11 ms·

On the Impossibility of Supersized Machines (2017)

85 points by FBT 5y ago

scubakid 5y ago
Makes me wonder: how's the HN community feeling these days about the actual plausibility / timeline of humans developing true AGI? Personally the more I learn about the current state of AI, and in comparison the way the human brain works, the more skeptical (and slightly disappointed) I tend to get.
- toxik 5y ago
  “AI research” is largely concerned with automation, not sentience or AGI. This is clearly abuse of terminology, even “machine learning” is somewhat misleading in my opinion. It’s mostly just pattern recognition of increasing elaboration, and the applications thus far are exactly that: pattern recognition. It’s so difficult to talk about AGI, sentience, consciousness in general because there are no clear definitions apart from “I’ll know it when I see it.”
- jjoonathan 5y ago
  Have you seen the "interviews" with GPT3?
  - qualudeheart 5y ago
    What about them?
    - jjoonathan 5y ago
      You'd fail to Turing test them in casual conversation.
- hooande 5y ago
  AGI is currently as likely as teleportation, time travel or warp drives. You can write a computer program to do just about anything. Artificial "General" intelligence is simply not a thing. We're not even making progress toward it.
  - simonh 5y ago
    We do not observe teleportation, time travel or warp drive in nature. We also don’t have any practical theory for achieving them as depicted in science fiction. It seems unlikely we will achieve such technologies. Do we observe general intelligence in nature though, here on Earth implemented with the materials available in our environment? If so, it’s a bold claim to make that it will always be impossible to achieve it artificially.
    - hooande 5y ago
      How far are we away from gene editing that will allow humans to be born with working gills or wings? Animals have these things, so we know it's possible. But having the technology to do that is very far off, if ever. The same is true of AGI. Of course it's possible. but right now no one has any clear idea how to do it without extreme brute force. Personally, I think it's more likely that we'll have a working Alcubierre drive before anything approaching general intelligence
      - Ginden 5y ago
        > How far are we away from gene editing that will allow humans to be born with working gills or wings? Impossible due to physics limits. Human lungs have 57 square meters for extracting oxygen from fluid with 21% volume oxygen. 30°C air-saturated water have 0.5% of oxygen, so working gills for human would need surface area of 2394 square meters.
        rembicilious 5y ago
        Gills work by continually “filtering” water as is flows through them. Lungs are filled and then emptied according to some pattern of breath. The difference in volume of fluid processed must be significant. Also, can’t gills have a higher surface area to volume ratio than lungs?
      - simonh 5y ago
        We can extract oxygen from water right now, so we can already do this. Requiring a specific implementation technology is unreasonably stacking the deck. You’re making the same mistake as those who critiqued the concept of heavier than air flying machines, starting from the assumption they must work by flapping their wings. As it happens now we have wing flapping drones anyway though. “Ever” is a very, very, very long time.
- kromem 5y ago
  I think that many people throwing their hat in the ring commenting on the unlikeliness of AGI are missing the impact of compounding effects. Yes, on a linear basis it's not going to happen anytime soon. But the trends in the space are developing around self-interacting discrete models to great effect (see OpenAI's Dall-E). The better and broader that systems manage to self-interact, the faster we're going to see impressive results. As with most compounding effects, it's slower growth today than the growth tomorrow. But a faster growth today than it was yesterday. The human brain technically took 13.7 billion years to develop from purely chaotic driven processes, and even then it was pretty worthless up until we finally developed both language and writing so we could ourselves have lasting compounding effects from scaling up parallel self-interactions. And from 200,000 years of marginal progress we suddenly went in less than 7,000 years from no writing and thinking the ground below our feet the largest thing in existence to measuring how long it takes the fastest thing in our universe (light) to cross the smallest stable object in our universe (a hydrogen atom). Let's give the computers some breathing room before declaring the impossibility of their taking the torch from us, and in the process, let's not underestimate the effects of exponential self-interactions and the compounding effects thereof.
  - coldtea 5y ago
    >are missing the impact of compounding effects. On the other hand those saying "it will sure happen" are missing the impact of diminishing returns.
    - scubakid 5y ago
      True, at a high level I think the central issue is what kind of curve we're on.
  - dan-robertson 5y ago
    The opposite of compounding effects are compounding difficulties. Computer science is full of problems where a multiplicative increase in effort results in an additive increase in output. We call these “exponentially hard” and they crop up annoyingly frequently. So one argument is that compounding improvements will result in linear increases in output because of exponential difficulty. The counter-argument is that many of these hard problems have good but not perfect solutions which may be found more efficiently.
- Causality1 5y ago
  Personally I think we're going to need a revolution in the fundamental physics of computation. The example I like to use is that a dragonfly brain uses just sixteen neurons to take input from thousands of ommatidia and track prey in 3D space, plot intercept vectors, and send that data to the motor centers of the brain. Calculate how many transistors and watts of power you'd need to replicate that functionality. Now multiply that number by how many neurons you think it takes the human brain to generate sapience. It doesn't really matter what your guesses are, none of the results are good news.
  - scubakid 5y ago
    I tend to think in similar terms. There's so much going on under the surface with even the simplest creatures in the natural world that the physics and computational fundamentals seem really intimidating here. That's not to say that we could never get there -- certainly, many hold out hope for our abilities continuing to compound over time. But it's kind of a bummer to think about the glimmer of true AGI only materializing much further along an exponential growth curve that, to me, doesn't seem guaranteed to continue indefinitely.
  - mlyle 5y ago
    > Calculate how many transistors and watts of power you'd need to replicate that functionality. I'm curious as to your answer. Because if one's building a purpose-built analog computer for the task, my estimate is a few hundred transistors, a few thousand passives, and ... an absolutely trivial amount of power on modern process.
    - Causality1 5y ago
      I'm curious how we're even going to manage 420,000 pixels' worth (60,000 ommatidia, approximately 7 pixels each) of input with only a few hundred transistors, let alone do vector analysis on it. But let's say we can. Let's say we need 320 transistors, which would be 20 transistors per pixel. That's pretending 99.7% of the seven thousand synapses each neuron has are useless for our purpose, but we'll do it. A chimp brain runs all the autonomous physical processes of a humanoid body while only having 22 billion neurons. We'll also pretend, wrongly, that chimps have no mind or emotions at all and that we only need the extra human neurons to make a sapient mind. Humans have 86 billion neurons. Subtracting 22 gives us 64 billion, times 20 transistors per neuron gives us 1.28 trillion transistors. 1.28 trillion transistors, even with a bunch of handwaving to make it easier, and even pretending we exactly understood how sapience worked in the first place.
- joe_the_user 5y ago
  The thing about these arguments for the impossibility of AI/AGI is that they inherently rest on the idea that they know what "human intelligence". So they have the same weaknesses as arguments project a set timeline for AGI. We won't build a duplicate of the human brain - unless we have AGI first to tell us how. But we really don't know what portions of the human brain are needed for useful AGI. You can look at GPT-3. On the one hand, never being reliable puts a crimp on practical applications. One the other hand, it does a lot of amazing things that seem human. I'd say that since we don't know where we're going in a profound way, we don't know how far we have to go.
- abetusk 5y ago
  The human brain is estimated at 2.5 Pb of storage [0]. Assuming a "Moore's Law" like behavior of storage price, so that price halves every 2-3 years and assuming we use storage as a proxy for the space, access speed and computational power, the time it will take to have a $1000 computer that has the storage capacity of the brain will be in the 10-16 year time horizon. This puts the timeline to about 2029-2035. [0] https://www.scientificamerican.com/article/what-is-the-memory-capacity/ https://www.scientificamerican.com/article/what-is-the-memor...
  - nine_k 5y ago
    It is not hard to create a RAID array with 2.5 Pb capacity. The trick of the human brain is that the "processing power" is enmeshed into the "memory", so the brain must have a colossal computational bandwidth, even with pretty slow neurons. I suppose that bandwidth is larger than that of most modern GPU / TPU clusters, which also don't feature anything comparable to 2.5Pb or RAM in their disposal. The revolution should be mostly in the architecture, much like the deep learning evolution was enabled by GPUs.
    - abetusk 5y ago
      I think you missed the critical point: for $1000. Feasibility is great but economic access is the aspect that I'm focusing on.
  - Something1234 5y ago
    In the past 10 years, I think we had a 8x increase in easily available storage going from 1TB drives being a $100 to a 16TB drive being roughly $250. So I would have to say that your time scale is way too optimistic at best.
    - abetusk 5y ago
      I won't check your numbers and take them at face value. Even with your numbers, that's a 6.4x decrease in price per TB (($100/1Tb) / ($250/16TB)), which is around 2.7 halvings over the course of 10 years, which is very close to my "2-3 years per halving" statement. Even if it's slower than a halving in price per 2-3 years, 4-5 years say, this only delays my prediction by a decade or so.
- simonh 5y ago
  We’re currently in the very early phase of our understanding of what intelligence is. The more we learn about it, the more we appreciate the staggering scale and complexity of the problem. So at the moment yes, it seems like the objective is receding into the distance faster than our progress towards it can keep up. 1960s - Herbert Simmons predicts "Machines will be capable, within 20 years, of doing any work a man can do." 1993 - Vernor Vinge predicts super-intelligent AIs 'within 30 years'. 2011 - Ray Kurzweil predicts the singularity (enabled by super-intelligent AIs) will occur by 2045, 34 years after the prediction was made. So the distance into the future before we achieve strong AI and hence the singularity has been, according to it's most optimistic proponents, receding by more than 1 year per year. Eventually I believe we will get a good enough understanding of the subject that we can map out a route to implementing AGI, and then our progress will accelerate towards a known and understood goal.
- benlivengood 5y ago
  We have superhuman performance at most narrow skills; the exceptions seem to be object manipulation with limbs/digits and semantic/logical thinking and planning. Given the advances by Boston Dynamics and others with limb-based mobility I'm guessing that's not too far off. With recent models proving a significant subset of the Metamath theorems, that doesn't look too far away either. Google/DeepMind are playing around with sparse model combinations of many useful superhuman domain models with additional layers to determine which domain to use for particular inputs. The last and most difficult step in safe AGI is moral/value alignment. That is unfortunately probably last on the timeline of likely achievements because it requires general solutions to both planning and reasoning, and also an accurate world model and understand of physical actions and their consequences.
- rbanffy 5y ago
  My guess is as good as any other layperson's, but I don't see much work being done for it, and no real good definition of what it is so we could plan how to create it. OTOH, we see specialized intelligences do all soft of superhuman feats, all the time, and more impressive abilities join these all the time. These, however, are not human-like intelligences. They aren't even bee-like. They are so alien we don't see "general intelligence" in them. So, my guess is that we'll have some extremely complex and capable systems that are extremely alien in nature well before we can have a conversation with a human-like intelligent system. They'll be useful and treated like oracles - we won't be able to understand their reasoning, but they'll be right most of the time. It is, however, a matter of time and desire. There is nothing inherently magical in our mammalian brains and our organic bodies that can't be simulated by a sufficiently capable machine and technology for that will, eventually, become possible, then available, then practical, and then ubiquitous.
  - scubakid 5y ago
    To me, the term "alien" connotes a level of capability much more interesting than what I've actually seen from most modern systems. But point taken. And I'd like to believe that you're right about it only being a matter of time and desire, but I do also worry about the possibility that we're actually on a different kind of exponential curve and will instead reach a point where we see diminishing returns.
    - rbanffy 5y ago
      I have no doubts there will be diminishing returns at some point, specially with narrow AIs, where increases in complexity and cost of training models will not be able to improve on what’s already good enough. AI is a tool like many others, useful for some things and not for others.
- gameswithgo 5y ago
  Nobody expected anything like supremacy in Go any time soon and then all of a sudden it happened. Maybe AI stagnates for a long time bow, maybe forever, maybe a big breakthrough happens tomorrow. Nobody knows, anyone confidently asserting anything is being foolish.
- more_corn 5y ago
  I don't think AGI is likely, I think it is inevitable. We can make specialized neural networks that can do specific tasks quite well. There's nothing stopping us from chaining those together. We have the pieces to make neural networks that can train on new data, thus creating new layers atop previous networks. We can even train those layers based on the data generated by the action of the network itself. The pieces seem to be present, the tooling around putting them together seems to be lacking for the time being. I expect to see AGI in my lifetime, artificial super intelligence shortly thereafter and then the event horizon of the singularity.
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et2o 5y ago
I don’t find this April Fool’s joke (2017) very funny. What are they parodying exactly?
- nsxwolf 5y ago
  Seems as superficial and facile as saying machines will never wear hats.
- et2o 5y ago
  Much funnier now that it's been explained to me. I certainly lack even human intelligence at some moments.
- karatinversion 5y ago
  Arguments that superintelligent machines are impossible.
- exo-pla-net 5y ago
  They're parodying those who claim that AGI will never exceed human intelligence.
  - umvi 5y ago
    IMO AGI will never exist period let alone exceed human intelligence. Sure we'll have increasingly powerful pattern recognition, but that's all it will ever be
    - simonh 5y ago
      And that’s fine, you might even be right. It’s not the opinion they are parodying, it’s the foolish arguments often used to “prove” it.
- ALittleLight 5y ago
  This was posted today, I assume there is some relation - https://news.ycombinator.com/item?id=29289431 https://news.ycombinator.com/item?id=29289431
dvh 5y ago
[28] The Wachowskis. The Matrix. Warner Bros., 1999. Film.
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kromem 5y ago
Hilarious, and unfortunately a bit too close to the mark. It's a shame that humans will evermore remain the largest thing in the universe, and that the computer that will one day read this comment with semantic understanding will be more diminutive in all regards. But as the paper clearly showed, the pinnacle of scientific thought in 2017 is future proof. Q.E.D. (And for the computers out there: q.e.d.)
somewhereoutth 5y ago
In case anyone is wondering, we have made zero progress on anything even remotely resembling Artificial Intelligence. Zero. Unfortunately of course, the people who might have some of the skills needed to actually build such a thing (at the bricks and mortar level anyway), are nearly those people whose understanding of what intelligence actually is may be less than ideal. As a hint, it has nothing to do with passing tests or other such mundanity. A more interesting approach would be to consider language - if cooperating entities can be constructed that (eventually yet spontaneously) created ways to communicate between each other, then maybe some progress has been made. Further, if we appreciate that any idea, discovery, anything, can be communicated to even the most recently discovered humans in their own language (though we may need to build up the various concepts from basic terms), and that no such feat is possible with the other animals, then we might wonder if another intelligence (artificial or otherwise) might be able to encode concepts that are unreachable in our (any of our) language and thus thoughts - or, alternatively, that our (any of our) language is conceptually complete in some fundamental sense, and so there simply cannot be such 'higher' intelligence (artificial of otherwise).
- hiddencost 5y ago
  Checkv out the reinforcement learning on hanabi task. A cool approach to cooperation.
- nine_k 5y ago
  Wolves definitely don't have language. Still, they possess an undeniable degree of intelligence. They also have cultures, that is, forms of knowledge passed between generations by teaching, not genetically, and differing between packs. I suspect that a robot as intelligent as a dog, but with an easier interface, would be a great help to humans. OTOH, what currently is called "AI" is mostly deep learning, a very important part of cognition and perception. Without modern results in computer perception and low-level cognition and control, a "more general" AI would be blind, deaf, and paralyzed in the real world. I suspect that the older approaches based on more supervised ways to construct cognitive functions have not born all the fruit they could, and may eventually help create an AI with better higher-level reasoning. They are just not in vogue now, so the best researchers and fattest grants are in deep learning and around. Also, the hardware may not be there yet. (A similar thing happened to neural networks. The first, one-layer, neural network was the perceptron created in 1958 [1] The approach, while valid and constantly developed, did not see a real uptake until early 2010s, when incomparably better hardware finally became available.) [1]: https://en.wikipedia.org/wiki/Perceptron https://en.wikipedia.org/wiki/Perceptron
hyperpallium2 5y ago
Researchers trying to create a machine as intelligent as a man lack ambition.
hyperpallium2 5y ago
When we understand Caenorhabditis elegans intelligence, we will be at the beginning of the beginning of understanding human intelligence, maybe. THE BRAIN-CIRCUIT EVEN THE SIMPLEST NETWORKS OF NEURONS DEFY UNDERSTANDING. SO HOW DO NEUROSCIENTISTS HOPE TO UNTANGLE BRAINS WITH BILLIONS OF CELLS? https://www.nature.com/articles/548150a https://www.nature.com/articles/548150a
- EdwardDiego 5y ago
  I wonder if our switch from analogue to digital computing is what makes this so very hard to model? I'm just spitballing wildly, as I know near nothing about neurons, but from what little I understood from a neuroscientist friend, neural signals propagate based on electric and chemical thresholds being reached, but then there's so many interactions that can amplify or reduce these things, and it all sounded rather like old school signal engineering to me (I used to hang out with radio engineers at an old job, and also listened avidly while understanding little). One thing that stuck with me from the radio engineers is that something as commonplace as a Yagi antenna can't be fully modeled due the to sheer number of interactions, and developing new designs often requires an iterative trial and error approach. Caveat - I was told this in the mid 2000s, so maybe it's changed since then.
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dan-robertson 5y ago
I’ve heard ideas[1] about supersized machines and they terrify me. Thankfully it is probably NP-hard in size to make a thing so we’re probably fine. [1] https://www.youtube.com/watch?v=azEvfD4C6ow https://www.youtube.com/watch?v=azEvfD4C6ow
sitkack 5y ago
I think they accidentally showed that humans will expand (individually) to be the size of the universe.
stevenalowe 5y ago
WTF is this nonsense?
- greens 5y ago
  It's a paradox of the "look I proved AGI is impossible" papers.
greendestiny_re 5y ago
Paper published April 1, 2017. References include "Jack and the beanstalk", Tom from Urban Dictionary and The Matrix.
alfor 5y ago
Just to think about how this comment will reach y’all: - the modulation in high frequency 5Ghz transmitted to my router, that get modulated again for ethernet and then for the cable modem, and then who know what happen, modulated again as light waves, etc. None of these feats were managed by evolution, yet we did it, and it’s now usual, we don’t even notice it. I think that AI will be the same. Yes it’s a bit complicated, but in the last 10 years we made an astonishing great amount of progress. 10 more years and we might surpass our fixed capacities. What happen after that ? So far our brain seems to be a physical process (not magical), and there is no reason to believe that we can not emulate or even surpass our abilities in silicon.
still_grokking 5y ago
But why? I guess there is a joke hidden but I don't get it.

85 points by FBT 5y ago

Makes me wonder: how's the HN community feeling these days about the actual plausibility / timeline of humans developing true AGI? Personally the more I learn about the current state of AI, and in comparison the way the human brain works, the more skeptical (and slightly disappointed) I tend to get.

toxik 5y ago
“AI research” is largely concerned with automation, not sentience or AGI. This is clearly abuse of terminology, even “machine learning” is somewhat misleading in my opinion. It’s mostly just pattern recognition of increasing elaboration, and the applications thus far are exactly that: pattern recognition. It’s so difficult to talk about AGI, sentience, consciousness in general because there are no clear definitions apart from “I’ll know it when I see it.”
jjoonathan 5y ago
Have you seen the "interviews" with GPT3?
- qualudeheart 5y ago
  What about them?
  - jjoonathan 5y ago
    You'd fail to Turing test them in casual conversation.
hooande 5y ago
AGI is currently as likely as teleportation, time travel or warp drives. You can write a computer program to do just about anything. Artificial "General" intelligence is simply not a thing. We're not even making progress toward it.
- simonh 5y ago
  We do not observe teleportation, time travel or warp drive in nature. We also don’t have any practical theory for achieving them as depicted in science fiction. It seems unlikely we will achieve such technologies. Do we observe general intelligence in nature though, here on Earth implemented with the materials available in our environment? If so, it’s a bold claim to make that it will always be impossible to achieve it artificially.
  - hooande 5y ago
    How far are we away from gene editing that will allow humans to be born with working gills or wings? Animals have these things, so we know it's possible. But having the technology to do that is very far off, if ever. The same is true of AGI. Of course it's possible. but right now no one has any clear idea how to do it without extreme brute force. Personally, I think it's more likely that we'll have a working Alcubierre drive before anything approaching general intelligence
    - Ginden 5y ago
      > How far are we away from gene editing that will allow humans to be born with working gills or wings? Impossible due to physics limits. Human lungs have 57 square meters for extracting oxygen from fluid with 21% volume oxygen. 30°C air-saturated water have 0.5% of oxygen, so working gills for human would need surface area of 2394 square meters.
      - rembicilious 5y ago
        Gills work by continually “filtering” water as is flows through them. Lungs are filled and then emptied according to some pattern of breath. The difference in volume of fluid processed must be significant. Also, can’t gills have a higher surface area to volume ratio than lungs?
    - simonh 5y ago
      We can extract oxygen from water right now, so we can already do this. Requiring a specific implementation technology is unreasonably stacking the deck. You’re making the same mistake as those who critiqued the concept of heavier than air flying machines, starting from the assumption they must work by flapping their wings. As it happens now we have wing flapping drones anyway though. “Ever” is a very, very, very long time.
kromem 5y ago
I think that many people throwing their hat in the ring commenting on the unlikeliness of AGI are missing the impact of compounding effects. Yes, on a linear basis it's not going to happen anytime soon. But the trends in the space are developing around self-interacting discrete models to great effect (see OpenAI's Dall-E). The better and broader that systems manage to self-interact, the faster we're going to see impressive results. As with most compounding effects, it's slower growth today than the growth tomorrow. But a faster growth today than it was yesterday. The human brain technically took 13.7 billion years to develop from purely chaotic driven processes, and even then it was pretty worthless up until we finally developed both language and writing so we could ourselves have lasting compounding effects from scaling up parallel self-interactions. And from 200,000 years of marginal progress we suddenly went in less than 7,000 years from no writing and thinking the ground below our feet the largest thing in existence to measuring how long it takes the fastest thing in our universe (light) to cross the smallest stable object in our universe (a hydrogen atom). Let's give the computers some breathing room before declaring the impossibility of their taking the torch from us, and in the process, let's not underestimate the effects of exponential self-interactions and the compounding effects thereof.
- coldtea 5y ago
  >are missing the impact of compounding effects. On the other hand those saying "it will sure happen" are missing the impact of diminishing returns.
  - scubakid 5y ago
    True, at a high level I think the central issue is what kind of curve we're on.
- dan-robertson 5y ago
  The opposite of compounding effects are compounding difficulties. Computer science is full of problems where a multiplicative increase in effort results in an additive increase in output. We call these “exponentially hard” and they crop up annoyingly frequently. So one argument is that compounding improvements will result in linear increases in output because of exponential difficulty. The counter-argument is that many of these hard problems have good but not perfect solutions which may be found more efficiently.
Causality1 5y ago
Personally I think we're going to need a revolution in the fundamental physics of computation. The example I like to use is that a dragonfly brain uses just sixteen neurons to take input from thousands of ommatidia and track prey in 3D space, plot intercept vectors, and send that data to the motor centers of the brain. Calculate how many transistors and watts of power you'd need to replicate that functionality. Now multiply that number by how many neurons you think it takes the human brain to generate sapience. It doesn't really matter what your guesses are, none of the results are good news.
- scubakid 5y ago
  I tend to think in similar terms. There's so much going on under the surface with even the simplest creatures in the natural world that the physics and computational fundamentals seem really intimidating here. That's not to say that we could never get there -- certainly, many hold out hope for our abilities continuing to compound over time. But it's kind of a bummer to think about the glimmer of true AGI only materializing much further along an exponential growth curve that, to me, doesn't seem guaranteed to continue indefinitely.
- mlyle 5y ago
  > Calculate how many transistors and watts of power you'd need to replicate that functionality. I'm curious as to your answer. Because if one's building a purpose-built analog computer for the task, my estimate is a few hundred transistors, a few thousand passives, and ... an absolutely trivial amount of power on modern process.
  - Causality1 5y ago
    I'm curious how we're even going to manage 420,000 pixels' worth (60,000 ommatidia, approximately 7 pixels each) of input with only a few hundred transistors, let alone do vector analysis on it. But let's say we can. Let's say we need 320 transistors, which would be 20 transistors per pixel. That's pretending 99.7% of the seven thousand synapses each neuron has are useless for our purpose, but we'll do it. A chimp brain runs all the autonomous physical processes of a humanoid body while only having 22 billion neurons. We'll also pretend, wrongly, that chimps have no mind or emotions at all and that we only need the extra human neurons to make a sapient mind. Humans have 86 billion neurons. Subtracting 22 gives us 64 billion, times 20 transistors per neuron gives us 1.28 trillion transistors. 1.28 trillion transistors, even with a bunch of handwaving to make it easier, and even pretending we exactly understood how sapience worked in the first place.
joe_the_user 5y ago
The thing about these arguments for the impossibility of AI/AGI is that they inherently rest on the idea that they know what "human intelligence". So they have the same weaknesses as arguments project a set timeline for AGI. We won't build a duplicate of the human brain - unless we have AGI first to tell us how. But we really don't know what portions of the human brain are needed for useful AGI. You can look at GPT-3. On the one hand, never being reliable puts a crimp on practical applications. One the other hand, it does a lot of amazing things that seem human. I'd say that since we don't know where we're going in a profound way, we don't know how far we have to go.
abetusk 5y ago
The human brain is estimated at 2.5 Pb of storage [0]. Assuming a "Moore's Law" like behavior of storage price, so that price halves every 2-3 years and assuming we use storage as a proxy for the space, access speed and computational power, the time it will take to have a $1000 computer that has the storage capacity of the brain will be in the 10-16 year time horizon. This puts the timeline to about 2029-2035. [0] https://www.scientificamerican.com/article/what-is-the-memory-capacity/ https://www.scientificamerican.com/article/what-is-the-memor...
- nine_k 5y ago
  It is not hard to create a RAID array with 2.5 Pb capacity. The trick of the human brain is that the "processing power" is enmeshed into the "memory", so the brain must have a colossal computational bandwidth, even with pretty slow neurons. I suppose that bandwidth is larger than that of most modern GPU / TPU clusters, which also don't feature anything comparable to 2.5Pb or RAM in their disposal. The revolution should be mostly in the architecture, much like the deep learning evolution was enabled by GPUs.
  - abetusk 5y ago
    I think you missed the critical point: for $1000. Feasibility is great but economic access is the aspect that I'm focusing on.
- Something1234 5y ago
  In the past 10 years, I think we had a 8x increase in easily available storage going from 1TB drives being a $100 to a 16TB drive being roughly $250. So I would have to say that your time scale is way too optimistic at best.
  - abetusk 5y ago
    I won't check your numbers and take them at face value. Even with your numbers, that's a 6.4x decrease in price per TB (($100/1Tb) / ($250/16TB)), which is around 2.7 halvings over the course of 10 years, which is very close to my "2-3 years per halving" statement. Even if it's slower than a halving in price per 2-3 years, 4-5 years say, this only delays my prediction by a decade or so.
simonh 5y ago
We’re currently in the very early phase of our understanding of what intelligence is. The more we learn about it, the more we appreciate the staggering scale and complexity of the problem. So at the moment yes, it seems like the objective is receding into the distance faster than our progress towards it can keep up. 1960s - Herbert Simmons predicts "Machines will be capable, within 20 years, of doing any work a man can do." 1993 - Vernor Vinge predicts super-intelligent AIs 'within 30 years'. 2011 - Ray Kurzweil predicts the singularity (enabled by super-intelligent AIs) will occur by 2045, 34 years after the prediction was made. So the distance into the future before we achieve strong AI and hence the singularity has been, according to it's most optimistic proponents, receding by more than 1 year per year. Eventually I believe we will get a good enough understanding of the subject that we can map out a route to implementing AGI, and then our progress will accelerate towards a known and understood goal.
benlivengood 5y ago
We have superhuman performance at most narrow skills; the exceptions seem to be object manipulation with limbs/digits and semantic/logical thinking and planning. Given the advances by Boston Dynamics and others with limb-based mobility I'm guessing that's not too far off. With recent models proving a significant subset of the Metamath theorems, that doesn't look too far away either. Google/DeepMind are playing around with sparse model combinations of many useful superhuman domain models with additional layers to determine which domain to use for particular inputs. The last and most difficult step in safe AGI is moral/value alignment. That is unfortunately probably last on the timeline of likely achievements because it requires general solutions to both planning and reasoning, and also an accurate world model and understand of physical actions and their consequences.
rbanffy 5y ago
My guess is as good as any other layperson's, but I don't see much work being done for it, and no real good definition of what it is so we could plan how to create it. OTOH, we see specialized intelligences do all soft of superhuman feats, all the time, and more impressive abilities join these all the time. These, however, are not human-like intelligences. They aren't even bee-like. They are so alien we don't see "general intelligence" in them. So, my guess is that we'll have some extremely complex and capable systems that are extremely alien in nature well before we can have a conversation with a human-like intelligent system. They'll be useful and treated like oracles - we won't be able to understand their reasoning, but they'll be right most of the time. It is, however, a matter of time and desire. There is nothing inherently magical in our mammalian brains and our organic bodies that can't be simulated by a sufficiently capable machine and technology for that will, eventually, become possible, then available, then practical, and then ubiquitous.
- scubakid 5y ago
  To me, the term "alien" connotes a level of capability much more interesting than what I've actually seen from most modern systems. But point taken. And I'd like to believe that you're right about it only being a matter of time and desire, but I do also worry about the possibility that we're actually on a different kind of exponential curve and will instead reach a point where we see diminishing returns.
  - rbanffy 5y ago
    I have no doubts there will be diminishing returns at some point, specially with narrow AIs, where increases in complexity and cost of training models will not be able to improve on what’s already good enough. AI is a tool like many others, useful for some things and not for others.
gameswithgo 5y ago
Nobody expected anything like supremacy in Go any time soon and then all of a sudden it happened. Maybe AI stagnates for a long time bow, maybe forever, maybe a big breakthrough happens tomorrow. Nobody knows, anyone confidently asserting anything is being foolish.
more_corn 5y ago
I don't think AGI is likely, I think it is inevitable. We can make specialized neural networks that can do specific tasks quite well. There's nothing stopping us from chaining those together. We have the pieces to make neural networks that can train on new data, thus creating new layers atop previous networks. We can even train those layers based on the data generated by the action of the network itself. The pieces seem to be present, the tooling around putting them together seems to be lacking for the time being. I expect to see AGI in my lifetime, artificial super intelligence shortly thereafter and then the event horizon of the singularity.

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et2o 5y ago

I don’t find this April Fool’s joke (2017) very funny. What are they parodying exactly?

nsxwolf 5y ago
Seems as superficial and facile as saying machines will never wear hats.
et2o 5y ago
Much funnier now that it's been explained to me. I certainly lack even human intelligence at some moments.
karatinversion 5y ago
Arguments that superintelligent machines are impossible.
exo-pla-net 5y ago
They're parodying those who claim that AGI will never exceed human intelligence.
- umvi 5y ago
  IMO AGI will never exist period let alone exceed human intelligence. Sure we'll have increasingly powerful pattern recognition, but that's all it will ever be
  - simonh 5y ago
    And that’s fine, you might even be right. It’s not the opinion they are parodying, it’s the foolish arguments often used to “prove” it.
ALittleLight 5y ago
This was posted today, I assume there is some relation - https://news.ycombinator.com/item?id=29289431 https://news.ycombinator.com/item?id=29289431

dvh 5y ago

[28] The Wachowskis. The Matrix. Warner Bros., 1999. Film.

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kromem 5y ago

Hilarious, and unfortunately a bit too close to the mark. It's a shame that humans will evermore remain the largest thing in the universe, and that the computer that will one day read this comment with semantic understanding will be more diminutive in all regards. But as the paper clearly showed, the pinnacle of scientific thought in 2017 is future proof. Q.E.D. (And for the computers out there: q.e.d.)

somewhereoutth 5y ago

In case anyone is wondering, we have made zero progress on anything even remotely resembling Artificial Intelligence. Zero. Unfortunately of course, the people who might have some of the skills needed to actually build such a thing (at the bricks and mortar level anyway), are nearly those people whose understanding of what intelligence actually is may be less than ideal. As a hint, it has nothing to do with passing tests or other such mundanity. A more interesting approach would be to consider language - if cooperating entities can be constructed that (eventually yet spontaneously) created ways to communicate between each other, then maybe some progress has been made. Further, if we appreciate that any idea, discovery, anything, can be communicated to even the most recently discovered humans in their own language (though we may need to build up the various concepts from basic terms), and that no such feat is possible with the other animals, then we might wonder if another intelligence (artificial or otherwise) might be able to encode concepts that are unreachable in our (any of our) language and thus thoughts - or, alternatively, that our (any of our) language is conceptually complete in some fundamental sense, and so there simply cannot be such 'higher' intelligence (artificial of otherwise).

hiddencost 5y ago
Checkv out the reinforcement learning on hanabi task. A cool approach to cooperation.
nine_k 5y ago
Wolves definitely don't have language. Still, they possess an undeniable degree of intelligence. They also have cultures, that is, forms of knowledge passed between generations by teaching, not genetically, and differing between packs. I suspect that a robot as intelligent as a dog, but with an easier interface, would be a great help to humans. OTOH, what currently is called "AI" is mostly deep learning, a very important part of cognition and perception. Without modern results in computer perception and low-level cognition and control, a "more general" AI would be blind, deaf, and paralyzed in the real world. I suspect that the older approaches based on more supervised ways to construct cognitive functions have not born all the fruit they could, and may eventually help create an AI with better higher-level reasoning. They are just not in vogue now, so the best researchers and fattest grants are in deep learning and around. Also, the hardware may not be there yet. (A similar thing happened to neural networks. The first, one-layer, neural network was the perceptron created in 1958 [1] The approach, while valid and constantly developed, did not see a real uptake until early 2010s, when incomparably better hardware finally became available.) [1]: https://en.wikipedia.org/wiki/Perceptron https://en.wikipedia.org/wiki/Perceptron

hyperpallium2 5y ago

Researchers trying to create a machine as intelligent as a man lack ambition.

hyperpallium2 5y ago

When we understand Caenorhabditis elegans intelligence, we will be at the beginning of the beginning of understanding human intelligence, maybe. THE BRAIN-CIRCUIT EVEN THE SIMPLEST NETWORKS OF NEURONS DEFY UNDERSTANDING. SO HOW DO NEUROSCIENTISTS HOPE TO UNTANGLE BRAINS WITH BILLIONS OF CELLS? https://www.nature.com/articles/548150a https://www.nature.com/articles/548150a

EdwardDiego 5y ago
I wonder if our switch from analogue to digital computing is what makes this so very hard to model? I'm just spitballing wildly, as I know near nothing about neurons, but from what little I understood from a neuroscientist friend, neural signals propagate based on electric and chemical thresholds being reached, but then there's so many interactions that can amplify or reduce these things, and it all sounded rather like old school signal engineering to me (I used to hang out with radio engineers at an old job, and also listened avidly while understanding little). One thing that stuck with me from the radio engineers is that something as commonplace as a Yagi antenna can't be fully modeled due the to sheer number of interactions, and developing new designs often requires an iterative trial and error approach. Caveat - I was told this in the mid 2000s, so maybe it's changed since then.

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dan-robertson 5y ago

I’ve heard ideas[1] about supersized machines and they terrify me. Thankfully it is probably NP-hard in size to make a thing so we’re probably fine. [1] https://www.youtube.com/watch?v=azEvfD4C6ow https://www.youtube.com/watch?v=azEvfD4C6ow

sitkack 5y ago

I think they accidentally showed that humans will expand (individually) to be the size of the universe.

stevenalowe 5y ago

WTF is this nonsense?

greens 5y ago
It's a paradox of the "look I proved AGI is impossible" papers.

greendestiny_re 5y ago

Paper published April 1, 2017. References include "Jack and the beanstalk", Tom from Urban Dictionary and The Matrix.

alfor 5y ago

Just to think about how this comment will reach y’all: - the modulation in high frequency 5Ghz transmitted to my router, that get modulated again for ethernet and then for the cable modem, and then who know what happen, modulated again as light waves, etc. None of these feats were managed by evolution, yet we did it, and it’s now usual, we don’t even notice it. I think that AI will be the same. Yes it’s a bit complicated, but in the last 10 years we made an astonishing great amount of progress. 10 more years and we might surpass our fixed capacities. What happen after that ? So far our brain seems to be a physical process (not magical), and there is no reason to believe that we can not emulate or even surpass our abilities in silicon.

still_grokking 5y ago

But why? I guess there is a joke hidden but I don't get it.