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DeepMind's Mustafa Suleyman says general AI is still a long way off

170 points by seycombi 10y ago

saycheese 10y ago
>> "We founded the company on the premise that many of our complex social problems are becoming increasingly stuck" Real AI will not simplify the complexities of social problems — and to believe so shows a complete lack of understanding of those problems and what real AI will become.
- maaaats 10y ago
  > and to believe so shows a complete lack of understanding of those problems and what real AI will become When the CEO of one of the most well-known AI-companies makes a claim you disagree with, you should probably give a better reason for him being wrong than "a complete lack of understanding".
  - allengeorge 10y ago
    I guess with the OP is asking is: is there a technical reason that complex social problems are getting stuck. If so, how will general AI address those problems, and how will it itself avoid the same pitfalls? It's not clear to me at all that throwing AI at a social problem somehow solves it, so...
    - meira 10y ago
      An AI that calculates how to fix social problems would suggest SV billionaries to give up their money and power. We are a long away off from this, and not technologically.
  - leereeves 10y ago
    Being CEO of an AI company doesn't mean he has a greater understanding of "social problems".
    - k__ 10y ago
      This. I mean Schmidt, Ballmer or Scully, didn't seem to have much expertise in their field.
    - patrickmn 10y ago
      "Science talks about very simple things, and asks hard questions about them. As soon as things become too complex, science can’t deal with them… But it’s a complicated matter: Science studies what’s at the edge of understanding, and what’s at the edge of understanding is usually fairly simple. And it rarely reaches human affairs. Human affairs are way too complicated." — Noam Chomsky
    - bbctol 10y ago
      To be fair, his background is in social work and public policy; Hassabis is the technical lead, Suleyman is very much focused on strategy and societal impact.
    - squeaky-clean 10y ago
      The original article title was a (now corrected) typo. Suleyman isn't CEO, but "Co-Founder & Head of Applied AI" (from their website).
  - hokkos 10y ago
    What a CEO says is not what he thinks, but what he wants you to believe. There is lot of discussions and justified fears about the future of jobs in relation with AI, so he try to make us believe his company was founded to help our social problems, but I don't believe it was, I believe it was founded because it was a mean to do cool things in their domain of expertise and earn money in the process.
  - eli_gottlieb 10y ago
    Social structures today are built out of millions of independent agents, each of whom is modelling many others in detail, but not quite accurately, while also modelling themselves somewhat more accurately, modelling the world in general at a low level-of-detail, and trying to meet their own embodied needs. There are ways to make accurate social reasoning easier (transparency, egalitarianism, precise communication, etc.), but our social structures are currently moving away from those. Adding one more agent who happens to be artificial is not going to make these social-reasoning problems any simpler.
- thinkMOAR 10y ago
  what is 'real' 'artificial' intelligence, is it real or artificial?
- simonh 10y ago
  Where did he talk about simplifying them? I must have missed that part.
skocznymroczny 10y ago
That's what he wants you to think!
sapphireblue 10y ago
Is he a CEO though? Wikipedia and other press articles say that Hassabis is the CEO: https://en.wikipedia.org/wiki/DeepMind https://en.wikipedia.org/wiki/DeepMind and Suleyman is Chief Product Officer, the head of applied AI at DeepMind.
- cybertronic 10y ago
  https://deepmind.com/about/ https://deepmind.com/about/ Hassabis is CEO
- muse900 10y ago
  he aint the CEO title is wrong.
dpandey 10y ago
The fascinating thing about his answers is that he says nothing that wasn't already known 25 years ago. 'General AI' is a really vague term and means almost nothing. It's well known in AI that common sense AI systems are incredibly hard to build and expert AI systems are relatively straight forward to model and build. Given that the most 'common sense' type products we see like Siri and Alexa still appear to be rules based systems (that have been enhanced with historical data no doubt), we all know the world is not suddenly going to become a common sense AI paradise unless a new Marvin Minsky makes some breakthroughs. I find that the term 'AI' is frequently used when a company has taken an existing problem and enhanced the solution by using machine learning at one or more places. Nothing wrong with that fundamentally, but calling that AI is more of a marketing gimmick than anything else. Google/Facebook do some of the best machine learning enhanced workflows that delight users. They usually refrain from branding it as AI.
- _pmf_ 10y ago
  What we currently observe is not a revival of AI research, but an emergent mutual exponentiation of large-scale data collection and classic statistical AI techniques. They now have a nearly infinitely customizable source of training data and verification data that can be used to train bog standard neural nets.
  - dpandey 10y ago
    Agree, except with the 'nearly infinite' qualifier. We have some large data sets now and we can draw a cat. We don't know if we can build anything interesting with those data sets yet.
  - rspeer 10y ago
    This is essentially true, and I'm sad that someone is so caught up in the hype that they'd downvote a simple description of the actual state of the field. What we have right now is a boom in AI engineering, with AI research fairly neglected because it doesn't produce the same kind of hype. Here's a Twitter thread [1] where NLP researchers describe people who work on machine translation as 'depressed', because they spend their time tweaking neural net parameters to get tiny improvements over the best techniques of last decade, with no opportunity to understand what causes an improvement. [1] https://twitter.com/haldaume3/status/805055952789573635 https://twitter.com/haldaume3/status/805055952789573635
denzil_correa 10y ago
Anyone who has spend time in AI or ML would know this is true. Currently, AI is very helpful to solve certain types of tasks. The recent advances in Deep Learning etc. is the improvement of AI to solve some of these specific tasks. A lot of people have confused this to assume there would be a master AI system that would solve general tasks. I don't see that happening anytime soon.
- datashovel 10y ago
  I think a legitimate fear, though, is that once general AI has become a reality, it's "off to the races". This, in my mind, is certainly a problem where the dialogue really should be had before-hand. I think it's no longer a matter of "if", but a matter of "when".
  - somestag 10y ago
    I've heard this argument a lot--that the first true general AI may lead to to extremely rapid advances in GAI capabilities (through one means or another), and it will be impossible to do damage control after the fact if something goes wrong because the world will change effectively overnight. This would imply that GAI is worth talking about now even if we suspect it won't happen for a long time. If we accept that GAI is far off, though, it's very likely that we simply can't have a productive conversation about it at this time. In fact, such conversations could even be counterproductive if we make incorrect assumptions, leading to the illusion of safety. Most talks about the dangers of AI assume we'll one day finally "break through" and create a metaphorical ghost in the machine, at which point all bets are off. However, this scenario seems awfully unlikely to me. Human intelligence is far beyond that of any other known organism, but there are plenty of intelligent animals on Earth, and the process of solving GAI will almost certainly produce intelligence on par with those animals before it breaks through to human-level intelligence. Dog-level intelligence is a decent milestone; at that point, we'll clearly have created GAI in the sense of creating a being that can exhibit truly "intelligent" behavior (including emotions), but it's clearly not intelligent enough to cause any problems that are specific to GAI. The rebuttal to this argument is that a generalized learning algorithm running on a computer will be far more powerful than a dog's brain, but it's fallacious to assume that the only difference between a dog and a human is the processing powers of their brains. That would imply that a bigger brain (however you choose to measure it) is all that's needed to create more intelligence. As far as we can tell, this isn't true, and architectural differences (which imply "software" differences) seem important for creating higher intelligence. When we do get to GAI, we don't know if it'll be through software running on a "normal" computer, or if it'll be running on specialized hardware in a specialized shell designed to navigate a real environment, or if it'll be in some other form that we haven't really thought of yet. The dangers and resolutions are very different between those forms, and when we don't seem close to GAI at all, it can be argued that talk about its "dangers" may be a complete waste of time, or perhaps even counterproductive to safety in the long-run.
rectang 10y ago
Step 1: State a problem. Any problem which has been articulated is vastly closer to being solved than any problem which has not. Step 2: Rescue the problem from necessitating general AI by developing an algorithm. Any problem which has been split off from general AI is vastly closer to being solved.
mark_l_watson 10y ago
I like his honesty in saying we are decades away from any general sort of AI. I remember at AAAI 1982, the conference was handing out bumper stickers saying "AI its for real" that my coworkers and I happily put on our cars. Yeah, a little optimistic:-) That said, I like the way Deep Mind is run, especially the forays into health science.
roymurdock 10y ago
DeepMind sounds more and more like IBM Watson by the day. Both created AI engines for games (Jeopardy, Go) and are now focusing on the medical market. The two examples of actual AI applications cited in the article focus on DeepMind's healthcare efforts: The company is working with the National Health Service (NHS) in the UK on a project around the early detection of acute kidney injuries. Critics, however, argue that the collaboration with DeepMind is wider than the company and the NHS previously disclosed. In addition, it’s also working with the Moorfields Eye Hospital on looking at how it can use the hospital’s eye scans to diagnose eye conditions better and faster. The NHS, however, mostly used its own algorithm in its project, with DeepMind focussing on the front-facing app. Suleyman argued that this is due to the fact that it’s still early days for this collaboration, which only started 12 months ago. So in the health space they're currently doing anomaly detection and building applications for their clients. Sounds very Watson/consulting. Lots of money in healthcare due to the amount of data generated and the complexity of building regulation-compliant. Judging from their website, they've also built an algorithm for reducing cooling energy usage in Google's data centers. There are a ton of IoT platforms that are currently competing to connect a bunch of industrial/medical/automotive/aerospace and defense devices and servers, analyze that data with machine learning and statistical techniques, make it easy for users to build their own cloud/edge applications, and eke out every last drop of efficiency they can for their customers. DeepMind is fortunate to have Google's brand, infrastructure, and reach. I'm just not sure what else separates them from any other "AI" (read machine learning/algorithm-building/efficiency consultancy) out there.
- tfgg 10y ago
  AFAIK the health stuff at DeepMind is just one part, the research division is the main bit. Not like IBM Watson consultancy-pretending-to-be-AI-research. > I'm just not sure what else separates them from any other "AI" (read machine learning/algorithm-building/efficiency consultancy) out there. probably the amount of pure research they produce: https://deepmind.com/research/publications/ https://deepmind.com/research/publications/
  - dpandey 10y ago
    Those are 2 very different things as much as we'd like to believe they're one since they're within the same company. I wouldn't be surprised if google sunsets the company and absorbs the employees in its more profitable products.
xianshou 10y ago
FYI, Mustafa Suleyman is not CEO, but rather "Co-Founder & Head of Applied AI," as described in the article. Demis Hassabis is the CEO.
- sctb 10y ago
  Thanks, we've updated the submission title.
airesQ 10y ago
People with high-profile jobs are severely constrained in what they can say (even though this guy is not the CEO, contrary to what the title claims ATM). And we already saw that google doesn't want to touch the "uglier" aspects of ML/AI/robotics with a ten-foot-pole (e.g. see how they reacted to Boston Dynamics's humanoid robot video). So I'm not sure if we should take this seriously. DeepMind technical views are mostly on its papers. Not press statements.
- dpandey 10y ago
  Really good point. He might just be following google's PR directives. Also, while their research team is ostensibly doing great work, maybe the product team doesn't have much to show or claim after all. Which CEO/exec wouldn't want to make a tall claim about their product or company while on stage (that they can reasonably back up if questioned)?
cr0sh 10y ago
I personally think that if "general AI" (that is, something akin to human-level or beyond, and possibly sentient) ever happens - it'll happen by accident, and will be an emergent phenomenon that we won't be able to explain. It will surprise all of us, and will likely be a "earth-shaking", akin to an extra-terrestrial alien contact. Perhaps even more so - because it would be a hard example against the idea of dualism (unless it arises from a quantum computing system - then humans can posit an "out" of course, regardless of whether it is true or not). All pure speculation, of course. I honestly don't think we'll be able to "design" a general AI - we don't even understand how sentience and consciousness (among other things in the philosophy of mind) even works or exists in human brains. We understand the gears and wheels, but can't describe the factory.
curiousgal 10y ago
Curious to know about his technical expertise, he's listed as an entrepreneur who dropped out of college.
patkai 10y ago
It's quite shocking that even technical people think AI is "a" thing, and will "come" at a certain time.
socmag 10y ago
I totally agree with the general sentiment of the comments and the article that AGI is a long way off... in the anthropomorphic sense we usually imagine. That said in many regards, the sum total of the internet, social networks and automated systems that already exist, to me is fast beginning to resemble an emergent AGI / ASI, and furthermore is already out and about busy doing its business. That it just happens to use networks, humans and machines as cells and DNA seems kind of irrelevant. Of course this is a silly POV thought experiment, but seriously, if that were the case, would we even notice? I'm not sure our own cells and DNA know they are part of a larger entity for example. Okay, enough weird thoughts.. time for bed.
ilaksh 10y ago
I thought Hassabis said he was seriously trying to build grounded AGI based on some type of system with deep learning-ish stuff. I think it will work within around a dozen years or so. How do they know that they can't take their current deep learning-type techniques or some variation/enhancement of them and apply them to more demanding and general circumstances? For example, they have the agent that goes around trying to score in a 3d first-person-shooter with the pixels as input. Has it been determined that there isn't a way to gradually train that system to recognize words, phrases, or even sentences that would give it hints about how to score better, maybe by associating words with other (spatial/navigation) parts of the model or more general association between aspects of the learning system in different domains. To me it seems like some type of deep learning (or maybe a variant using spiking neurons since those can reportedly learn with fewer examples?) when grounded by integrated sensory inputs of different times and incrementally trained, may be able to already exhibit general animal/human-like intelligence, or will be able to with one or two minor 'breakthroughs'. I'm still going with 2029 (as suggested by Kurzweil I think).

170 points by seycombi 10y ago

>> "We founded the company on the premise that many of our complex social problems are becoming increasingly stuck" Real AI will not simplify the complexities of social problems — and to believe so shows a complete lack of understanding of those problems and what real AI will become.

maaaats 10y ago
> and to believe so shows a complete lack of understanding of those problems and what real AI will become When the CEO of one of the most well-known AI-companies makes a claim you disagree with, you should probably give a better reason for him being wrong than "a complete lack of understanding".
- allengeorge 10y ago
  I guess with the OP is asking is: is there a technical reason that complex social problems are getting stuck. If so, how will general AI address those problems, and how will it itself avoid the same pitfalls? It's not clear to me at all that throwing AI at a social problem somehow solves it, so...
  - meira 10y ago
    An AI that calculates how to fix social problems would suggest SV billionaries to give up their money and power. We are a long away off from this, and not technologically.
- leereeves 10y ago
  Being CEO of an AI company doesn't mean he has a greater understanding of "social problems".
  - k__ 10y ago
    This. I mean Schmidt, Ballmer or Scully, didn't seem to have much expertise in their field.
  - patrickmn 10y ago
    "Science talks about very simple things, and asks hard questions about them. As soon as things become too complex, science can’t deal with them… But it’s a complicated matter: Science studies what’s at the edge of understanding, and what’s at the edge of understanding is usually fairly simple. And it rarely reaches human affairs. Human affairs are way too complicated." — Noam Chomsky
  - bbctol 10y ago
    To be fair, his background is in social work and public policy; Hassabis is the technical lead, Suleyman is very much focused on strategy and societal impact.
  - squeaky-clean 10y ago
    The original article title was a (now corrected) typo. Suleyman isn't CEO, but "Co-Founder & Head of Applied AI" (from their website).
- hokkos 10y ago
  What a CEO says is not what he thinks, but what he wants you to believe. There is lot of discussions and justified fears about the future of jobs in relation with AI, so he try to make us believe his company was founded to help our social problems, but I don't believe it was, I believe it was founded because it was a mean to do cool things in their domain of expertise and earn money in the process.
- eli_gottlieb 10y ago
  Social structures today are built out of millions of independent agents, each of whom is modelling many others in detail, but not quite accurately, while also modelling themselves somewhat more accurately, modelling the world in general at a low level-of-detail, and trying to meet their own embodied needs. There are ways to make accurate social reasoning easier (transparency, egalitarianism, precise communication, etc.), but our social structures are currently moving away from those. Adding one more agent who happens to be artificial is not going to make these social-reasoning problems any simpler.
thinkMOAR 10y ago
what is 'real' 'artificial' intelligence, is it real or artificial?
simonh 10y ago
Where did he talk about simplifying them? I must have missed that part.

skocznymroczny 10y ago

That's what he wants you to think!

sapphireblue 10y ago

Is he a CEO though? Wikipedia and other press articles say that Hassabis is the CEO: https://en.wikipedia.org/wiki/DeepMind https://en.wikipedia.org/wiki/DeepMind and Suleyman is Chief Product Officer, the head of applied AI at DeepMind.

cybertronic 10y ago
https://deepmind.com/about/ https://deepmind.com/about/ Hassabis is CEO
muse900 10y ago
he aint the CEO title is wrong.

dpandey 10y ago

The fascinating thing about his answers is that he says nothing that wasn't already known 25 years ago. 'General AI' is a really vague term and means almost nothing. It's well known in AI that common sense AI systems are incredibly hard to build and expert AI systems are relatively straight forward to model and build. Given that the most 'common sense' type products we see like Siri and Alexa still appear to be rules based systems (that have been enhanced with historical data no doubt), we all know the world is not suddenly going to become a common sense AI paradise unless a new Marvin Minsky makes some breakthroughs. I find that the term 'AI' is frequently used when a company has taken an existing problem and enhanced the solution by using machine learning at one or more places. Nothing wrong with that fundamentally, but calling that AI is more of a marketing gimmick than anything else. Google/Facebook do some of the best machine learning enhanced workflows that delight users. They usually refrain from branding it as AI.

_pmf_ 10y ago
What we currently observe is not a revival of AI research, but an emergent mutual exponentiation of large-scale data collection and classic statistical AI techniques. They now have a nearly infinitely customizable source of training data and verification data that can be used to train bog standard neural nets.
- dpandey 10y ago
  Agree, except with the 'nearly infinite' qualifier. We have some large data sets now and we can draw a cat. We don't know if we can build anything interesting with those data sets yet.
- rspeer 10y ago
  This is essentially true, and I'm sad that someone is so caught up in the hype that they'd downvote a simple description of the actual state of the field. What we have right now is a boom in AI engineering, with AI research fairly neglected because it doesn't produce the same kind of hype. Here's a Twitter thread [1] where NLP researchers describe people who work on machine translation as 'depressed', because they spend their time tweaking neural net parameters to get tiny improvements over the best techniques of last decade, with no opportunity to understand what causes an improvement. [1] https://twitter.com/haldaume3/status/805055952789573635 https://twitter.com/haldaume3/status/805055952789573635

denzil_correa 10y ago

Anyone who has spend time in AI or ML would know this is true. Currently, AI is very helpful to solve certain types of tasks. The recent advances in Deep Learning etc. is the improvement of AI to solve some of these specific tasks. A lot of people have confused this to assume there would be a master AI system that would solve general tasks. I don't see that happening anytime soon.

datashovel 10y ago
I think a legitimate fear, though, is that once general AI has become a reality, it's "off to the races". This, in my mind, is certainly a problem where the dialogue really should be had before-hand. I think it's no longer a matter of "if", but a matter of "when".
- somestag 10y ago
  I've heard this argument a lot--that the first true general AI may lead to to extremely rapid advances in GAI capabilities (through one means or another), and it will be impossible to do damage control after the fact if something goes wrong because the world will change effectively overnight. This would imply that GAI is worth talking about now even if we suspect it won't happen for a long time. If we accept that GAI is far off, though, it's very likely that we simply can't have a productive conversation about it at this time. In fact, such conversations could even be counterproductive if we make incorrect assumptions, leading to the illusion of safety. Most talks about the dangers of AI assume we'll one day finally "break through" and create a metaphorical ghost in the machine, at which point all bets are off. However, this scenario seems awfully unlikely to me. Human intelligence is far beyond that of any other known organism, but there are plenty of intelligent animals on Earth, and the process of solving GAI will almost certainly produce intelligence on par with those animals before it breaks through to human-level intelligence. Dog-level intelligence is a decent milestone; at that point, we'll clearly have created GAI in the sense of creating a being that can exhibit truly "intelligent" behavior (including emotions), but it's clearly not intelligent enough to cause any problems that are specific to GAI. The rebuttal to this argument is that a generalized learning algorithm running on a computer will be far more powerful than a dog's brain, but it's fallacious to assume that the only difference between a dog and a human is the processing powers of their brains. That would imply that a bigger brain (however you choose to measure it) is all that's needed to create more intelligence. As far as we can tell, this isn't true, and architectural differences (which imply "software" differences) seem important for creating higher intelligence. When we do get to GAI, we don't know if it'll be through software running on a "normal" computer, or if it'll be running on specialized hardware in a specialized shell designed to navigate a real environment, or if it'll be in some other form that we haven't really thought of yet. The dangers and resolutions are very different between those forms, and when we don't seem close to GAI at all, it can be argued that talk about its "dangers" may be a complete waste of time, or perhaps even counterproductive to safety in the long-run.

rectang 10y ago

Step 1: State a problem. Any problem which has been articulated is vastly closer to being solved than any problem which has not. Step 2: Rescue the problem from necessitating general AI by developing an algorithm. Any problem which has been split off from general AI is vastly closer to being solved.

mark_l_watson 10y ago

I like his honesty in saying we are decades away from any general sort of AI. I remember at AAAI 1982, the conference was handing out bumper stickers saying "AI its for real" that my coworkers and I happily put on our cars. Yeah, a little optimistic:-) That said, I like the way Deep Mind is run, especially the forays into health science.

roymurdock 10y ago

DeepMind sounds more and more like IBM Watson by the day. Both created AI engines for games (Jeopardy, Go) and are now focusing on the medical market. The two examples of actual AI applications cited in the article focus on DeepMind's healthcare efforts: The company is working with the National Health Service (NHS) in the UK on a project around the early detection of acute kidney injuries. Critics, however, argue that the collaboration with DeepMind is wider than the company and the NHS previously disclosed. In addition, it’s also working with the Moorfields Eye Hospital on looking at how it can use the hospital’s eye scans to diagnose eye conditions better and faster. The NHS, however, mostly used its own algorithm in its project, with DeepMind focussing on the front-facing app. Suleyman argued that this is due to the fact that it’s still early days for this collaboration, which only started 12 months ago. So in the health space they're currently doing anomaly detection and building applications for their clients. Sounds very Watson/consulting. Lots of money in healthcare due to the amount of data generated and the complexity of building regulation-compliant. Judging from their website, they've also built an algorithm for reducing cooling energy usage in Google's data centers. There are a ton of IoT platforms that are currently competing to connect a bunch of industrial/medical/automotive/aerospace and defense devices and servers, analyze that data with machine learning and statistical techniques, make it easy for users to build their own cloud/edge applications, and eke out every last drop of efficiency they can for their customers. DeepMind is fortunate to have Google's brand, infrastructure, and reach. I'm just not sure what else separates them from any other "AI" (read machine learning/algorithm-building/efficiency consultancy) out there.

tfgg 10y ago
AFAIK the health stuff at DeepMind is just one part, the research division is the main bit. Not like IBM Watson consultancy-pretending-to-be-AI-research. > I'm just not sure what else separates them from any other "AI" (read machine learning/algorithm-building/efficiency consultancy) out there. probably the amount of pure research they produce: https://deepmind.com/research/publications/ https://deepmind.com/research/publications/
- dpandey 10y ago
  Those are 2 very different things as much as we'd like to believe they're one since they're within the same company. I wouldn't be surprised if google sunsets the company and absorbs the employees in its more profitable products.

xianshou 10y ago

FYI, Mustafa Suleyman is not CEO, but rather "Co-Founder & Head of Applied AI," as described in the article. Demis Hassabis is the CEO.

sctb 10y ago
Thanks, we've updated the submission title.

airesQ 10y ago

People with high-profile jobs are severely constrained in what they can say (even though this guy is not the CEO, contrary to what the title claims ATM). And we already saw that google doesn't want to touch the "uglier" aspects of ML/AI/robotics with a ten-foot-pole (e.g. see how they reacted to Boston Dynamics's humanoid robot video). So I'm not sure if we should take this seriously. DeepMind technical views are mostly on its papers. Not press statements.

dpandey 10y ago
Really good point. He might just be following google's PR directives. Also, while their research team is ostensibly doing great work, maybe the product team doesn't have much to show or claim after all. Which CEO/exec wouldn't want to make a tall claim about their product or company while on stage (that they can reasonably back up if questioned)?

cr0sh 10y ago

I personally think that if "general AI" (that is, something akin to human-level or beyond, and possibly sentient) ever happens - it'll happen by accident, and will be an emergent phenomenon that we won't be able to explain. It will surprise all of us, and will likely be a "earth-shaking", akin to an extra-terrestrial alien contact. Perhaps even more so - because it would be a hard example against the idea of dualism (unless it arises from a quantum computing system - then humans can posit an "out" of course, regardless of whether it is true or not). All pure speculation, of course. I honestly don't think we'll be able to "design" a general AI - we don't even understand how sentience and consciousness (among other things in the philosophy of mind) even works or exists in human brains. We understand the gears and wheels, but can't describe the factory.

curiousgal 10y ago

Curious to know about his technical expertise, he's listed as an entrepreneur who dropped out of college.

patkai 10y ago

It's quite shocking that even technical people think AI is "a" thing, and will "come" at a certain time.

socmag 10y ago

I totally agree with the general sentiment of the comments and the article that AGI is a long way off... in the anthropomorphic sense we usually imagine. That said in many regards, the sum total of the internet, social networks and automated systems that already exist, to me is fast beginning to resemble an emergent AGI / ASI, and furthermore is already out and about busy doing its business. That it just happens to use networks, humans and machines as cells and DNA seems kind of irrelevant. Of course this is a silly POV thought experiment, but seriously, if that were the case, would we even notice? I'm not sure our own cells and DNA know they are part of a larger entity for example. Okay, enough weird thoughts.. time for bed.

ilaksh 10y ago

I thought Hassabis said he was seriously trying to build grounded AGI based on some type of system with deep learning-ish stuff. I think it will work within around a dozen years or so. How do they know that they can't take their current deep learning-type techniques or some variation/enhancement of them and apply them to more demanding and general circumstances? For example, they have the agent that goes around trying to score in a 3d first-person-shooter with the pixels as input. Has it been determined that there isn't a way to gradually train that system to recognize words, phrases, or even sentences that would give it hints about how to score better, maybe by associating words with other (spatial/navigation) parts of the model or more general association between aspects of the learning system in different domains. To me it seems like some type of deep learning (or maybe a variant using spiking neurons since those can reportedly learn with fewer examples?) when grounded by integrated sensory inputs of different times and incrementally trained, may be able to already exhibit general animal/human-like intelligence, or will be able to with one or two minor 'breakthroughs'. I'm still going with 2029 (as suggested by Kurzweil I think).