[HN Gopher] Science fiction hasn't prepared us to imagine machin...
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Science fiction hasn't prepared us to imagine machine learning
Author : polm23
Score : 180 points
Date : 2021-02-07 12:21 UTC (10 hours ago)
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| emtel wrote:
| I 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?
| godelzilla wrote:
| If 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 wrote:
| The 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
| andi999 wrote:
| Maybe 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 wrote:
| _> 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 wrote:
| There 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 wrote:
| Parent 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 wrote:
| It seems like there should be tons, like what about the
| computer on any Star Trek series?
| bryanrasmussen wrote:
| The 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.
| wongarsu wrote:
| If 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.
| wruza wrote:
| AI is not always humanlike, and when it is, it's because it
| is a good fit for servitude. I remember a story of a planet
| with small tetrahedron bots that formed protective clouds to
| destroy electrically active organisms. T-series were
| humanlike for a reason, other bots were not. Starships often
| have AI that is not even a person. Social fiction is just the
| most popular, because it is the same old drama, but with
| robots.
| andi999 wrote:
| So 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 wrote:
| I believe you will find that there are artificial
| intelligences in different Star Trek productions.
| andi999 wrote:
| Yes. My point was, that I couldn't figure out what the
| author actually means and where he is coming from.
| username90 wrote:
| I 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 wrote:
| cats 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 wrote:
| The 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 wrote:
| I'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 wrote:
| Yeah, 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.
| furstenheim wrote:
| There are such stories. Roald dahl has a very nice short story
| about it https://www.roalddahlfans.com/dahls-work/short-
| stories/the-g....
| n4r9 wrote:
| At the risk of bringing up The Culture series in every HN
| thread about sci fi, Iain M Banks does a thoughtful job of
| exploring this. In particular, in the book Look to Windward
| there's a discussion between the orbital's AI Mind and a
| renowned composer about how it could mimic their work perfectly
| if it chose to.
| zem wrote:
| jack williamson's "with folded hands" is a quietly horrifying
| look at that, all the more so because it takes all the holy
| grails of sf - unlimited free energy, faster than light travel
| and communication, and strong ai that obeys asimov's three
| laws, and crafts a truly frightening dystopia out of them.
| ginko wrote:
| ML 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
| xvilka wrote:
| Most 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.
| PicassoCTs wrote:
| Well, 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..
| zxcvbn4038 wrote:
| ML 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 wrote:
| Dang, we moved the AI goalposts from "good at chess" to "new
| Bogart films"? Tough!
| zxcvbn4038 wrote:
| Don't forget stairs, the ultimate obstacles for AI and
| daleks!
| Bakary wrote:
| >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.
| smlckz wrote:
| Currently 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 wrote:
| How will we know?
| Radim wrote:
| I 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 wrote:
| Could you explain? I know about RB, but am missing the thing
| about capitalization.
| smlckz wrote:
| Maybe I tried to compare AI with God or just thought that
| it would be funny.
| smlckz wrote:
| I 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?
| spodek wrote:
| Nothing 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.
| superbcarrot wrote:
| Science 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 wrote:
| Isn't that the point of science fiction?
| cstross wrote:
| One 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.
| [deleted]
| m463 wrote:
| That touches on a point about science fiction I've noticed.
|
| _reality_ can be boring. Reality dictates that we travel at a
| fraction of the speed of light. We cannot fix things we did. We
| have a limited lifespan.
|
| Honestly the made-up stuff makes fiction a lot more
| entertaining. Time travel is really fun (though primer required
| a dive into wikipedia to unravel). Warp drives and wormholes
| open the universe to exploration. Living forever might be just
| as fun as time travel - you can fix stuff forward or just see
| it all. I don't mind suspending my disbelief.
|
| EDIT: On the other hand, there might be one real subject that
| is interesting from
|
| https://jsomers.net/i-should-have-loved-biology/
|
| it had a quote:
|
| _Imagine a flashy spaceship lands in your backyard. The door
| opens and you are invited to investigate everything to see what
| you can learn. The technology is clearly millions of years
| beyond what we can make.
|
| This is biology.
|
| - Bert Hubert, "Our Amazing Immune System"_
| Gibbon1 wrote:
| I have long and continuous string of 'jokes' that are about a
| future where common technological items have been replaced by
| some sort of genetically engineered plant, animal or fungus.
| jayd16 wrote:
| I feel like the Running Man is a good example of machine
| learning in sci-fi.
|
| It dug into deep fakes and how they could be used to create a
| massive propaganda machine. I wouldn't call that boring.
| Balgair wrote:
| Hey Mr. Stross, I'm a big fan of your work! Thanks for hanging
| out here on HN with us. I thought _Accelerando_ was superb.
| Keep up the hard work of writing! I know it can be tough, but
| your efforts have really paid off, at least to me.
|
| One question, if you're up for doing any questions: what do you
| think about the use of drones and loitering munitions in the
| recent Azerbaijani-Armenian War of 2020?
|
| Thanks again for all the hard work!
|
| https://en.wikipedia.org/wiki/2020_Nagorno-Karabakh_conflict
| justin66 wrote:
| It's a bit of a tangent, but I got a kick out of hearing Paul
| Krugman make a glowing endorsement of your work last week:
|
| https://www.nytimes.com/2021/02/04/podcasts/ezra-klein-podca...
| bfdm wrote:
| I tend to agree that ML will not itself be the subject, but
| rather a device or tool misused by Someone Bad. As you say,
| it's a necessary and integral piece of the story, but not the
| star.
|
| For example, it brings to mind some combination of Minority
| Report and Eagle Eye, say. Where a surveillance state combined
| with ML analysis leads to something akin to pre-crime arrests
| and the fight back against that.
| akovaski wrote:
| > Where a surveillance state combined with ML analysis leads
| to something akin to pre-crime arrests
|
| While I haven't seen Minority Report or Eagle Eye, this aptly
| describes the anime TV series Psycho-Pass (2012). If I
| remember correctly, the show is mostly focused on the effects
| of having a crime-coefficient system.
| Izkata wrote:
| > I tend to agree that ML will not itself be the subject, but
| rather a device or tool misused by Someone Bad.
|
| I got a counterexample:
|
| _Person of Interest_ [0] was a crime series from 2011-2016
| premised around machine learning. The opening narration from
| each episode of the first season[1]: _You are being watched.
| The government has a secret system, a machine that spies on
| you every hour of every day. I know because, I built it. I
| designed the machine to detect acts of terror but it sees
| everything. Violent crimes involving ordinary people. People
| like you. Crimes the government considered "irrelevant". They
| wouldn't act, so I decided I would. But I needed a partner,
| someone with the skills to intervene. Hunted by the
| authorities, we work in secret. You will never find us. But
| victim or perpetrator, if your number's up, we'll find you._
|
| Revealed in flashbacks over the first season, the government
| doesn't have access to the system. It runs independently
| (even from its creator) and just provides information.
|
| Being TV it does of course expand past the original premise,
| with a reveal that it's not just a machine learning system
| but the world's first true AI, and later another AI with
| conflicting goals is brought online. But for the first season
| at least, the machine sticks to the role described in the
| narration, and appears to be just a machine learning system.
|
| [0]
| https://en.wikipedia.org/wiki/Person_of_Interest_(TV_series)
|
| [1] https://www.youtube.com/watch?v=yBfVndEtDyY
| dllthomas wrote:
| If you haven't _read_ Minority Report, I recommend it.
| DiggyJohnson wrote:
| Do you frequent any forums or sites recommend for the serious
| amateur interested in the production of the sci-fi?
|
| I especially appreciate this discussion. It's fun to think
| about the gaps in our imagination. Especially when it comes to
| science fiction, those gaps are often wider than we think.
|
| Good luck with your work! I'll be on the lookout for Invisible
| Sun, unless you recommend a different title.
|
| Besides ML, do you have any other fururist predictions that are
| not being realized in science fiction?
| superkuh wrote:
| Robert Charles Wilson's "Blind Lake" (2004) is a scifi book
| about a (then) very near future when the data from telescopes
| would be almost as much hallucinated from big data models as
| composed of actual data from measurements. It's plot goes a
| little more quantum handwavy than direct machine learning but
| the gist is the same.
| indymike wrote:
| "ML is, to most non-technical people, intensely boring."
|
| Maybe, or maybe it's just an old trope as you point out. So
| much of science fiction assumes some level of intelligent
| computers and has since the beginning. The phrase "machine
| learning" is really a rebrand of the "thinking machines" of the
| 60s and artifical intelligence" of the 70s and 80s. Even in the
| old Star Trek TV series, you had people talking to the
| computer, not unlike we talk to Alexa, Siri and Hey Google
| today.
|
| That said, now that people are seeing ML affect their lives
| directly, there is a lot of exploration that may be possible,
| as perhaps, ML is just not science fiction anymore.
| notahacker wrote:
| I think the point is we gained the scifi UX, and lost most of
| the interesting plot devices. We got the talking computer
| _without_ enough self awareness or reliability or uniqueness
| compared with other forms of data interrogation to be a
| particularly interesting plot point.
|
| Alexa and Siri and Google Home aren't going to take over the
| world or try to become human, and aren't infallible or even
| particularly smart. They're a speech input interfaces over a
| search engine with some jokes hardcoded in. From a technical
| standpoint, very impressive; from a fiction standpoint a dead
| end
| gradys wrote:
| How do I make sure I hear about Invisible Sun when it comes
| out?
| ideonode wrote:
| It's Charles Stross, one of the leading SF writers of the
| day.
| cstross wrote:
| ... It's also the ninth (and final) book in a long-running
| series, so not the greatest starting point!
| klyrs wrote:
| Hah, Robert Jordan taught me to watch for the phrase
| "[n]th (and final)". No, I won't start on that book, but
| I'll definitely pick up a copy of the first :)
| cstross wrote:
| Hint: I remastered the original six book series in three
| revised omnibus editions circa 2011. (There's then a
| subsequent trilogy, of which "Invisible Sun" is the
| climax.) Anyway, start with "The Bloodline Feud" rather
| than the slim original marketed-as-fantasy six-pack. I
| learned a lot in the decade between writing the first
| books and re-doing them, and the omnibus versions read
| more cleanly.
| EGreg wrote:
| Literally every movie or book that depicts AI in 100-200 years
| would be super boring.
|
| Imagine star trek where instead of Data being one android, you
| just had a ton of machines that could do everything better than
| humans. No point for the humans to explore space or do
| anything. The end.
|
| Imagine in Minority Report where Tom Cruise is instantly caught
| because his whereabouts can easily be tracked and triangulated,
| by his gait, infrared heart signature, smell, and a number of
| other things. Movie takes 2 minutes. The end.
|
| In fact, this is the world we are building for ourselves. We're
| going to be like animals in a zoo, unable to affect nothing.
| Just like a cat has no idea why you're doing 99% of the things
| you do, but has to go along with it, similarly you will have no
| idea why the robot networks do 99% of their activities, you
| just kinda live your life with as much understanding as a cat
| has in your house, as you go about your daily business.
|
| The closest I can think of is Isaac Asimov's "I Robot" maybe.
| And even there, the robots weren't in charge really.
| Izkata wrote:
| > Imagine in Minority Report where Tom Cruise is instantly
| caught because his whereabouts can easily be tracked and
| triangulated, by his gait, infrared heart signature, smell,
| and a number of other things. Movie takes 2 minutes. The end.
|
| Agh, I can't find it now, but there's a short film half based
| on this: A time traveler from the future is identified
| instantly because she's in two places at once. The short has
| both of them in adjacent interrogation rooms, with two
| onlookers - a rookie and an experienced investigator -
| talking about how to identify time travelers. It ends with
| the experienced one commenting that they've been showing up
| more and more often.
|
| _Minority Report_ might not be possible with such
| technology, but it does open different possibilities.
| Malic wrote:
| Do share the name of the short, if it comes to mind later.
| jodrellblank wrote:
| I have a feeling it might be "Plurality" by DUST on
| YouTube, a 15min short film -
| https://www.youtube.com/watch?v=pocEN5HprsM
|
| DUST make a lot of cool sci-fi short films, worth
| checking some of their others too
| https://www.youtube.com/c/watchdust/videos e.g. Bleem,
| the number between 3 and 4, slightly remeniscent of the
| film Pi and the crazy mathematician trope
| https://www.youtube.com/watch?v=qXnFr1d7B9w or Orbit Ever
| After, a love story in a dystopian Brazil style future of
| orbital habitats
| https://www.youtube.com/watch?v=DpFXMIxlgPo
|
| And just because, from another channel a
| https://www.youtube.com/watch?v=vBkBS4O3yvY a short about
| quantum suicide - One-Minute Time Machine | Sploid Short
| Film Festival.
| Izkata wrote:
| Yep, "Plurality" is it - the parts of the interview I'm
| remembering are the explanation at 9 minutes and the
| plane crash at 9:40. Scrolled through their videos
| earlier but the name didn't stick out.
| drdeadringer wrote:
| > ML is, to most non-technical people, intensely boring. How do
| you dramatize it?
|
| To me it's akin to several scenes in the film "War Games" where
| you basically have to make a rogue AI in a computer sexy on
| film.
|
| "Show a computer thinking. Make it scary. Inhuman. Enhance that
| it's impersonal."
|
| So we get a camera person slowly walking around an obelisk-like
| table with ominous music. "This is where the AI lives, thinking
| on how to rain nuclear fire upon the vile Soviets, no humans
| need interfere, enhance and intensify, will Tic-Tac-Toe save us
| from our folly". And around and around the evil obelisk table
| we go watching bits flip up and down back and forth with
| nuclear missiles in question.
|
| You can find similar elsewhere. Dramatic flashing lights on a
| server rack, a human taken over by external forces blindly
| jabbing at a keyboard or keypad with intense purpose. All of a
| sudden from these wonders computational magic happens.
| Geminidog wrote:
| It's even boring to technical people. It reduces intelligence
| to a multidimensional optimization problem. Now intelligence
| just involves all kinds of mechanical ways to fill out the
| weights for a neural network. I use to be more interested. Upon
| learning more about it, I am less motivated.
| mmcnl wrote:
| Technical is quite a broad term. There are quite some
| challenges in designing and engineering large ML data
| pipelines, both from a technical and business perspective.
| But I agree it's a specific problem that is arguably boring
| to a lot of people. Some people take more fun in the
| modelling part, others more in the engineering. Personally,
| I'm more into the engineering part than creating the actual
| model.
| Schiphol wrote:
| > It reduces intelligence to a multidimensional optimization
| problem.
|
| Did you mean to say "... which it is not", or "which it is,
| thus the boringness"?
| Geminidog wrote:
| Let me clarify. I mean "intelligence from the perspective
| of modern ML" is just an optimization problem.
| saeranv wrote:
| I'm sure this is due to my beginner status in ML/DL, but I'm
| really disappointed in how much deep learning seems removed
| from the things that I enjoyed the most in statistical
| learning.
|
| I enjoy the creative challenge of applying domain knowledge
| when building (for example) linear or bayesian regressions.
| In contrast, DL seems like a whole bunch of hyperparameter
| tuning and curve plotting. Curious to see if this assessment
| seems correct from those more experienced...
| cercatrova wrote:
| I've found exactly the same experience. Data science is
| mostly cleaning data in the first place, and the 10% that
| isn't, it's just fiddling knobs (hyperparameter optimization)
| to get the model to work.
|
| But man, I can't argue the incredible results it creates.
| Perhaps that's why people do it, for the ends not the means.
| karmakaze wrote:
| That's the difference between research and application.
| Someone had to first come up with better ways of
| formulating/training models.
| karmakaze wrote:
| That's one way to look at it.
|
| What's described there is the predicting patterns, which is a
| part of intelligence but there's much more to discover and
| invent. Even within the 'optimization' task there's huge
| differences in the leaps from NNs to DNNs and from DNNs to
| AlphaGo/Zero. The details are what make it interesting.
|
| If we were to understand exactly how the brain operates and
| learns, we'd see that it's solved/solving just an
| optimization problem, but that doesn't make it uninteresting.
| gnramires wrote:
| Isn't that like saying, "I used to marvel at nature, that it
| has elements such as fire, water, ice, and amazing living
| things. Then I discovered it is all made of atoms
| interacting... I am now less motivated." ?
|
| I mean, the fire, the water, the ice, the amazeness of life
| and intelligence are still there. You just _gained_ a new
| foundational view. Now you can understand and manipulate
| better what you already knew, maybe now you learned about
| plasma, or even extremely advanced and mysterious phenomena
| like bose-einstein condensates or superfluidity. The old
| wonders are still there, you 've gained new ones.
|
| I'm not going to claim complete cognitive equivalence (or
| even preference) between the two states of mind, but it is a
| bit like childhood: firmly believing in Santa Claus, or
| Wizards or whatever can be exciting, perhaps more exciting
| than knowing they are myths; but growing up and understanding
| they are mythical brings new opportunities, capabilities, and
| even new mysteries you could not reach before (buying and
| building whatever you want, vast amounts of knowledge,
| understanding more about technology and society, etc.). It's
| the adults that keep us alive and well, that make decisions
| for us and for society at large. So perhaps (although I'm not
| entirely convinced by the cumulative argument) truth is a
| sacrifice, but it is one well worth bearing, at least for me.
| I am deeply interested in how intelligence works, in how "the
| sausage is made" (at least for certain highly useful sausages
| that compose the fundamentals of the world).
|
| Even more, understanding is above all a responsibility, if
| not for all of us, at least for some of us, or hopefully in
| one way or another for most of us.
|
| I can't recommend enough Feynman on Beauty: (this argument is
| largely inspired by that)
|
| https://fs.blog/2011/10/richard-feynman-on-beauty/
|
| In the same vein, intelligence to me used to be a black box
| where you got input from the world, some kind of wondrous
| magic happened, and then you got talking kids, scientists,
| artists, and so on. Now I still view it as wondrous, but now
| I understand the fundamental is apparently a network-like
| structure with functional relationships that change, adapt to
| previously seen information in other to explain it, that
| there are a number of interesting phenomena and internal
| structures (going well beyond the simple idea of 'parameter
| tuning') that can be formalized -- essentially the
| architecture of the brain (or better, 'a brain').
|
| To give an example, there have been formalizations of
| Curiosity, i.e. Artificial Curiosity, and I consider it
| essential for an agent interacting independently in the world
| or in a learning environment (part of the larger problem of
| motivation). How amazing is it to formalize and understand
| something so profound and fundamental to our being as
| Curiosity? I felt the same way about Information theory years
| ago. How amazing is it that we've built robots (in virtual
| environments), and _it works_ -- they 're curious and learn
| the environment without external stimulus?
|
| Above considerations aside, I find that _amazing_ ,
| _beautiful_ , _awesome_.
| gnramires wrote:
| There's another related concept I came up with thinking
| about this discussion (which I've had with friends as
| well): 'freedom of utility'.
|
| The basic idea is, forget about what you think is beautiful
| or motivational. Suppose you could _choose_ to be motivated
| by something. Would you choose to be motivated by
| superficial mystery, or by deep knowledge of how things
| are? Should you choose to find beautiful just the surface
| of the flower, or also the wonders of how it works, its
| structure as a system, the connections to evolution and
| theory of color and so on -- all of which could turn out to
| be useful one way or another. If you could choose, would
| you choose to be exclusively motivated by the immediate
| external appearance or by the depth and myriad of
| relationships as well?
|
| Unfortunately, (unlike AI systems we could design) I don't
| think we have complete control of our motivation -- our
| evolutionary biases are strong. But I'm also fairly certain
| much of our aesthetic sense can be shaped by culture and
| rational ideals. If I hadn't heard Feynman, watched so many
| wonderful documentaries (and e.g. Mythbusters) and many
| popularizers of science, perhaps I wouldn't see this beauty
| so much as I do -- and I'm grateful for it, because I want
| to see this beauty, I _want_ to be motivated to learn about
| the world, and to improve it in a way.
| jacquesm wrote:
| Sagan: "The very act of understanding is a celebration of
| joining, merging, even if on a very modest scale, with the
| magnificence of the Cosmos."
| Geminidog wrote:
| > Isn't that like saying, "I used to marvel at nature, that
| it has elements such as fire, water, ice, and amazing
| living things. Then I discovered it is all made of atoms
| interacting... I am now less motivated." ?
|
| Yes it is exactly what I'm saying. I'm less interested
| because of this. I could turn it around and also say that
| with your extremely positive attitude you can look at a
| piece of dog shit and make it look "amazing." Think about
| it. That dog shit is made out of a scaffold of living
| bacteria like a mini-civilization or ecosystem! Each unit
| of bacteria in this ecosystem is in itself a complex
| machine constructed out of molecules! Isn't the universe
| such an interesting place!!!!!
|
| This history of that piece of shit stretches back though
| millions of years of evolutionary history. That history is
| etched into our DNA, your DNA and every living thing on
| earth!!! All of humanity shares common ancestors with the
| bacteria in that piece of shit and everything is
| interconnected through the tree of life!!! We can go deeper
| because every atom in that DNA molecule in itself has a
| history where the scale is off the charts. Each atom was
| once part of a star and was once part of the big bang! We,
| You and I are made out of Star Material! When I think about
| all of this I'm just in awe!!!! wowowow. Not.
|
| I'm honestly just not interested in a piece of shit. It's
| boring and I can't explain why, but hopefully the example
| above will help you understand where I'm coming from.
| Svip wrote:
| It'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.
| Shorel wrote:
| Hints? Only hints?
|
| I would recommend you to watch Star Trek Picard then =)
| ginko wrote:
| > 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 wrote:
| Ah 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.
| [deleted]
| renewiltord wrote:
| At 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.
| dgb23 wrote:
| Some 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.
| jimbob45 wrote:
| Came here to say this. Asimov's Multivac was the epitome of ML.
|
| I specifically remember a short story by him where one member
| of the population would be selected to be interviewed by
| Multivac and Multivac would then extrapolate out his answers to
| the whole population and be able to accurately pick who the
| population wanted to be president, removing the need for an
| expensive election. If that isn't ML, I don't know what is.
| geomark wrote:
| Yeah, I thought Asimov was all over this long ago. Also see
| "Machines Like Me" by Ian McEwan for a recent go at sentient
| androids.
| arcturus17 wrote:
| Yea, The Foundation is essentially about a group of
| mathematicians using statistics to predict History and build a
| civilization of superscientists.
| QuesnayJr wrote:
| I 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 wrote:
| I mean, it's possible that Assimov imagined it but decided
| that "automatic radio stations" wasn't a compelling enough
| basis for a story.
| arcturus17 wrote:
| The 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 wrote:
| Yup. 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.
| wombatmobile wrote:
| It's not sci-fi but Neil Postman anticipates a world like
| 2020 in Technopoly.
| rthomas6 wrote:
| I 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
| plaidfuji wrote:
| > 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.
| [deleted]
| viach wrote:
| In a sense how miserable our actual achievements will be
| comparing to what sci-fi expected in 2021? Agree.
| sillysaurusx wrote:
| I'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...)
| 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.
| WanderPanda wrote:
| To me this was google search response was mindblowing. I
| searched for it some time ago without the "springer" but I
| added it now, because some (good) reddit explanation is now the
| top result. But if you go to that springer page it is an
| endless technical document and google just found the perfect
| sentence out of it. Now THIS is a bicycle for the brain!
|
| If this is not amazing to you there is only one possible
| explanation for that (by the almighty himself):
|
| > The only thing I find more amazing than the rate of progress
| in AI is the rate in which we get accustomed to it - Ilya
| Sutskever
|
| [1] https://www.google.de/search?client=safari&hl=en-
| gb&biw=414&...
| fock wrote:
| and yet the same machinery decided to translate the director
| of a movie as "direktor" in germany. I guess your quote
| applies there as well!
| Bakary wrote:
| We get easily used to it because presumably the fundamental
| parameters of our lives will not change: we will still have
| to work for a living and so far advances in AI seem to simply
| help to increase inequality, the concentration of capital,
| and to tighten surveillance over workers' lives.
| WanderPanda wrote:
| If central banks would allow deflation to happen, we would
| probably need to work less. In the way it is now they just
| absorb the underlying deflation inherent to technological
| progress to allow more government debt and more zombie
| companies to survive. Technological progress is not the
| reason we still have to work so much
| Bakary wrote:
| I'm not attempting to lay the blame on a specific element
| for the current situation, as we must look at the whole.
| Simply blaming the banks doesn't make much sense in
| isolation, either.
|
| I'm just saying that at the final count we see our lives
| stay the same except when they sometimes get worse and
| this has and will continue to affect our sense of wonder
| and our capacity to be surprised.
| sdflhasjd wrote:
| I've seen similar infoboxes that are completely and outright
| wrong by taking excerpts out of context.
|
| For example, I searched for "How to do Y"
|
| The google infobox says "X"
|
| Clicking into the article to find the more explanation, and I
| read "X is never the right way to do Y, you should do Z
| instead"
|
| I've seen this happen enough that I literally cannot trust
| those snippets.
|
| A bit of an absurd, exaggerated example, Google search (or
| ask your Google Home) "Is the moon made of cheese"
| WanderPanda wrote:
| They seem to have fixed it. Google home answers properly.
| Sad, I was hoping for something funny :D
| IdiocyInAction wrote:
| I think the applicability of ML, at least so far, is quite
| narrow. That's not to say that there are no applications; but
| rather, that it's not the universal AI tool that it is being
| portrayed as in the media.
|
| ML in practice seems to resemble a complex DSP-like step more
| than anything. It seems to be mostly used in classical DSP-like
| domains too (text, speech, images, etc.) It's a tool to handle
| complex, high-dimensional multi-media data.
|
| Though, models like GPT-3 and CLIP show some promise in being
| something beyond that. With the caveat of having billions of
| parameters...
| wombatmobile wrote:
| I didn't know how to search for this...
|
| I'm wondering if anyone has used GPT3 to power a bot that is
| a HN account?
| n4r9 wrote:
| I sympathise with your general point although as an aside I'm
| not sure this is accurate:
|
| > Feynman loved physics long before physics became world-
| changing.
|
| Feynman was an intensely practical person and learnt a lot
| about physics from e.g. fixing his neighbours' radios as a
| child. And radio is certainly something I'd class as "world-
| changing". He loved physics _because of_ the things you could
| build and create, and did not enjoy abstraction or generality
| for its own sake.
|
| A better example for your argument might be Hardy, who
| explicitly stated that his love of number theory was partly due
| to its abstraction and uselessness. This was long before it had
| critical applications in cryptography.
| bumbada wrote:
| You probably already know enough of machine learning and can
| study other topics in order to make ML more useful, for
| example:
|
| - Real marketing(people misunderstand marketing as sales and
| advertising) that is the study of people's needs
|
| -History, in particular History of inventors and inventions
| that really changed the world, like paper(also papyri and
| pergamine) Gutenberg press, crossing the Atlantic on a
| ship,electricity, bicycles and Ford cars, antibiotics, rockets,
| nuclear power, Internet.
|
| -Read books on innovation, like "The Innovator's Dilemma" that
| talks about most innovation having organic growth, looking so
| small at the beginning and then growing proportionally to
| itself. Almost everybody that cares about absolute things, like
| fame or fortune, ignoring it at first because the absolute
| value is so low.
|
| Once you do that you will literally "see the future". You will
| recognize patterns that happened in the past and are happening
| right now. And you will be able to invest or move to those
| areas with a great probability of success.
| robotresearcher wrote:
| > I can't think of ways it's seriously impacted my life
|
| It's there in a thousand little prosaic things, like trackpads,
| camera autofocus, credit applications, news feeds, movie
| recommendations, Amazon logistics optimization. You don't feel
| it but it's there, and the effects accumulate.
|
| It's like robots: dishwashers and laundry washers are
| commonplace computer- and feedback-controlled mechatronics, ie.
| simple special-purpose robots. And almost everything you own
| was made partially with robots. But it doesn't _feel_ like the
| world's full of robots.
| smeeth wrote:
| >I can't think of ways it's seriously impacted my life, other
| than being an interesting challenge to pursue.
|
| What an odd framing. Are technologies only impactful if they
| result in a shiny new toy? Machine learning is a functional
| part of at least 50% of the tech I use daily. I typed this on
| my phone, so I unintentionally used machine learning (key-tap
| recognition) to reply to your comment about machine learning
| impact.
|
| Machine learning is a technology whose benefit is mostly in
| facilitating other technologies. In that way it's more like the
| invention of plastic than the invention of the personal
| computer. Plastic has made other inventions lighter, more
| affordable, and cheaper. So too will ML, but I see where you're
| coming from.
| chiefalchemist wrote:
| > Thus my point: I can't think of ways it's seriously impacted
| my life, other than being an interesting challenge to pursue.
|
| Benefitted? Perhaps not. But you, me, we're all being impacted.
| The fact that it's not easily recognizable - intentionally, I
| might add - doesn't mean it isn't there.
|
| Truth be told, I'm approx half way through Zuboff's "The Age of
| Surveillance Capitalism." As for your hopes, she specifically
| makes mention of the fact that these tools are _not_ being used
| to solve big problems (e.g., poverty) but instead to harvest
| more and more data and exploit that as much as possible. Rest
| assured this imperative is by no means limited.
|
| https://www.publicaffairsbooks.com/titles/shoshana-zuboff/th...
|
| https://www.wnycstudios.org/podcasts/otm/segments/living-und...
| A12-B wrote:
| Machine Learning has literally partially solved protein
| folding. I used to be a denier too but there's no getting past
| this now.
| dfilppi wrote:
| Perhaps ML is just a necessary building block to the
| traditional science fiction future.
| calebkaiser wrote:
| I also work in the field and while the work itself keeps me
| obsessed, similar to you, I keep a list of companies doing
| amazing things beyond "better ad personalization" so that I
| don't get a bit jaded. Some that might be interesting to you:
|
| PostEra - A medicinal chemistry platform that accelerates the
| compound development process in pharmaceuticals. They're
| running an open source moonshot for developing a compound for
| treating COVID, with tons of chemists around the world
| participating.
|
| Thorn - They use ML to identify child abuse content, both to
| help platforms filter it and to help law enforcement save
| children/arrest abusers.
|
| All of the healthcare startups (too many to list all),
| including Benevolent, Grail, Freenome, and more.
|
| Wildlife Protection Services - use ML to detect poachers in
| nature preserves around the world, and have already
| significantly increased the capture rate by rangers.
| pdimitar wrote:
| Is there any open data that clearly demonstrates those
| companies have made a practical difference? Have their NNs
| been used at scale already?
| calebkaiser wrote:
| Yep, if you Google Thorn you'll find a bunch of material on
| how law enforcement uses them and related statistics.
| Several of the other companies (I admittedly haven't done a
| deep dive on all of them) have similarly accessible
| material.
| hooande wrote:
| my issue is that none of these things represent new
| capacities that humans didn't have before. a spreadsheet will
| help you to identify and track child abuse content. you could
| do that using paper if you committed enough resources
|
| My hope for machine learning was that it would allow people
| to see patterns that could not be seen before. While this
| does happen, most practical problems are driven by a few very
| obvious indicators. ML can identify them with a high
| consistency and low cost. This is a useful tool (like a
| hammer) much more than a super power (like iron man's suit)
| philipkglass wrote:
| Numerical weather forecasting enables genuinely new
| capabilities. Where is a hurricane going to make landfall a
| few days from now?
|
| In principle, all the arithmetic operations going in to the
| final forecast could be performed by hand. But then the
| "forecast" would be completed millennia after the hurricane
| arrived. The only way to get _foreknowledge_ of weather
| from the model is to do the arithmetic at inhuman speeds.
|
| This isn't even AI by most people's intuitive notions of
| AI. AI is colloquially an artificial approach to
| intellectual tasks traditionally performed well by humans.
| Since humans were not very good at predicting hurricane
| tracks in the first place, the increasing capabilities of
| models to predict weather probably doesn't have as much wow
| factor. It's a new capability without any human-genius
| antecedents.
| calebkaiser wrote:
| I don't know about that.
|
| Before founding PostEra, its founders published research
| about their model, which significantly outperforms human
| chemists (if you're interested in ML, it's actually a
| fascinating use of an architecture commonly used in
| language tasks):
| https://www.chemistryworld.com/news/language-based-
| softwares...
|
| Thorn's flagship tool, Spotlight, uses NLP to analyze huge
| volumes of advertisements on escort sites and flag profiles
| that have a higher risk of representing trafficking
| victims. You would need an enormous spreadsheet and near
| infinite supply of dedicated humans to manually review and
| refine some sort of statistical model for scoring ads, as
| the volume of advertisements produced is insane.
|
| The same for the deep genomics companies. The size of data
| generated by deep sequencing is beyond a person's ability
| to pattern match, and the patterns are potentially complex
| enough that they may never be noticed by human eyes.
|
| And, again, this is just a small list of startups in
| particularly moonshot-y spaces.
| blacklion wrote:
| Your life is heavily impacted by ML right now.
|
| Ask bank for loan? Your request is scored by ML-based system.
|
| Apply to some position via big HR agency? You CV is scored by
| ML system.
|
| Buy some tickets to flight (I understand, that it sound sad in
| 2021)? You go to airport, ML-based system recognize yur face
| and scans of your luggage and mark you (pray for this!) as
| harmless.
|
| Take some modern drug? It was selected for synthesis and tests
| by large ML system out of myriads other formulas (exactly what
| author of this essay says!).
|
| See this ad on Instagram or some page? ML-based AI decided to
| show it to you.
|
| And so on, and so on.
| [deleted]
| superbcarrot wrote:
| > 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 wrote:
| I 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/.
| ..
|
| 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.
| api wrote:
| I studied biology and point this kind of thing out all the
| time. It usually gets dismissed by people who have not
| studied biology with a lot of hand waving.
|
| Everything you say is true, and more. There is another kind
| of cell in the brain that outnumbers neurons about ten to
| one. They're called glial cells and they come in numerous
| forms. We used to think they were just support cells but
| more recently started to find ways they are involved in
| computation. Here is one link:
|
| https://en.m.wikipedia.org/wiki/Tripartite_synapse
|
| The computational role they have is unclear so far (unless
| there is more recent stuff I am not aware of) but they are
| involved.
|
| We are nowhere near the human brain. I think it will take
| at least a few more orders of magnitude plus much
| additional understanding.
|
| GPT-3 only looks amazing to us because we are easily fooled
| by bullshit. It impresses us for the same reason millions
| now follow a cult called Qanon based on a series of vague
| shitposts. This stuff glitters to our brains like shiny
| objects for raccoons.
|
| What this stuff does show is that generating coherent and
| syntactically correct but meaningless language is much
| easier than our intuition would suggest:
|
| https://nbviewer.jupyter.org/gist/yoavg/d76121dfde261842213
| 9
|
| Those are extremely simple models and they already produce
| passable text. You could probably train it on a corpus of
| new age babble and create a cult with it. GPT-3 is just
| enormous compared to those models, so it's not surprising
| to me that it bullshits very convincingly.
|
| Edit: forgot to mention the emerging subject of quantum
| biology. It's looking increasingly plausible that quantum
| computation of some kind (probably very different from what
| we are building) happens in living systems. It would not
| shock me if it played a role in intelligence. The speed
| with which the brain can generalize suggests something
| capable of searching huge n-dimensional spaces with crazy
| efficiency. Keep in mind that the brain only consumes
| around 40-80 watts of power while doing this.
| username90 wrote:
| Neural nets can solve some problems though like image
| classification, and looking for more applications like
| that is useful. Its just very doubtful that they can ever
| lead to something looking like human or even ant level
| intelligence.
| api wrote:
| Agreed. I didn't say they were useless, just that they
| were not going to become Lt. Cmdr Data.
|
| They're really just freaking enormous regression models
| that can in theory fit any function or set of them with
| enough parameters. Think of them as a kind of lossy
| compression but for the "meta" or function itself rather
| than the output.
|
| The finding that some cognitive tasks like assembling
| language are easier than we would intuitively think is
| also an interesting finding in and of itself. It shows
| that our brains probably don't have to actually work that
| hard to assemble text, which makes some sense because we
| developed our language. Why would we develop a language
| that had crazy high overhead to synthesize?
| gbear605 wrote:
| In my opinion, GPT-3 is impressive not because it's good
| at being human but because it's good at doing lots of
| previously exclusively human things (like poetry) without
| being human at all. It's certainly a better poet than I
| am, though that's a low bar. It's still concerning for
| that reason though - that relatively dumb algorithms can
| convincingly do things like "write a news article" or
| "write a poem". What happens when we get to algorithms
| that are a lot smarter than this one (but still not as
| smart as our brains)?
| api wrote:
| I don't think it's a good poet. I think it does an
| excellent job assembling text that reads like poetry, but
| if you go read some good poets that's only a small part
| of what makes their poetry good. Good poetry talks about
| the human experience in a place and time.
|
| It absolutely could be used to manufacture spam and low
| quality filler at industrial scale. Those couple Swedish
| guys that write almost all pop music should be worried
| about their jobs.
| ganstyles wrote:
| My company has used ML to create synthetic cancer data to train
| classifiers to augment doctors/specialists who are looking for
| cancer. This work has greatly increased accuracy in diagnosis,
| saving lives. To say it's only for music generation or
| generating waifus is a bit unfair.
| pdimitar wrote:
| What did your company to do share those findings with the
| doctors worldwide? Did your company reduce mortality?
|
| Otherwise it's kind of like, I have invented SkyNet in my
| garage but I am only using it to become richer through the
| stock market.
|
| It's admirable that you are working on saving human lives.
| But are human lives actually saved?
| edouard-harris wrote:
| > Did your company reduce mortality?
|
| From the parent:
|
| > This work has greatly increased accuracy in diagnosis,
| saving lives.
| rscho wrote:
| ... which is apparently pure speculation
| rscho wrote:
| > This work has greatly increased accuracy in diagnosis,
| saving lives.
|
| As an MD with a special interest in statistics, color me
| skeptical. I'd love to be proven wrong though, so please
| provide references.
|
| Edit: yeah, so the way this whole thread is developing really
| goes to show (yet again) that medical AI hype is relying as
| strongly as ever on the fantasies of people who've never seen
| any clinical work.
| BadInformatics wrote:
| I know of at least one Canadian hospital that's
| incorporated ML into 100% of their ED triage. Sure it's not
| some state of the art deep learning architecture, but it's
| definitely a step above the old crop of heuristic-based
| systems you see so often in medical software. "Medical AI"
| is a stupid term that's been co-opted by more hucksters
| than legitimate practitioners, so I prefer to talk about
| more concrete (and less fanciful) applications like patient
| chart OCR or capacity forecasting.
| rscho wrote:
| > I know of at least one Canadian hospital that's
| incorporated ML into 100% of their ED triage.
|
| Cool! Which hospital is that? Is the clinical staff happy
| with the results?
|
| Personally, I've never seen any medical ML application
| that made my job easier. But it would be nice to see.
| Thebroser wrote:
| Maybe not hard data, but EPIC's software (which is used in
| about ~25% of hospitals for EHR) has over the years been
| utilizing patient data to be used for treatment
| recommendation purposes. Again, difficult to weigh the
| impact if we don't know how many doctors are relying on
| these types of recommendations and acting on them but it is
| definitely out there in the real world at the moment.
| >>https://www.epic.com/software#AI
| rscho wrote:
| > we don't know how many doctors are relying on these
| types of recommendations and acting on them
|
| I can answer that: close to zero. Clinicians don't want
| stuff that makes recommendations, as good as they may be.
| They want a bycicle for the mind: something that helps
| them visualize, understand the big picture and anticipate
| better. And also ensure that trivial stuff to do is not
| forgotten (now that's the place a recommender engine
| could fit in). That's a fundamental misunderstanding of
| what a clinician's job is that is unfortunately very
| common.
|
| What do you ask of your software tooling? Do you want
| something that just tells you what to write? No, you want
| a flexible debugger. A compiler with precise error
| messages. You want a profiler with a zillion detailed
| charts allowing you to understand how everything fits
| together and why such and such is not the way you
| anticipated. Same thing for medicine until the day
| machines will actually do better than humans, which is
| not tomorrow nor the day after.
| lasagnaphil wrote:
| I think ML's currently temporarily useful in fields that have
| been making decisions mostly based on intuition and
| heuristics. The medical field's one example, even with some
| knowledge on biology and anatomy it's hard to diagnose and
| treat patients only with deductive reasoning, a lot of
| guesswork and "experience" is involved. In that case ML might
| be able to perform better than humans, but I think this will
| have its limits. Above a certain point, I think biological
| simulation (as in physics simulation) would be a much more
| useful tool for doctors to understand the human body.
| hderms wrote:
| I don't know, if you ever look at a flowchart of
| biochemical processes, realizing that what we've mapped out
| is only a tiny sliver of what actually occurs, you'd be
| more pessimistic about simulation in the near term. We can
| simulate things all we want but the hard part is rooting
| the simulation in hard evidence, something which requires
| massive capital and time investment. Epigenetics complicate
| even further.
| imbnwa wrote:
| Would you happen to have any links to share further
| explaining the limits of our knowledge of biochem
| processes?
|
| How does epigentics complicate this further, is it that
| it wides the number of inputs into a biochem system
| jpeloquin wrote:
| Not exactly what you asked for, but PathBank is a
| database that quantitatively describes a large part of
| what we do know: https://pathbank.org/
|
| As far as what we _don 't_ know, I'm not sure there's a
| list. Lack of knowledge implies lack of awareness. I can
| offer one example: We don't know much about the processes
| by which collagen fibers are grown and assembled into mm-
| and mm-scale load-bearing structures in tendon, ligament,
| bone between embryo and adult, particularly in mammals.
| Or the extent to which collagen fiber structures are
| capable of turnover in adults; healing might only be
| possible by replacement with inferior tissue such as
| scar.
|
| Personally, I think the complexity of biological systems,
| and the difficulty of observing their components directly
| when and where you'd want to, means that they can only be
| understood with the help of machines. Not necessarily
| using convolutional neural networks though.
| Enginerrrd wrote:
| I'm skeptical... But it depends what data sources are
| available. I was a paramedic so my medical knowledge is
| limited, but at the same time, we frequently had to do
| field diagnosis. It's hard to explain... but you can have
| patients with the same symptoms and two totally different
| diagnoses. You basically just learn to intuit the
| difference but none of the stuff we can write down or
| quantify drives the differential diagnosis. And it's funny
| because you get pretty good at it. I could just tell when
| an elderly patient had a UTI even though they had a whole
| cluster of weird symptoms. Or more importantly, I could
| tell you when someone was just a psych case despite
| complaining of symptoms matching some other condition with
| great accuracy.
|
| It'd be really hard to train a computer when to stop
| digging because there's nothing find, or when to keep
| digging because this patient really doesn't feel like a
| psych case. And the tests and doagnostics aren't without
| risk and cost.
|
| I've had a greybeard doctor in my personal life that
| somehow read between the lines and nailed a diagnosis
| despite my primary symptoms being something else entirely.
| (I had recurring strep tonsilitis for months and yet he
| just somehow knew to step back and order a mono test. It
| came back negative the first time, and he knew to have me
| tested AGAIN, and lo and behold it was positive.) None of
| symptoms were really consistent with mono. I tested
| positive for strep each time and antibiotics would clear
| it.). Thankfully I happen to be allergic to the first line
| antibiotic because if you give amoxicillin to someone with
| mono they'll get a horrible rash all over their body in
| like 90% of people.
| [deleted]
| jhowell wrote:
| Earlier detection. Is this new tech, or just a sharper
| hammer?
| rscho wrote:
| We don't know yet. What's sure is that it has greatly
| increased the number of cancer surgeries, especially lungs.
|
| We don't know if that's a good thing yet.
| TaupeRanger wrote:
| Do you have any papers published to support such a strong
| claim (one that directly contradicts the sentiment of almost
| every single oncologist and pharmacologist I know that isn't
| trying to generate profits for a biotech company)?
| ganstyles wrote:
| edit: I posted that I have internal data, but also realized
| I said a little bit too much about the process. The below
| point someone is making is a totally fair one. Editing this
| though for Reasons while trying to keep the part of the
| comment that led to the below dismissal, and also to
| clarify my definition of "internal data" to be more
| expansive than "internal testing on datasets" which is what
| I realize it might sound like.
| TaupeRanger wrote:
| That's not how this works. The only way to show an actual
| reduction in all cause mortality as the result of an
| intervention, treatment, or screening process is through
| a randomized controlled clinical trial. If none have been
| performed, you don't have evidence that lives have been
| saved. Extraordinary claims require extraordinary
| evidence.
| ganstyles wrote:
| Totally fair. It is a very, very hard field to make
| progress in. I would also take anything I say with a
| grain of salt, I'm not trying to convince you, just to
| bring an additional data point to the thought that these
| techniques aren't very useful or impactful.
| jhowell wrote:
| Maybe the GP threw the wrong buzzword and meant AI
| instead of ML.
| hadsed wrote:
| i think focusing entirely on one type of evidence is a
| little unimaginative. if these guys have data on doctors
| performing some task with and without their tool, they're
| in a good place to measure the difference. they can take
| that all the way to the bank, and to me that would
| contribute to what id call evidence.
| rscho wrote:
| Until they have to really show that it's working in day-
| to-day practice. Where it most likely won't,
| unfortunately.
| sillysaurusx wrote:
| That's actually wonderful to hear! Is there some way to
| assist with that work? Doing something with a human impact is
| appealing.
|
| (To be clear, my argument wasn't that ML isn't useful -- but
| rather that individual lone hackers are less likely to be
| using ML to achieve superman-type powers than I originally
| thought. Supermen do exist, but they are firmly in the ranks
| of DeepMind et al, and must pursue projects collectively
| rather than individually.)
| rscho wrote:
| Yes, if you carry some weight in the field then the most
| useful contribution would be to push for better automated
| gathering of quality clinical data. This is the most
| limiting factor currently.
|
| Of course policy activism is far less sexy than building
| new shiny things, so there's little interest in that.
| yorwba wrote:
| > individual lone hackers are less likely to be using ML to
| achieve superman-type powers than I originally thought
|
| For a single individual to have "superhuman" impact with
| ML, they need not only generic ML knowledge, but also
| specialized knowledge of some domain they want to impact.
| Actually, because ML has become so generic (just grab a
| pre-trained model, maybe fine-tune it, and push your data
| through it) a very shallow understanding of the
| fundamentals is probably enough, and in-depth domain
| knowledge much more important.
|
| That doesn't mean generic ML research isn't important, it's
| just that it has an average impact on everything, not a
| huge impact in one specific area.
|
| (I suspect many hobbyist ML projects are about generating
| entertaining content because everyone has experience with
| entertainment, even ML researchers.)
| counters wrote:
| !00% nailed it. ML/AI are tools. As in any other
| exercise, tools can make it easier for beginners/amateurs
| to engage with a project, but they don't replace 10,000
| hours of experience and deep domain experience and
| understanding. It's the master craftsmen and domain
| experts who will create the most value with these tools,
| but that may not be in obvious or clearly visible ways.
| np_tedious wrote:
| They also likely need a lot of training data and compute
| resources
| bosie wrote:
| Can you expand on how you create that synthetic data and how
| the evaluation (increased accuracy in diagnosis) works?
| [deleted]
| ramraj07 wrote:
| It has affected a small number of fields for sure. Imaging
| based diagnosis might be better off due to ML, but imaging
| based diagnosis isn't going to cure cancer or be helpful for
| every single disease. Glad it's helping but the authors point
| is only reinforced. Unless you can make a case that we will
| cure basically everything with ML that is.
| yread wrote:
| Imaging based diagnosis is not going to cure cancer, but it
| can guide treatment - based on what the AI reads from the
| images patients can get drugs that are very effective for
| their particular cancer. We have very effective drugs
| nowadays, large part of treating cancer is figuring which
| drug to give.
|
| Imaging based diagnosis could read presence or absence of
| particular gene mutations from the images so that the genes
| can be silenced by the drugs.
|
| Imaging based diagnosis could also figure out whether a
| particular cancer precursor is going to develop into
| invasive cancer and do it better than the experts we have
| now (otherwise we wouldn't use the AI).
|
| This can also be done cheaper than paying consultants to
| figure it out and it can be done in locations where they
| don't have the specialists.
|
| Some companies working in the field (some already have
| tools approved for use on patients):
|
| https://analogintelligence.com/artificial-intelligence-ai-
| st...
| timy2shoes wrote:
| > Imaging based diagnosis could read presence or absence
| of particular gene mutations from the images so that the
| genes can be silenced by the drugs.
|
| >Imaging based diagnosis could also figure out whether a
| particular cancer precursor is going to develop into
| invasive cancer and do it better than the experts we have
| now (otherwise we wouldn't use the AI).
|
| Where is the evidence for these claims, other than a VC
| hype sheet? Like real clinical trials. These claims also
| show a fundamental misunderstanding of what this data can
| tell us. Imaging data doesn't give you tumor genetic
| profiles. It can give you tumor phenotype, which is
| associated with specific mutations. To get the true
| genetic profile you need to do deep sequencing at tens of
| thousands of dollars per tumor, and even then you have
| the problem of tumor heterogeneity, which lets the cancer
| evade the treatment.
|
| A major concern I have working in this space is that
| we're selling people on grand promises of far off
| possibilities rather than what we can actually deliver
| right now.
| yread wrote:
| Histology slides absolutely can tell us a lot about
| molecular changes, see
|
| https://www.nature.com/articles/s41591-019-0462-y
|
| Of course changes in the genotype that impact the
| phenotype enough to influence the disease also influence
| the morphology of the cells.
|
| But this is area of active research so you can't expect
| phase 3 clinical trials. Yet.
|
| EDIT: here is another more "perspective" paper how such
| tools could be used and integrated in current processes,
| from the same authors
|
| https://www.nature.com/articles/s41416-020-01122-x
| ramraj07 wrote:
| Just the latest iteration of people who don't know
| biology (used to be Physicists, now it's the AI guys)
| coming in to save all of us. Once in a while someone does
| make meaningful contributions, but in the end it's hard
| to say if the collective investment in attention and
| money have made it worthwhile or not.
| TaupeRanger wrote:
| ML diagnosis could actually be _worse_ for us overall, as
| we might find more harmless cancers and subject people to
| more unnecessary tests and treatments. Iatrogenic harms are
| real, especially when ML gives us only diagnostics, and
| never any treatments.
| polm23 wrote:
| Regina Barzilay has done some work in this area; I posted
| slides from a great talk she gave years back a few years ago.
| The slides seem to be gone and not on Internet Archive
| sadly...
|
| https://news.ycombinator.com/item?id=20019355
|
| This Twitter thread also has a lot of good stuff.
|
| https://twitter.com/maite_taboada/status/1086415051127308288
| polm23 wrote:
| Ah, found the PDF - the URL changed at some point before
| disappearing.
|
| https://web.archive.org/web/20190527041657/http://people.cs
| a...
| laurent92 wrote:
| ML has been key in finding the invaders of Congress.
|
| I'm more worried about ancestral issues about crime: The
| definition of what a << crime >> is (hatecrime: verbally
| misgendering someone) and unequal application of law (one side
| being encouraged to commit $2bn damage, the other receiving
| condemnation of international presidents). It is just being
| leveraged to give more power to the powerful, enabling not the
| 1% but the 1%0.
| dgb23 wrote:
| Much of current AI is concerned with optimization and
| automation. Not something we couldn't do before, but faster and
| automated. This is exciting in the sense of being a force
| multiplier.
|
| But I agree with the sentiment that progress is often driven by
| intrinsic motivation.
| ironchef wrote:
| I think it's getting there... but I also think a lot of the
| impact are things we don't see. Top of mind would be: *
| autonomous driving * language translation * salience mapping *
| fraud detection
|
| I guess I'm somewhat on the opposite side of the fence. I see
| it everywhere... although yes I think Big Bang things are
| probably a few years off
| Daho0n wrote:
| >Big Bang things are probably a few years off
|
| As far as I have seen experts see autonomous driving as at
| least ten years away (unless you look at the sliding "next
| year" BS from Tesla) so I don't think we're only a few years
| off big changes because of ML. More like 10-15.
| rakhodorkovsky wrote:
| Could you point me to some of those expert takes on
| autonomous driving?
| aaron695 wrote:
| There's a GPT-2 on HN which you've talked(replied) to.
|
| I guess, if a tree falls in the forest.
|
| But when there are hundreds of them, I feel like it will
| 'seriously impact'. They are exceedingly stupid.
| wombatmobile wrote:
| Oh?
|
| Is there a GPT3 bot?
| aaron695 wrote:
| GPT-3 is not very open.
|
| https://en.wikipedia.org/wiki/GPT-3
|
| Related - https://liamp.substack.com/p/my-gpt-3-blog-
| got-26-thousand-v...
| YeGoblynQueenne wrote:
| >> As someone on the forefront of ML, you would expect me to be
| in a position to reap the benefits.
|
| Can you say how you are "someone at the forefront of ML"?
| indigochill wrote:
| A girl I went to high school with went on to apply machine
| learning to identify human trafficking victims and ads for law
| enforcement.
|
| My perception of machine learning as a mere dabbler myself is
| that "machine learning" is just a sci-fi name for what's
| essentially applied statistics. In places where that is useful
| (e.g. clustering ads by feature similarity to highlight
| unclassified ads that appear similar to known trafficking ads),
| then machine learning is useful. It's not necessarily as one-
| size-fits-all as, say, networking or operating systems are, but
| in cases where you can identify a useful application of
| statistics, machine learning can be a useful tool.
| ctdonath wrote:
| The great tragedy of AI: a promise of creating synthetic
| sentience, a reality of mundane number crunching.
| canoebuilder wrote:
| That's the question. If consciousness/intelligence is
| wholly in the brain, and the brain's interaction with the
| physical world, is that something that can be modeled with
| number crunching, i.e. computation? Perhaps we are still
| very early days.
| hooande wrote:
| a black hole is entirely a product of physical processes.
| how long until we can make one? or even fully understand
| them
| lupire wrote:
| ML (neural nets) are useful because they automate much of
| parameter search. Instead of trying an SVM and then Random
| forests and then whatever, just throw all the data at a GPU
| and let it build an NN for you.
| PartiallyTyped wrote:
| NNs come with many caveats and lack the theoretical
| guarantees and support of SVMs and RFs. They should never
| be the first approach to solving a problem unless a) you
| have good reason to support the hypothesis that other
| models don't cut it such as a non stationary problem e.g.
| RL, or b) other methods can't scale to the difficulty of
| the problem. NNs are also very expensive to train compared
| to everything else.
| hooande wrote:
| It's a rare case when a neural net will give you materially
| different results than a random forest or an svm. ie, if an
| svm is 80% accurate, a well tuned neural net might be 83%
| accurate. sometimes that's a huge difference. in a domain
| like medical image classification, maybe not so much
|
| also you can just "throw all the data" at an svm or random
| forest, or any number of similar models. Automated
| parameter tuning can be convenient, but it's prone to
| overfitting and doesn't eliminate a lot of the actual work
| baxtr wrote:
| _> My perception of machine learning as a mere dabbler myself
| is that "machine learning" is just a sci-fi name for what's
| essentially applied statistics_
|
| As a physicist I used to say that ML is simply non-linear
| tensor calculus. (I'm not sure if I'm right though)
| PartiallyTyped wrote:
| I don't think you are, if you have never heard of
| Reinforcement Learning, I think you are in for a treat.
| [deleted]
| jjcon wrote:
| > I'm increasingly concerned that the impact of ML is going to
| be limited.
|
| You say likely typing on a keyboard with ML predictive
| algorithms on it, or dictating with NLP speech to text. On a
| phone capable of recognizing your face, uploading photos to
| services that will recognize everything in them.
| username90 wrote:
| And that seems to be the limits of ML. We might eek out self
| driving cars, but I don't think we will get much more than
| that. It is pretty significant, but still limited compared to
| general purpose AI.
| ChefboyOG wrote:
| Predictive text and image classification are not the extent
| of ML's limits, even going by what is currently in
| production. Recommendation engines, ETA prediction,
| translation, drug discovery, medicinal chemistry, fraud
| detection--these are all areas where ML is already very
| important and present.
|
| Sure, it's not artificial general intelligence, but what
| technological invention in history would compare to the
| impact of AGI? That's sort of a weird bar.
| PartiallyTyped wrote:
| One step at a time. As of the previous decade, we have
|
| - Learned how to play all atari games [1]
|
| - Mastered GO [2]
|
| - Mastered Chess without (as much) search [3]
|
| - Learned to play MOBAs [4]
|
| - Made progress in Protein Folding [5]
|
| - Mastered Starcraft [6]
|
| Notice that all these methods require an enormous amount of
| computation, in some cases, we are talking eons in
| experiences. So there is a lot of progress to be made until
| we can learn to do [1,2,3,4,6] with as much effort as a
| human needs.
|
| [1]
| https://deepmind.com/blog/article/Agent57-Outperforming-
| the-...
|
| [2] https://deepmind.com/research/case-studies/alphago-the-
| story...
|
| [3] https://deepmind.com/blog/article/alphazero-shedding-
| new-lig...
|
| [4] https://openai.com/projects/five
|
| [5] https://deepmind.com/blog/article/AlphaFold-Using-AI-
| for-sci...
|
| [6] https://deepmind.com/blog/article/alphastar-mastering-
| real-t...
| username90 wrote:
| AI playing games is cool, but applying those techniques
| to real world scenarios would require a huge
| breakthrough. If a huge breakthrough happens then sure,
| but my point was based on us continuing using techniques
| similar to what we currently use.
|
| Huge breakthroughs happens very rarely so I wouldn't
| count on it.
| PartiallyTyped wrote:
| We can learn a lot by observing what we learned from
| games. With starcraft in particular, we learned that RL
| agents can achieve godlike micro play but they are weaker
| at macro. Dota Five showed that it is possible to
| coordinate multiple agents at the same time with little
| information shared between them.
|
| This suggests that human theory crafting and ML accuracy
| should be able to achieve great things. One step at a
| time.
| cma wrote:
| The protein folding thing could be big.
| jjcon wrote:
| For the average person that is their greatest exposure -
| but were already seeing huge movements in medicine and
| defense and plenty of places where ML is not in average
| consumer use (the biggest applications are not for
| consumers). Add in your note on transportation and it is at
| the front of a huge section of the world economy. That's
| all on track today - what will tomorrow's innovations bring
| (the question asked by sci-fi)?
| username90 wrote:
| Image recognition is just image recognition no matter
| where it is used.
| jjcon wrote:
| Wrong sub thread?
| lucidrains wrote:
| You can get a taste of the mentioned technology in the article
| today. https://github.com/lucidrains/deep-daze
| https://github.com/lucidrains/big-sleep
| mmmmmk wrote:
| The GPT-3 Jerome K. Jerome essay blew my mind. Better than most
| writers out there. Close up Iowa Writers' Workshop- that place is
| toast!
| bsanr2 wrote:
| True 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/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.
| 29athrowaway wrote:
| Machines 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.
| lasagnaphil wrote:
| From 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).
| malka wrote:
| Imo it would be easier to interact with real neurons. It
| raises some ethics questions though
| 29athrowaway wrote:
| You forget one thing: we have people reverse engineering
| biological neural networks from various perspectives.
|
| We got to deep learning because Mountcastle, Hubel and Wiesel
| reverse engineered the visual cortex of cats.
|
| That was the starting point of Fukushima's Neocognitron, the
| ancestor of the deep learning stuff you study today.
|
| Then, only a fraction of our brain is used on cognitive
| tasks. The rest is used in motor tasks and taking care of
| autonomous tasks like regulating your heart, glands and such.
|
| Things will happen faster than you think.
| [deleted]
| cjauvin wrote:
| I 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-
| Appe...
| inetsee wrote:
| This 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.
| rscho wrote:
| Regarding 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/
|
| And for where this all comes from:
|
| https://youtu.be/DQouNG9iuDE
|
| The underlying system:
|
| 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 wrote:
| What is it that the ML people have to understand about the
| clinical system before they can be effective?
| rscho wrote:
| That 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.
| EamonnMR wrote:
| Providence by Max Barry did a pretty good job. It follows the
| crew of self-driving spaceship.
| godelzilla wrote:
| In fairness it would've been hard to imagine the current level of
| hype about data analysis.
| imbnwa wrote:
| What's a good place to start getting into the mechanics of
| machine learning? Prerequisites?
| tryonenow wrote:
| The 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.
| egberts wrote:
| Wut? 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
| flohofwoe wrote:
| Maybe 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 wrote:
| Lem 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 wrote:
| > 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...
| loopz wrote:
| Some 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.
| gbear605 wrote:
| Depending on what you mean by understand, it seems that
| some ML models are already beyond human understanding.
| op03 wrote:
| I 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.
| Mediterraneo10 wrote:
| My 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).
| Bakary wrote:
| You 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.
| ThomPete wrote:
| I 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-realtim...
| TaupeRanger wrote:
| "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.
| bregma wrote:
| It'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 wrote:
| Glad 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 wrote:
| If 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."
| zurfer wrote:
| That'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 wrote:
| Why 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 wrote:
| Isn'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 wrote:
| No, 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 wrote:
| Human reasoning is always contextualised by the humans
| assets - wealth, beauty, status, ideology, character,
| temperament, location, affiliations.
| jondiggsit wrote:
| Here'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.
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