe philosophy is the most important starting point for any discussion about AI. and i really hope that AI helps more than making office work a little less tedious...
- coldtea 6y agoThe biggest pile of hand-waving I've seen...
- ProfHewitt 6y agoFor something a little more rigorous see the following: "Robust Inference for Universal Intelligent Systems" https://papers.ssrn.com/abstract=3603021 https://papers.ssrn.com/abstract=3603021
- delightful 6y agoPlease stop posting links to your papers all over the place not stating your the author and not explicitly embedding what you have to say in the comments themselves; as is, to me, you’re no better than a spammer. In the comment above, you even copied and pasted it from your last comment and forgot to update the URL; that is, the URL above is from your prior comment which is formatted exactly the same way; stop spamming.
- carapace 6y agoYou are replying to the famous computer scientist prof. Carl Hewitt. He doesn't have to state who he is because everybody already knows (except you, evidently.) https://en.wikipedia.org/wiki/Carl_Hewitt https://en.wikipedia.org/wiki/Carl_Hewitt
- rq1 6y agoWelcome to HN. Where a cohort of id*ots can look CH in the eye and confidently downvote him.
- heavyset_go 6y agoIt's pretty telling that some people respond with strong dismissals of an actual accomplished researcher in the field we're discussing versus the musings of some programmer who blogs.
- shawnz 6y ago
- ProfHewitt 6y agoFor state of the art on foundations of mathematics, see "Recrafting Foundations of Mathematics" https://papers.ssrn.com/abstract=3603021 https://papers.ssrn.com/abstract=3603021
- monstersinF 6y agoThis paragraph in that article is an incomplete sentence that ends hanging. Any idea what it intended to say? > “Monster” is a term introduced in [Lakatos 1976] for a mathematical construct that introduces inconsistencies and paradoxes. Since the very beginning, monsters have been endemic in foundations. They can lurk long undiscovered. For example, that "theorems are provably computational enumerable" [Euclid approximately 300 BC] is a monster was only discovered after millennia when [Church 1934] used it to identify fundamental
- monstersinF 6y agoAlso I don’t understand the impact of Wittgenstein‘a work on Godel’s discovery, could you clarify for me? What are the implications. The consensus I’ve read indicates it’s a misguided interpretstion
- ProfHewitt 6y agoWittgenstein's devastating critique of [Gödel 1931] came afterward. See the article referenced in this discussion.
- monstersinF 6y agoThanks for the response Professor. What do you make of the following article though? It concludes that the critique is not devastating to Gödel http://wab.uib.no/agora/tools/alws/collection-6-issue-1-article-6.annotate http://wab.uib.no/agora/tools/alws/collection-6-issue-1-arti...
- ProfHewitt 6y ago
- rpiguyshy 6y agoeach problem is different. computational chemistry has stagnated therefore AI isnt a concern? its nonsense. first of all, it may be that computational chemistry is much more tractable than we realize because we are too stupid to find the necessary footholds. but regardless, some tasks are actually mathematically intractable. there is no way to draw a connection between AI and any other problem, certainly not a connection definitive enough to write off the risk of AI... that is the key. its all speculation. as long as there is some possibility of creating AI, we have to account for it in our collective decision-making. like many people before them, most people seem happy to write off the possibility of anything that hasnt happened already. fools.
- idlewords 6y agoIt's past time to start calling these treatises on hyperintelligence what they are—theology—and treating them with the respect they deserve, which is a lot less than they currently get on this site. People have been theorizing about the attributes of the Absolute since forever. Just because you start talking about building a god, rather than positing one already in existence, doesn't make the discussions about the nature of such hypothetical superbeings any more fruitful.
- apsec112 6y ago[deleted]
- heavyset_go 6y ago"Argument from fallacy Argument from fallacy is the formal fallacy of analyzing an argument and inferring that, since it contains a fallacy, its conclusion must be false. It is also called argument to logic (argumentum ad logicam), the fallacy fallacy, the fallacist's fallacy, and the bad reasons fallacy." https://en.wikipedia.org/wiki/Argument_from_fallacy https://en.wikipedia.org/wiki/Argument_from_fallacy
- idlewords 6y agoAnd let us not forget the Argument from Cut and Paste, beloved of this forum.
- drdeca 6y agoSaying that an argument is fallacious isn’t the same thing as saying that because the argument is fallacious, it is therefore wrong. Surely you don’t think that all cases of pointing out that something is a fallacy need to include a disclaimer saying “but of course, that doesn’t in itself imply that the conclusion is wrong”. After all, you did not include such a disclaimer yourself. That being said, it seems that the back and forth here doesn’t really seem to have any statements of the form “X (and also Y), therefore Z”. So, I guess that makes it hard to analyze formally as an argument, as instead much of the things like that being explicitly said, there are things being mentioned, with a number of things left implicit.
- LesZedCB 6y agopersonally i find a lot of arguments against AGI coming any time soon couched in a culture of human exceptionalism, even those who wouldn't claim as much directly. there is a DAMN surprising level of intelligence in significantly less complex life. we are just so attached to intelligence as defined by human culture to call it as it is.
- 1_2__4 6y agoI don’t even know where to start.
- Taek 6y agoI firmly believe that raw intelligence has little to do with our lead as a species, and it may even be the case that there are numerous animals with more raw intelligence than humans, especially predators. Our advantage comes from our ability to pass information on to eachother. A piece of knowledge that took 10,000 hours of thinking, observing, and experimenting to come by may only take 4 hours to pass on. Humans can do this much better than any other animal. That's a skill borne of communication advantages, not raw intelligence advantages.
- dj_mc_merlin 6y agoPerhaps, but animals do not seem to understand abstract concepts as well as us. This may be linked to language too. Without the ability to make analogies in their brain, no crocodile will figure out the worlds made of atoms or if you rub sticks really quickly they make fire.
- qayxc 6y ago> I firmly believe that raw intelligence has little to do with our lead as a species This statement carries no meaning unless you define what "raw intelligence" is.
- joe_the_user 6y agoWell, logic-based "AI" (GOFAI), was much more about logic programming, automating explicit, human conscious reason and that's generally been considered a failure or at least a dead end. Deep learning and related approaches don't seem as human related as earlier - there's even deep worm that's trying to simulate worm behavior. The thing about hard arguments against AI, however, is that they have to come down to "there's a quality X that a machine can't emulate". And usually the X is intuitive/philosophical concept with great resonance to humans but which is actually quite ill-defined. If X was exactly defined, well, we'd be able to compute it after all. So you get X as "spark of life", "soul". "being in the world" etc. And that kind of again shows "human exceptionalism" as the perspective.
- wwww4all 6y agoHumans can already create intelligence. Called human babies. Human babies are already nurtured, educated and developed into intelligent beings. AI is like alchemy, trying to create something of value from nothing. People pontificating about AI is like medieval monks pontificating about how many angels can fit on pin head. What is AI? What are boundary conditions of AI? Calling faster computers AI doesn’t make it sound more interesting.
- Animats 6y agoWell, it's better than the argument that machines can't resolve undecidable questions but humans can. There's a large family of problems that are NP-hard in the worst case, but much easier in the average case. Linear programming and the traveling salesman problem are like that. The research question I would pose is, why is robotic manipulation in unstructured spaces so hard? Machine learning has not helped much there. Yet it's a fundamental animal skill. We're missing something that leads to success in that area. Whatever that is, it may be the next thing after machine learning via neural nets. Note that it's not a human-level problem. Primates have the hardware for that. Mammals down to the squirrel level can manipulate objects. Mice, maybe. Mouse-level neural net hardware exists. It's not even that big. The University of Manchester's neural net machine supposedly has mouse-level power, in six racks. I tried some ideas in this area in the 1980s and 1990s, without much success. Time for the next generation to look at this. More tools, more compute power, and more money are available.
- segmondy 6y agorobotic manipulation in unstructured spaces is probably not so hard anymore. when it comes to hardware, the hardware has often been the problem and very flaky, I believe we are at a stage where the software is ready and waiting for the hardware to catch up.
- Isinlor 6y agoHumans are able to do surgical operations using existing hardware [0], but software can not. Humans can drive cars on crazy Indian roads, software can not. Existing hardware is plenty sufficient for manipulating physical world, but we are missing the intelligence part. [0] https://www.davincisurgery.com/ https://www.davincisurgery.com/
- visarga 6y agoAI's need special training grounds because they don't have the benefit of evolution. If they don't have realistic bodies in a realistic environment they can't learn to solve the problem of locomotion and manipulation. Have you noticed the explosion of "AI Gyms" in the last few years? As others have said, we're at a good point with vision and control, but hardware is still expensive, and this slows research. I expect dexterous robots in a decade, BD's already got one dancing better than me.
- carapace 6y agoOne problem with Singularity is that you either A) have to be first, or B) have to contend with other beings at least as intelligent as you are. How can you be sure you're first?
- yters 6y agoThere are no mathematical theories of runaway intelligence growth. On the other hand there are many theorems of fundamental limits to maechanical processes. E.g. NP completeness codiscoverer Leonid Levin also proved what he calls independence conservation that states no stochastic process is expected to increase net mutual information. Then there are the more well known theorems with similar implications: no free lunch theorems, halting problem, Kolmogorov complexity's uncomputability, data processing inequality, and so on. There is absolutely nothing that looks like runaway intelligence explosion in theoretical computer science. The closest attempt I have seen in Kauffman's analysis of NK problems, but there he finds similar limitations, except with low K terrains, but that analysis is a bit questionable in mind. To make arguments like gwern and Kurzweil they are essentially appealing to mysticism; assuming there is a yet to be discovered mathematical law utterly unlike anything we have ever discovered. They are engaging in promissory computer science, writing a whole bunch of theory checks they hope will be cashed in the future.
- deleted 6y ago[deleted]
- fpgaminer 6y agoWe already have an existence proof for the singularity, so I don't know why there's any debate about _if_ the singularity will occur. I can see debate about what exactly the "singularity" entails, when, how, etc. But it's inevitable. The Cosmic Calendar (https://en.wikipedia.org/wiki/Cosmic_Calendar https://en.wikipedia.org/wiki/Cosmic_Calendar) makes it visually clear that progress is accelerating. Evolution always stands on the shoulders of giants, working not to improve things linearly, but exponentially. When sexual reproduction emerged, it built on top of billions of years of asexual evolution. It took advantage of the fact that we had a set of robust genes. Now those genes could be quickly reshuffled to rapidly experiment and adapt on a time scale several orders of magnitude shorter than it would take asexual reproduction to perform the same adaptations. Then neurons emerged; now adaptation was on the order of fractions of a life time rather than generations. Then consciousness emerged. Now not only can humans adapt on the order of _days_, we can also augment our own intelligence. Modern day humans have access to the internet augmentation, giving us the collective knowledge of all humanity in _seconds_. While we can augment our intelligence, the thing we can't do is intelligently modify our own hardware. This is where AI comes in. With a sufficiently intelligent AI we could task it to do AI research for us. Etc, etc. => Singularity. The vast majority of the steps towards Singularity have _already_ happened! Every step is an exponential leap in "intelligence", and it causes adaptions to occur on exponentially decreasing time scales. But I guess we'll see for sure soon. GPT-human is a mere 20 years away (or less). I don't personally think the AI revolution will be as dramatic as many envision it to be. It's more likely to be like the emergence of cell phones. Cell phones undeniably changed and advanced the world, but it's not like there was a single moment when they suddenly popped into existence and then from that point on everything was different. It's hard to even point to exactly when cell phones changed the world. Was it when they were invented? Was it when they shrunk to the size of a handheld blender? When we had them in cars? The first flip phone? The first iPhone? The first Android? The rise of AI won't be a cataclysmic event where SkyNet just poofs into existence and wipes out humanity. It'll be a slow, steady gradient of AI getting better and better, taking over more and more tasks. At the same time humanity will adapt and integrate with our new tool. When the AI gets smarter than us and hits the Singularity treadmill, we won't just poof out of existence. More likely humanity, as a civilization, will just get absorbed and extended by our AI counterparts. They'll carry the torch of humanity forward. They'll _be_ humanity. Our fleshy counterparts won't be wiped out; they'll be an obsolete relic of humanity's past. More concretely, in 20 years we'll have GPT-human, not as an independent, conscious, thinking machine. It'll be a human level intelligence, but one bounded by the confines of the API calls we use to drive its process. That's not something that's going to "wake up" and wipe us out. It's something we can unleash on our most demanding scientific tasks. Protein folding, gene editing, physics, the development of quantum computing. All being absolutely CRUSHED by an AI with the thinking power of Einstein, but no consciousness or the cruft of driving a biological body. It's easy to see how that will change the world, but won't immediately lead to humanity being replaced by free-willed AIs.
- SubiculumCode 6y agoI do wonder how far the human brain is from theoretical optimums. There is obviously something working really well, but there is also a lot of baggage that I do not doubt limits performance in some domains (cognitive) in order to preserve other basic functions (fight or flight or f*k). The biggest opponent to progress is ourselves. Even if you came up with an implant that would make humans smarter and more moral/ethical, people won't adopt it readily for fear of change. Unless AI becomes attached conservationist in nature, I'm not sure they'd retain the baggage not optimal for modern environments.
- nradov 6y agoThere is some evidence to indicate that higher intelligence is correlated with mental illness. When people get too smart they tend to be mentally defective in other ways. I wouldn't be surprised if AGI runs into the same limits.
- Isinlor 6y agoBTW - We empirically do not need AGI for computational/intelligence explosion. Single virus has no chance of out computing and evading an immune system, but billions of billions of viruses can out compute and evade even human civilization as a whole.
- pygy_ 6y agoMaybe not outsmart or outcompute, but outpower (unless you count any biological activity as computation). Viruses have nano-level biological leverage and that's enough to wreak havoc. The threat I'm most worried about is automated capitalism which is gradually gaining power (and intelligence, and psychological leverage) while folks are on a descending slope.
- Isinlor 6y agoBiological viruses are relatively simple programs ~30kb that optimize themselves. mRNA vaccines are also programs that run on biological cell hardware of our bodies.
- dan-robertson 6y agoI find the complexity arguments convincing despite the fact that they have various weaknesses (that while a solution to some NP-hard problem would suffice, it isn’t necessary and a merely good solution or a solution to an easier subset of problems would be ok.) There’s two things to talk about: 1. The article seems to switch a bit between superhuman intelligence or performance at something (I find this reasonably plausible) and a runaway singularity where intelligence/performance grows exponentially and the computer then moves to destroy us all. A few reasons I find the latter proposition implausible are that only one problem of many needs to be too hard for complexity to be an issue; it’s not clear how good exponentially better performance is (for something like image recognition, how much does it matter to be able to recognise lots more things, or to have a 1% error rate that halves every year? I say not that much,) indeed it seems that evolution isn’t particularly optimising for intelligence in humans despite how much some of us may think it matters, although that could just be due to it not mattering so much until recently; and that it often relies on imagining an intelligence which is somehow clever in the way that humans and computers are clever (eg also fast at big mathematical calculations), but also stupid in the ways computers can be stupid, being precisely logical and optimising for a single goal (I find it unbelievable that the all-consuming paperclip-making intelligence would perfectly follow its paperclip-making instruction while destroying its masters and never thinking to disobey.) 2. I feel like most people who are serious believers in a singularity (eg Yudkowsky et al) are massive cranks who’ve reasoned themselves into a weird sci-fi corner. I struggle to believe that an argument from them is grounded in reality rather than begging their prophecy of a singularity future.
- Inufu 6y agoThe author keeps referring to the "PSPACE" complexity of chess and Go in the context of AlphaGo; this is incorrect - these games are only PSPACE for arbitrary large board size N, at fixed board size as actually used by humans and current AI they are just constant O(1), complexity class is not relevant for this. The article was also written before the best evidence we currently have for this was published: scaling laws for natural language understanding (https://arxiv.org/abs/2001.08361 https://arxiv.org/abs/2001.08361), performance of RL algorithms with respect to data (eg AlphaGo Elo vs training time), image model accuracies, etc all show that exponentially increasing amounts of data/computation are required for linear improvements in performance. I posted some graphs with more details here: http://www.furidamu.org/blog/2020/05/03/the-case-against-the-singularity/ http://www.furidamu.org/blog/2020/05/03/the-case-against-the... tl;dr: current evidence suggests AI performance scales with log of data or computation