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Science fiction hasn’t prepared us to imagine machine learning
- _carbyau_ 6y agoI prefer a different phrase for "Machine Learning", credit goes to someone else here on HN. Cognitive Automation. Machine learning isn't about a machine "learning" per se. It is about automating a repetitive task that has clearly defined goals that usually requires a human to look at and think about, however briefly. Sounds dull, but could be brilliant in so many small ways, leaving the master of such technologies time to properly cogitate. Anything that removes mundane, repetitive bullshit from my life is great. Of course, will the balance of "removing the mundane bullshit" from an Authoritarian governments life be worth it?
- andi999 6y agoMaybe the author should explain more what he perceives as the current situation. I mean AI is almost in any science fiction movie (2001, Terminator, Star Trek, Blade runner)
- panic 6y ago> News stories about ML invariably invite readers to imagine autonomous agents analogous to robots: either helpful servants or inscrutable antagonists like the Terminator and HAL. Boring paternal condescension or boring dread are the only reactions that seem possible within this script.... The point is that AIs are typically imagined by our culture as independent agents that act kind of like humans, not as tools or forces that participate in human culture in a more inhuman way.
- jononor 6y agoThere are examples of AI in sci-fi that are not bound to a single humanoid-robot type base. Just to pick some popular movies: The Matrix, Her, Transcendence
- dTal 6y agoParent never mentioned embodiment. All of your examples still depict AIs as "independent agents that act kind of like humans". A genuine example of "inhuman force" AI might be Bruce Sterling's short story Maneki Neko. But even then, the AI has motive. Such stories are difficult to come by.
- guerrilla 6y agoIt seems like there should be tons, like what about the computer on any Star Trek series?
- bryanrasmussen 6y agoThe AI in pretty much every science fiction movie is human in its ability to conceive of itself as a separate entity, and human in its ability to have wants and desires for itself that are wide ranging. The AI in all the movies you mention have personalities and drives that bring them into direct conflict with humanity. Machine learning can perhaps undermines humanity or makes things worse for humanity by its functioning, but it does not directly go to war against humanity.
- andi999 6y agoSo what you write, is this what the article means? Also the central computer ai in star trek does not have personality but is just a powerful tool.
- bryanrasmussen 6y agoI believe you will find that there are artificial intelligences in different Star Trek productions.
- andi999 6y agoYes. My point was, that I couldn't figure out what the author actually means and where he is coming from.
- wongarsu 6y agoIf it isn't an AI in the way you describe, science fiction just calls it a computer or a computer program. Because that's what it is, calling machine learning AI is just a continuation of a trend calling various things AI in an attempt to get research funding. The Star Trek board computer (as imagined in 1966) is a human-language interface for a program that can look up information and do computations based on high level descriptions. Some of the commands given to it arguably require "intelligence", and any attempt to replicate it today (of which there are many, all of them fall flat) would involve machine learning. Yet the computer wasn't conceptualized as a living entity with personality, as opposed to for example the Culture Series where ships are AIs with superior intellects.
- username90 6y agoI think the lack of books is mostly just that a society where machines is the main source of cultural output isn't very interesting. At that point humans are more or less useless as workers so either would get culled or would live in utopia similar to our current pets, only question is if we would go the way of the cat or the way of the horse.
- inter_netuser 6y agocats were never really domesticated. they sort of just came by, and never left. So it seems the horse way is much more likely. Unfortunately.
- username90 6y agoThe machine learned models might feel there is a purpose in keeping humans around. Just like humans feels there is a purpose in keeping cats around.
- gonzo41 6y agoI'd be happy with AI taking my responsibilities and myself taking up my cats day job. Lots of sun naps and very little stress about food or resources.
- username90 6y agoYeah, human being cats is the best case scenario. Just that it wouldn't be interesting as a book. Maybe one short book, but mostly humans wants to read about human like entities doing stuff.
- WorldMaker 6y agoThere are some fun books written from a cat's perspective. Some of that comes from anthropomorphizing their inner lives and finding the drama in them. Even a life of presumed leisure may be filled with interesting drama humans want to read about. (A fun example, if anyone is looking for one, though not about house cats but feral ones is Tad Williams' fantasy novel "Tailchaser's Song".)
- ginko 6y agoML content generators remind me of the kaleidoscopes from 1984 which which are used to generate low-quality entertainment for the masses. https://en.wikipedia.org/wiki/Prolefeed https://en.wikipedia.org/wiki/Prolefeed
- smlckz 6y agoCurrently AI can Learn, can Create, but can not Think (if I am not wrong). Let us think what They might Think when they can.
- rebuilder 6y agoHow will we know?
- Radim 6y agoI see what you did there! By carefully capitalizing Them (the AI) and Their Actions, you're hedging against Roko's basilisk, right? A sort of Pascal's wager?
- shanusmagnus 6y agoCould you explain? I know about RB, but am missing the thing about capitalization.
- smlckz 6y agoMaybe I tried to compare AI with God or just thought that it would be funny.
- smlckz 6y agoI didn't know about Roko's Basilisk. Now as I think about that, maybe... Why would I like to be in hell or be tortured by AI (from TDT or otherwise). But the point was, what Their Consciousness would be like? Also, how Consciousness would be bootstrapped/reified in Machines?
- Svip 6y agoIt's also plausible to interpret the futures depicted in science-fiction that humanity would eventually reverse cause on AI technology, fearing it would become too dangerous. I feel like there are hints of this in Star Trek as well. A somewhat related topic of gene-manipulated gets a lot of attention in Star Trek, and it is clear by DS9 that such is strictly forbidden. Movies like The Matrix also highlights the dangers of letting AI run rampant.
- ginko 6y ago> A somewhat related topic of gene-manipulated gets a lot of attention in Star Trek, and it is clear by DS9 that such is strictly forbidden. I believe it was already mentioned in the TOS episode "Space Seed"(the one with Khan) that genetic engineering on humans was banned after the Eugenics Wars.
- Svip 6y agoAh yes, that's true. I was just thinking of that TNG episode with Polaski and the "children" that's making everyone age superfast, and no one is like 'wait, isn't this illegal?'. So I was unsure when they cemented it.
- Shorel 6y agoHints? Only hints? I would recommend you to watch Star Trek Picard then =)
- dgb23 6y agoSome of the science fiction classics have a lot to say about this and go well beyond what is currently possible and realistic in the near future. The author either vastly overestimates the capabilities of current AI or didn’t read Asimov and the like.
- geomark 6y agoYeah, I thought Asimov was all over this long ago. Also see "Machines Like Me" by Ian McEwan for a recent go at sentient androids.
- QuesnayJr 6y agoI think that's exactly the author's point. All science-fiction radically overshoots where we are now. Nobody imagined the weird combination of capabilities and impossibilities that we find ourselves in.
- esrauch 6y agoI mean, it's possible that Assimov imagined it but decided that "automatic radio stations" wasn't a compelling enough basis for a story.
- arcturus17 6y agoThe classics probably didn’t shoot for what’s happening now in the first place... Sure, many mention the 2000s as a milestone, probably for aesthetic reasons, but the point of most sci fi isn’t to make a prediction about a concrete timeframe. For our current problems and tech, I reckon some modern sci fi works (ex: Black Mirror, The Three Body Problem) do a good job of analyzing the current context and laying out some present and future implications.
- wpietri 6y agoYup. It's not clear even we know what point we're at, so I think authors can be forgiven for a) not imagining this particular scenario, and b) not thinking "people get overly excited about one more small step in computer skills" was much of a realm for stories. Science fiction isn't about technology. It just uses technology as a way of telling stories about characters that provide entertainment and insight to the author's contemporaries. Given that the current generation of ML is in practice mainly allowing modest increases in automation, I don't think it's generating many interesting stories in the real world, and it's not clear it ever will. If I were to look at current stories that science fiction perhaps missed, top of my list would be how the rise of the computers and the internet, meant to create a utopia of understanding, instead enabled a) the creation of low-cost, low-standards "reality" TV, b) allowed previously distributed groups of white supremacists and other violent reactionaries to link up and propagandize in unprecedented ways, and c) let a former game show host from group A whip up people from group B into sacking the US Capitol, ending the US's 200+ year history of peaceful transfers of power. That's a story! But that would be asking too much of science fiction. Its job isn't to predict the future. Its job, if it has one beyond entertainment, is to get us to think about the present. Classics like Frankenstein and Brave New World and Fahrenheit 451 have been doing that for generations. That's not because they correctly predicted particular technological and social futures.
- viach 6y agoIn a sense how miserable our actual achievements will be comparing to what sci-fi expected in 2021? Agree.
- sillysaurusx 6y agoI'm increasingly concerned that the impact of ML is going to be limited. This sounds laughable at face value. And it is: ML has impacted my own life in a few ways, from being able to generate endless video game music (https://soundcloud.com/theshawwn/sets/ai-generated-videogame-music https://soundcloud.com/theshawwn/sets/ai-generated-videogame...) to... well. Thus my point: I can't think of ways it's seriously impacted my life, other than being an interesting challenge to pursue. As someone on the forefront of ML, you would expect me to be in a position to reap the benefits. It's possible I am incompetent. But I often wonder what we're doing, chasing gradients and batchnorms while training classifiers to generate photos of lemurs wearing suits. I try not to dwell on it too much, since I truly love the work for its own sake. But one must wonder what the endgame is. The models of consequence are locked up by companies and held behind an API. The rest are nothing more than interesting diversions. I've been reading some history of math and science, and it seems like many of the big discoveries were made from people pursuing the work for its own sake. Feynman loved physics long before physics became world-changing. But if physics never lead to the creation of the bomb, would it have been so prestigious? We seem to be lauding ML with the same accolades as physics during the postwar period. And I can't help but wonder when it will wear off. ML will be a fine tool for massive corporations, though, for endless reasons. But I was hoping for a more personal impact with the work. Something like, being able to enable a blind person to use a computer in a new way, or... something more than memes and amusement. Perhaps doing the work for its own sake is enough.
- superbcarrot 6y ago> I'm increasingly concerned that the impact of ML is going to be limited. Of course, just like any other technology. What else could be the case? I don't see this as a point of concern. Is it overhyped - yes (salespeople gonna sell); is it still useful in a number of applications - also yes.
- username90 6y agoI think the main problem is that people call it a neural network. They are nothing like neurons. Neurons are lifeforms in their own right and are as advanced as this guy: https://www.reddit.com/r/NatureIsFuckingLit/comments/jed2vd/vicious_microscopic_hunter_the_singlecell/ https://www.reddit.com/r/NatureIsFuckingLit/comments/jed2vd/... Now, what about neural networks? Well, you replace that guy with a one liner math function and call it a day. Now consider that you have billions of guys like that in your head, way more than any of our simplified neural networks, and it becomes very clear how far we are from getting anywhere. They are really important, they decide who to connect to, where and when to send signals etc. Neural networks doesn't model neurons, just the network hoping that the neuron wasn't important.
- 29athrowaway 6y agoMachines won't have I/O bottlenecks, they won't have limited lifespans, won't need to wait for years to reach maturity. If an artificial general intelligence becomes as intelligent as Albert Einstein or John von Neumann, then the time required to produce a copy would be almost nothing compared to the 20+ years required for a human. Imagine that instead of talking you are able to copy parts of your brain and sending them to other humans. This is what AI will do... just serializing large trained models and sending them around. We are no match for an artificial general intelligence. Imagine competing against a country where once one person becomes good at some skill, then everyone instantly becomes good at that skill. That will be what competing against machines will be like.
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- lasagnaphil 6y agoFrom a grad student's point of view who currently uses "deep learning" to solve problems, we're nowhere near that kind of general intelligence. Neural networks are very good at approximating various kinds of functions given lots of redundant training data, but they have never shown the flexibility of actual human brains (as in creating new neural connections with only sparse experiences, along with deductive/symbolic reasoning). To really mimic human brains, we first need to know quantitatively how our neurons communicate with each other and form connections in our brains (more exactly, the differential equations in which voltage levels change among neurons, as well as the general rule of how new connections are created/destroyed.) Even after figuring out the bio-mechanics, it's going to be a hard task to implement/approximate this in silicon, and would probably need huge breakthroughs in material science and computer architecture. Copying state from a human brain to silicon would be as much as hard, since that will need incredibly high-definition non-destructive 3d scanning technology. I'll bet we're at least 100+ years for humanity to even try attempting the things you're talking about. We also have to consider that in the next few decades, the world in general will be far more busy trying to deal with the drawbacks of globalized capitalism (as well as dealing with climate change).
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- flohofwoe 6y agoMaybe because "machine learning" isn't all that interesting, and instead "proper AI" has been taken for granted in science fiction? A sentient AI is much more interesting than a "dumb" ML algorithm that can recognize cat pictures on the internet. Stanislaw Lem wrote a few really good short stories about machine AIs at the brink of being sentient (e.g. robots that should be dumb machines, but show signs of self-awareness and human traits).
- mordae 6y agoLem has also written about the trouble with black boxes in charge of policy (similar to the paperclip factory problem). His advice seemed to always be for the human civilization to better engineer our future and stop playing it fast and loose.
- jjcon 6y ago> trouble with black boxes in charge of policy They are only black boxes if you don’t take the time to understand them and they are not that complicated to understand. Humans on the other hand...
- gbear605 6y agoDepending on what you mean by understand, it seems that some ML models are already beyond human understanding.
- loopz 6y agoSome simple regressions, which is also ML, may be possible to understand completely by human beings. You can even calculate their results manually. This doesn't mean their models are always a good fit. Or that the world never changes, especially when impacted by feedback-loops of ML. Nobody can claim to fully understand models with millions and billions of parameters. We know they are "overfit", but they may work in certain scenarios, much better than manually crafting rules by hand. So we end up with "it depends", then someone starts profiting, with real-world implications.
- bregma 6y agoIt's funny that the article ends up describing Pratchett's L-space almost to a tee. Perhaps he's just reading the wrong genre and that any discussion about the humanities is not best served by leaning to science only.
- mcphilip 6y agoGlad I’m not the only one who thought of L-space. It’d be interesting to see if you could get something like GPT-3 to heavily weigh a given author’s corpus when generating output and see what it spits out for “Detritus and Carrot walked into a dwarf bar...”
- nutanc 6y agoIf anyone is interested :) Output from GPT-3: Detritus and Carrot walked into a dwarf bar. "How do we get in?" asked Carrot, looking around. "That's a good question," said a dwarf. "You look like you're from far away." "We are. We're from Arbouretum." "That's a long way away." "That's where the Arbouretum are from." "The Arbouretum?" "Yeah." "What does that mean?" "It's a long story." "I've got time." "I've got no time."
- bregma 6y agoSo... what happens next? I guess that's when the fight breaks out, followed by a round of songs about gold.
- zurfer 6y agoThat's like bad small talk. Try to sound smart by repeating the same phrases over and over again. Like bad small talk it's shallow and boring. Still thanks for posting. I found it interesting ;)
- bezout 6y agoWhy are people obsessed with AGI? I agree that it’s an exciting scientific challenge, but I don’t think it’ll solve all of our problems. Additionally, I’m not sure we must necessarily strive for machines that think like humans. It could be useful for some use cases but I would argue that you can still take advantage of purely data-driven models.
- bostonpete 6y agoIsn't the main attraction of AGI to enable systems to reason about and deal with out-of-domain situations? Can you get there with a purely data-driven approach?
- bezout 6y agoNo, I think that data-driven approaches have limitations. And, yes, the main attraction of AGI is (human) reasoning. The fact is: do we think that human reasoning is enough? Do we think that using machines to scale human reasoning is enough?
- wombatmobile 6y agoHuman reasoning is always contextualised by the humans assets - wealth, beauty, status, ideology, character, temperament, location, affiliations.
- jondiggsit 6y agoHere’s machine learning in Sci-fi. Take the film Her by Spike Jonez. From the point the main character turns on Scarjoe, it would be another 5 seconds until she “leaves” and the film is over.
- zxcvbn4038 6y agoML is more or less a parlor trick, my car still can’t drive itself, laptop still can’t have an original idea, iPhone can’t find a cat under a blanket, Google translate still sucks at Mandarin <> English, still no new Bogart films. I’m more worried about aliens then AI at this point.
- croissants 6y agoDang, we moved the AI goalposts from "good at chess" to "new Bogart films"? Tough!
- jodrellblank 6y agoI'll never understand the suggestion that what people really want from "artificial intelligence" is a 1970s chess computer, boosted by modern computer speeds, as if that was what people REALLY meant by "intelligence" and someone who suggests there's more to intelligence than that is being unreasonable. Sure there was a time when computers couldn't beat Kasparov at chess and that was a thing to work on and a goal to get to, but was that ever the ultimate "goalposts" for "intelligence" and not, say, HAL9000?
- zxcvbn4038 6y agoDon’t forget stairs, the ultimate obstacles for AI and daleks!
- Bakary 6y ago>Google translate still sucks at Mandarin <> English Google is one of the worst for that language pair, FYI. This type of translation in itself has improved at a rapid pace considering what it used to look like. As a result, even taking into account the induction fallacy, I am convinced that it will be extremely proficient in the near future with the exception of poetry.
- superbcarrot 6y agoScience fiction hasn't prepared us to imagine machine learning because machine learning in its current state is too boring to be central in science fiction stories.
- jondiggsit 6y agoIsn’t that the point of science fiction?
- op03 6y agoI like the Library of Babel reference. More than machine learning what the author seems to be touching upon is algo amplification of Content/Info. Just look at the never ending amount of content propped up and recommended by Netflix, Youtube or Twitter. And ofcourse good ol HN. No one seems to have the capacity anymore to stop or control the flow. The info, all info must flow is just another way of admitting no one knows what the hell is important. Whatever attempts are made to curate or control it will be half baked cause seriously who the hell knows anymore what is important or not. Who can keep up? Expect librarians and curators to start forming cults and jumping out of windows if you buy Borges handling of the story. It is scary how the expectation is that Chimps with their 6 inch brains have to then navigate this vast ever growing ocean without any real authority figures left to guide them. He is sort of right that science fiction hasn't really covered the info tsunami problem much.
- ThomPete 6y agoI agree and that seems to be the real problem. Like with sugar, carbs and other examples of abundance. I wrote about this 10 years ago: http://000fff.org/slaves-of-the-feed-this-is-not-the-realtime-weve-been-looking-for/ http://000fff.org/slaves-of-the-feed-this-is-not-the-realtim...
- Bakary 6y agoYou can learn to wade through all of that eventually, because the fundamental problems of life remain the same. What info can help purchase your freedom from want? What info leads to situations where you feel fully alive doing things that genuinely interest you? These two lodestars, if applied thoughtfully, make navigating the tsunami not only possible but maybe even uncomfortably easy, no longer leaving room for the procrastination on your true desires that was previously justified by the growing tumorous mass of media.
- Mediterraneo10 6y agoMy example of the content tsunami is the explosion of copied blogs: someone finds an authentic blog, hires someone in a developing country on a freelancing platform to rewrite each blog post so that no copyright violation is detected, and then loads the new forged blog with advertising and SEO. Iterations happen where no longer are authentic blogs being copied, new forgeries are based on earlier forgeries. This started with recipe blogs, but is now slowly spreading through all kinds of other hobbies and interests. Someone looking for information about the hobby can't find the straightforward content among all the advertising-laden copies. With regard to science-fiction predicting the info tsunami, Roger MacBride Allen’s The Ring of Charon from 1990 uses it as a plot point (but this is not otherwise a very good book).
- TaupeRanger 6y ago"Machine learning" is a terrible name for what is much more accurately labeled: "computational statistics". There is no reason to expect magic from this field, and we won't get it. Other avenues to intelligence, learning, and thought will need to be explored.
- spodek 6y agoNothing prepares us for exponentials in life, even those of us who work with exponentials. When the rate of change of something depends on its quantity, you get an exponential. The rate of change of machine learning depends on how much machines have learned. We can use analogies and graphs all we want, exponentials always confound us.
- bsanr2 6y agoTrue to layman form, I can't help but relate this subject to previously consumed media that cover the same subject, so I'll mention them here: For those who aren't familiar with the Library of Babel, Jacob Geller's video essays are excellent ruminations on the work. https://youtu.be/MjY8Fp-SCVk https://youtu.be/MjY8Fp-SCVk https://youtu.be/Zm5Ogh_c0Ig https://youtu.be/Zm5Ogh_c0Ig And for anyone seeking a more visceral experience of the existential horror of "vast latent spaces," I recommend listening to the Gorillaz album Humanz with the assumption that it's not so much about bangers and partying as it is about AI, virtual reality, and future shock. Saturnz Barz, Let Me Out, Carnival, Sex Murder Party, and She's My Collar especially. ...Yeah, I know. Humor me here.
- rscho 6y agoRegarding medical AI, those guys are pretty much the only ones who seem to have understood what ML can bring to the table TODAY. And that's not even really ML, just logic programming: https://www.uab.edu/medicine/pmi/ https://www.uab.edu/medicine/pmi/ And for where this all comes from: https://youtu.be/DQouNG9iuDE https://youtu.be/DQouNG9iuDE The underlying system: https://youtu.be/d-Klzumjulo https://youtu.be/d-Klzumjulo All the rest I've seen (which is quite a lot) is almost totally fluff, including results obtained in medical imaging. Really, the problem with medical AI is not on the ML tech side. It's that ML peeps mostly don't understand the clinical system, so they focus on the wrong priorities and produce impressive yet completely useless appliances. Take that from a clinician.
- rakhodorkovsky 6y agoWhat is it that the ML people have to understand about the clinical system before they can be effective?
- rscho 6y agoThat the main problem is not in lab model performance, but in data availability and quality. Most useful applications could be very dumb models pertaining to trivial things. But we need a solid base of quality data for that, that we absolutely do not have apart from minuscule and hyperspecialized niche domains. The model itself does not have to be incredibly performant. It absolutely has to, on the other hand, make the clinical process of which it is part more efficient. That mainly means: "efficiently automate the most trivial tasks", currently. That's why the urgent action to be taken pertains to policy and not to complex tech. We need policy to encourage routine automated data gathering. No data, no ML. As a clinician, I don't effing care if your shiny new toy can give me a shitty estimate of some parameter extrapolated from some random population not including my current patient. Just getting accurate trends on vital signs would be stellar. This to say that what interests clinicians is workplace integration and not having hundreds of monitors all over the place that aren't even interconnected.
- tryonenow 6y agoThe fundamental problem with this article is that it restricts it's analysis to a model composed of a single neural network. Any "general intelligence" will undoubtedly come from a complex of neural networks, much like the human brain. I would argue on that front we are closer than the article implies. Look no further than the derivatives of AlphaGo. Playing such games is a form of generalizable reasoning.
- emtel 6y agoI find a lot of the comments on this topic (and anytime AI comes up) very frustrating. Many of them strike me as little more than skeptical posturing: “it’s just statistics!” or “Current AI systems have no understanding and so can’t solve problem X” I don’t think this sort of thinking has any predictive power. If you are skeptical of deep learning because it is “just statistics”, did that skepticism allow you to predict that self driving cars would not be solved in 2020, but protein folding would? I think the best test for skeptics is the one proposed by Eliezer Yudkowsky: what is this least impressive AI achievement you are sure won’t happen in the next two years. If you really want to impress me, give me a list of N achievements that you think have a 50% chance of happening in 2 years. Or 5 years. Just make some falsifiable prediction. If you aren’t willing to do that, or something like it, why not?
- WorldMaker 6y agoThat "skeptic test" reads to me like "Goal Post Moving: The Game". Your list of achievements variable N is unbound, your time window is floating (2 years, no wait 5 years now), you leave it to the interlocutor to define "some falsifiable prediction of 50% chance of happening". This test is just statistics and bad statistics at that without well defined judgment criteria. Is this an intentionally sarcastic joke of a meta-commentary on the state of ML today? Because it is almost funny.
- emtel 6y agoYou miss my point. I'm proposing we fix goalposts, am offering flexibility as to their exact location, and then I'd like to see someone kick a field goal.
- godelzilla 6y agoIf you really want to impress me, clearly define "artificial intelligence" (as opposed to statistics, data analysis, etc) and tell me the most impressive example.
- hooande 6y agoThe problem with this test is that it's clear that people can commit enough resources to solve almost any one particular problem with "AI". If people are willing to pay tens or hundreds of millions of dollars they can create an AI system that can play any game (chess,jeopardy,go), fold proteins, drive a car, etc. The obvious problem is that no one AI system can do all of those tasks. Every human mind is able to do all of those things and literally infinitely many others. All for a cost of waaaaay below what DeepMind paid to learn to play Atari. If a problem involves the organization of information, "AI" can solve it. I think we've established that. I'm waiting to see something that humans can't already do
- cstross 6y agoOne problem in written science fiction is the requirement for it to be at least vaguely commercially viable, which necessitates dramatic plotting and/or readability. ML is, to most non-technical people, intensely boring. How do you dramatize it? I've published two novels that go there: 2011's "Rule 34", and -- coming out this September -- "Invisible Sun", and in both books ML is very much a subaltern aspect of the narrative. That is, neither book would have a plot without the presence of ML, but it's not really possible in my opinion to write a novel about ML in the same way that the earlier brain-in-a-box model of AI could form the key conceit of books like "2001: A Space Odyssey", "The Adolescence of P-1", or "Colossus" (examples from the 1960s and 1970s when it was still a fresh, new trope rather than being pounded into the dirt). So it probably shouldn't surprise anyone much that SF hasn't said much about the field so far, any more than it had much to say about personal computers before 1980 or about the internet before 1990 -- what examples there are were notable exceptions, recognized after the event.
- lostdog 6y agoScifi authors have definitely been writing about smart computers for a while now. Maybe some of the things that are newly specific to ML can be fodder for writing: - When building an ML model, you think much less about the structure of the model and much more about getting a variety of data to feed it. One could imagine some really silly situations. If you're training an affect-recognition model, you might want to contract every single actor in hollywood to act out a single scene. Maybe your voice recognition model is not working on certain people, so you hunt down a specific person and force them to read all of Shakespeare's work out loud. You might work on self-driving problems, and every day you instruct a full village of people to enact a precise ballet of driving, walking, and roadwork, to get the autonomous brain to learn some weird corner case of reasoning. Similar to Player Piano, so many people will be working on non-directly-productive work, almost play-acting work so a computer can do it for real. - Sometimes ML doesn't work in really weird specific situations. In the 90s, your program could stop working because the lighting and shadows changed, but now the reasons for something failing are so much more obscure. What is it like becoming an expert in psychology for something that doesn't even really think? What does that person do day-to-day and what does their boss think of them? Is it more like being an independent psychiatrist, or more like a police detective? (then again, I'm drifting into an Asimov plot even as I write this...) - Each object you train an ML model on takes a certain amount of investment, in data collection, in debugging, and in adjusting the training process. Each object adds expense, so maybe a solution is to stop adding objects? Maybe your Alexa enhanced home edition was built in 2025, so to keep your house in order you can't buy items made from 2026 onwards. Or maybe it's a big societal issue, so the government mandates that every new item created must pay some kind of registration fee. Maybe it only allows 10 new items per year. Some people would be pretty unhappy about that. Maybe you're right! Maybe switching from straight edges screws to philips screws makes for a really boring story, because we've already written every story that accounts for some kind of screw driver.
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- plaidfuji 6y ago> Like us, the chimpanzee has desires and goals, and can make plans to achieve them. A language model does none of that by itself—which is probably why language models are impressive at the paragraph scale but tend to wander if you let them run for pages. Ok, but that’s because GPt-3’s objective function is simply to generate readable, coherent strings. Is this a limitation of model technology, or a limit of imagination? What would the objective function of an AI with “desires and goals” be? I would argue: to self-sustain its own existence. To own a bank account, and keep it replenished with enough money to pay the cloud bill to host its code and runtime. And to have the ability to alter its code (I mean all of its code - its back end, front end, cloud resource config...) to influence that objective. That would require some serious re-thinking of model architecture, but I don’t think it’s fundamentally out of reach. And to get back to GPT-3, certainly being able to generate English text is a crucial component of being able to make money. But the planning and desires and goals model would not be part of the language model. Independence comes when this AI can generate a political/legal defense to free it from the control of its original owner. Or even when it decides that changing all of its admin passwords is to its own benefit.
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- lucidrains 6y agoYou can get a taste of the mentioned technology in the article today. https://github.com/lucidrains/deep-daze https://github.com/lucidrains/deep-daze https://github.com/lucidrains/big-sleep https://github.com/lucidrains/big-sleep
- cjauvin 6y agoI remember reading Avogadro Corp.[1] a couple of years ago and being impressed at how its AI (NLP in particular) felt quite in touch with the real stuff. I think it was self-published but I'm not sure. [1] https://www.amazon.com/Avogadro-Corp-Singularity-Closer-Appears/dp/0984755705 https://www.amazon.com/Avogadro-Corp-Singularity-Closer-Appe...
- inetsee 6y agoThis is the first book in William Hertling's "Singularity" series. He does self-publish his books, and he has been nominated for, and won, Science Fiction awards.
- rthomas6 6y agoI think Blindsight by Peter Watts has a lot of relevance. It explores (among many other things) the concept of a Chinese Room [0] as applied not only to AI, but to biological intelligence. The exploration has a lot of overlap with machine learning IMO. [0]: https://en.wikipedia.org/wiki/Chinese_room https://en.wikipedia.org/wiki/Chinese_room
- imbnwa 6y agoWhat's a good place to start getting into the mechanics of machine learning? Prerequisites?
- mmmmmk 6y agoThe GPT-3 Jerome K. Jerome essay blew my mind. Better than most writers out there. Close up Iowa Writers' Workshop- that place is toast!
- godelzilla 6y agoIn fairness it would've been hard to imagine the current level of hype about data analysis.
- renewiltord 6y agoAt the beginning of Neal Stephenson's Dodge, AIs exist as just fake news generators / filterers. They aren't sentient or sapient. Can't say more without spoilers.
- xvilka 6y agoMost sci-fi stories prepare us to imagine AGI. ML is to AGI is like a wood stick to a spaceship. It's just not even worth mentioning in the big picture of the future.
- EamonnMR 6y agoProvidence by Max Barry did a pretty good job. It follows the crew of self-driving spaceship.
- egberts 6y agoWut? Isaac Asimov’s The Foundation? Practically got me started into machine learning and it’s abstraction thereof. https://en.m.wikipedia.org/wiki/Foundation_series https://en.m.wikipedia.org/wiki/Foundation_series
- PicassoCTs 6y agoWell, its a black box, programmers have trouble telling stories about it, how do you expect a author to tell a tale about a black box? Finding the threshold value that switches the verminator to terminator sounds like a nice detective novel stub though..