4 ms·

And yet 30 years we could do all that with a whole lot of if statements. It would just return false positives a lot more. A couple of others have replied saying

And yet 30 years we could do all that with a whole lot of if statements. It would just return false positives a lot more. A couple of others have replied saying the same thing as you that this is 'AI', but it's not. As soon as you try to use it for something it wasn't programmed for, it fails. It doesn't even understand what it is doing right now. This isn't me 'moving the goalposts' either, we have literally never achieved anything close to AI. It baffles me that people think this is even remotely AI to be honest.

haser_au 10y ago
Have a read of this; http://waitbutwhy.com/2015/01/artificial-intelligence-revolution-1.html http://waitbutwhy.com/2015/01/artificial-intelligence-revolu... It's a very long read, but it will give you a much better overview of AI and the different "calibres" than I could possibly try to in a HN comment. What Mark has used here is "Artificial Narrow Intelligence (ANI)", the first of three levels/calibres of AI. Level 2 is "Artificial General Intelligence (AGI)", otherwise known as "Human Level AI". And level 3 is "Artificial Superintelligence (ASI)" which is "“an intellect that is much smarter than the best human brains in practically every field, including scientific creativity, general wisdom and social skills.” [Quote: Nick Bostrom].
- hacker_9 10y ago
  sigh this is why I don't usually get involved in arguments about whether something is considered AI or not; it just devolves into people trying to define and redefine what the word 'AI' even means. Final word: I follow this stuff closely and read the research articles, and what we currently have is really great, but it's still just pulling the wool over your eyes. These techniques and algorithms trick you into thinking they are intelligent when in fact they are anything but. What we have now is a parlour trick in comparison to what the brain is doing. When true AI actually comes along, no one will doubt it.
  - ecopoesis 10y ago
    I was unaware that we knew how how human intelligence works. </sarcasm> If we can build systems that can fool us into thinking their intelligent (which I will agree that outside of limited scopes we have not), then we built intelligence.
  - deleted 10y ago
    [deleted]
  - enobrev 10y ago
    To be fair, I fool people into thinking I'm intelligent all the time.
    - sdenton4 10y ago
      Superintelligence will be achieved by: a) Training a system to trick the smartest people on the planet that it's smart, and then b) Asking it to prove itself by solving the Riemann hypothesis.
  - joesb 10y ago
    Or may be you give your brain too much credits.
  - causalmachine 10y ago
    @hacker_9 ('A') Albeit, the human brain calculates roughly 10^16 to 10^18 synaptic operations per second. (Exascale Computation) THIS DAY, artificial neural models calculate 10^14+ synaptic operations per second. BY EXTENSION, artificial cognitive models have reduced larger number of cognitive tasks, as time diverged, in tandem with enhanced parallelism. THUSLY, exascale artificial neural models are but likely by 2020. (Moore's Law) It requires not Einsteinian intellect, such that one observes the prior sequence. SOLELY IDIOTS/THEISTS FAIL TO COMPUTE THE AFORESAID. . . . . . . ('B') By extension, artificial intelligence is enhancing exponentially, particularly on the order of Moore's Law. Here are a sequence COGNITIVE fields/tasks, where sophisticated ARTIFICIAL NEURAL models EXCEED mankind: 1) Language translation (eg: Skype 50+ languages) 2) Legal-conflict-resolution (eg: 'Watson') 3) Self-driving (eg: 'OTTO-Self Driving' ) 5) Disease diagnosis (eg: 'Watson') 6) Medicinal drug prescription (eg: 'Watson') 7) Visual Product Sorting (eg: 'Amazon Corrigon' ) 8) Help Desk Assistance ('eg: Digital Genius) 9) Mechanical Cucumber Sorting (eg: 'Makoto's Cucumber Sorter') 10) Financial Analysis (eg: 'SigFig') 11) E-Discovery Law (eg: ' Social Science Research Network.') 12) Anesthesiology (eg: 'SedaSys') 13) Music composition (eg: 'Emily') 14) Go (eg: 'Alpha Go') ... https://www.youtube.com/watch?v=P_-wn8ghcoY https://www.youtube.com/watch?v=P_-wn8ghcoY https://m.youtube.com/watch?v=7Pq-S557XQU https://m.youtube.com/watch?v=7Pq-S557XQU
  - TeMPOraL 10y ago
    I agree. What I see we have now is lots of bricks - often overly problem-specific (and it's important to stress this; a lot of things that get called "AI" in the news is really lots of compute thrown at super specific heuristics). To call it AI, we still need to connect them together into a system that can use those components to learn and solve problems it didn't see before, without bricking itself in the process.
  - ethbro 10y ago
    > parlour trick in comparison to what the brain is doing That's a good turn of phrase, because it speaks to the real rub between algorithmic insufficiency and hardware insufficiency. From my reading, it seems fair to say that "strong general AI" will require some product of both to be realized and that our current hardware capabilities likely fall short of the minimum requirement (even with optimal algorithms). Were they imagining exascale computing when Quicksort was dreamed up in 1959? No. But does that make it any less important?
mynameisvlad 10y ago
There's a difference between a strong/general AI, which is what you call AI and a weak AI, which is what the rest of the world calls current AIs. An AI doesn't need to do something it wasn't programmed for or understand what it's doing to count as one.
tim333 10y ago
You couldn't do face or voice recognition 30 years ago with if statements.
- Twisell 10y ago
  Theoretically you could, but as you were actually limited by hardware (camera resolution, CPU, etc...) anyway nobody really tried.
- sorbits 10y ago
  According to [1] there was a system in 1968 that “consistently outperformed humans when presented with the same recognition tasks”. As someone who was into programming and electronics in the eighties, I also feel a need to object whenever people say things like “we thought it was AI until we could make a computer do it, and now it’s just math” (paraphrasing). We (those of us interested in the subject back then) had a pretty good idea about what would be possible in the future (because of faster machines and more storage) and what would not be possible in the future (unless a breakthrough was made in understanding intelligence). Now, I do think we underestimated how fast things have developed, and especially the resources people have access today via the internet, but none of what I have seen today would have been classified as AI by myself back in the eighties. [1] https://en.wikipedia.org/wiki/Facial_recognition_system#History https://en.wikipedia.org/wiki/Facial_recognition_system#Hist...
  - tim333 10y ago
    I also mucked around with computers in the 80s and agree with most of that. I guess a lot of whether stuff is AI comes down to how you define it. The Oxford English Dict has: >[mass noun] The theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages. So obviously by that speech and Zucks type of face recognition are AI. I note the '68 system was hybrid and required humans to measure the faces and enter data for where the features are so it was more analysing numbers. There was actually speech recognition software in the 80s but it used a neural network approach rather than if statements and didn't work terribly well https://www.wired.com/2013/11/tech-time-warp-of-the-week-ibms-speech-savvy-computer-1986/ https://www.wired.com/2013/11/tech-time-warp-of-the-week-ibm... Human level thinking type AI is obviously still to come.

haser_au 10y ago

Have a read of this; http://waitbutwhy.com/2015/01/artificial-intelligence-revolution-1.html http://waitbutwhy.com/2015/01/artificial-intelligence-revolu... It's a very long read, but it will give you a much better overview of AI and the different "calibres" than I could possibly try to in a HN comment. What Mark has used here is "Artificial Narrow Intelligence (ANI)", the first of three levels/calibres of AI. Level 2 is "Artificial General Intelligence (AGI)", otherwise known as "Human Level AI". And level 3 is "Artificial Superintelligence (ASI)" which is "“an intellect that is much smarter than the best human brains in practically every field, including scientific creativity, general wisdom and social skills.” [Quote: Nick Bostrom].

hacker_9 10y ago
sigh this is why I don't usually get involved in arguments about whether something is considered AI or not; it just devolves into people trying to define and redefine what the word 'AI' even means. Final word: I follow this stuff closely and read the research articles, and what we currently have is really great, but it's still just pulling the wool over your eyes. These techniques and algorithms trick you into thinking they are intelligent when in fact they are anything but. What we have now is a parlour trick in comparison to what the brain is doing. When true AI actually comes along, no one will doubt it.
- ecopoesis 10y ago
  I was unaware that we knew how how human intelligence works. </sarcasm> If we can build systems that can fool us into thinking their intelligent (which I will agree that outside of limited scopes we have not), then we built intelligence.
- deleted 10y ago
  [deleted]
- enobrev 10y ago
  To be fair, I fool people into thinking I'm intelligent all the time.
  - sdenton4 10y ago
    Superintelligence will be achieved by: a) Training a system to trick the smartest people on the planet that it's smart, and then b) Asking it to prove itself by solving the Riemann hypothesis.
- joesb 10y ago
  Or may be you give your brain too much credits.
- causalmachine 10y ago
  @hacker_9 ('A') Albeit, the human brain calculates roughly 10^16 to 10^18 synaptic operations per second. (Exascale Computation) THIS DAY, artificial neural models calculate 10^14+ synaptic operations per second. BY EXTENSION, artificial cognitive models have reduced larger number of cognitive tasks, as time diverged, in tandem with enhanced parallelism. THUSLY, exascale artificial neural models are but likely by 2020. (Moore's Law) It requires not Einsteinian intellect, such that one observes the prior sequence. SOLELY IDIOTS/THEISTS FAIL TO COMPUTE THE AFORESAID. . . . . . . ('B') By extension, artificial intelligence is enhancing exponentially, particularly on the order of Moore's Law. Here are a sequence COGNITIVE fields/tasks, where sophisticated ARTIFICIAL NEURAL models EXCEED mankind: 1) Language translation (eg: Skype 50+ languages) 2) Legal-conflict-resolution (eg: 'Watson') 3) Self-driving (eg: 'OTTO-Self Driving' ) 5) Disease diagnosis (eg: 'Watson') 6) Medicinal drug prescription (eg: 'Watson') 7) Visual Product Sorting (eg: 'Amazon Corrigon' ) 8) Help Desk Assistance ('eg: Digital Genius) 9) Mechanical Cucumber Sorting (eg: 'Makoto's Cucumber Sorter') 10) Financial Analysis (eg: 'SigFig') 11) E-Discovery Law (eg: ' Social Science Research Network.') 12) Anesthesiology (eg: 'SedaSys') 13) Music composition (eg: 'Emily') 14) Go (eg: 'Alpha Go') ... https://www.youtube.com/watch?v=P_-wn8ghcoY https://www.youtube.com/watch?v=P_-wn8ghcoY https://m.youtube.com/watch?v=7Pq-S557XQU https://m.youtube.com/watch?v=7Pq-S557XQU
- TeMPOraL 10y ago
  I agree. What I see we have now is lots of bricks - often overly problem-specific (and it's important to stress this; a lot of things that get called "AI" in the news is really lots of compute thrown at super specific heuristics). To call it AI, we still need to connect them together into a system that can use those components to learn and solve problems it didn't see before, without bricking itself in the process.
- ethbro 10y ago
  > parlour trick in comparison to what the brain is doing That's a good turn of phrase, because it speaks to the real rub between algorithmic insufficiency and hardware insufficiency. From my reading, it seems fair to say that "strong general AI" will require some product of both to be realized and that our current hardware capabilities likely fall short of the minimum requirement (even with optimal algorithms). Were they imagining exascale computing when Quicksort was dreamed up in 1959? No. But does that make it any less important?

mynameisvlad 10y ago

There's a difference between a strong/general AI, which is what you call AI and a weak AI, which is what the rest of the world calls current AIs. An AI doesn't need to do something it wasn't programmed for or understand what it's doing to count as one.

tim333 10y ago

You couldn't do face or voice recognition 30 years ago with if statements.

Twisell 10y ago
Theoretically you could, but as you were actually limited by hardware (camera resolution, CPU, etc...) anyway nobody really tried.
sorbits 10y ago
According to [1] there was a system in 1968 that “consistently outperformed humans when presented with the same recognition tasks”. As someone who was into programming and electronics in the eighties, I also feel a need to object whenever people say things like “we thought it was AI until we could make a computer do it, and now it’s just math” (paraphrasing). We (those of us interested in the subject back then) had a pretty good idea about what would be possible in the future (because of faster machines and more storage) and what would not be possible in the future (unless a breakthrough was made in understanding intelligence). Now, I do think we underestimated how fast things have developed, and especially the resources people have access today via the internet, but none of what I have seen today would have been classified as AI by myself back in the eighties. [1] https://en.wikipedia.org/wiki/Facial_recognition_system#History https://en.wikipedia.org/wiki/Facial_recognition_system#Hist...
- tim333 10y ago
  I also mucked around with computers in the 80s and agree with most of that. I guess a lot of whether stuff is AI comes down to how you define it. The Oxford English Dict has: >[mass noun] The theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages. So obviously by that speech and Zucks type of face recognition are AI. I note the '68 system was hybrid and required humans to measure the faces and enter data for where the features are so it was more analysing numbers. There was actually speech recognition software in the 80s but it used a neural network approach rather than if statements and didn't work terribly well https://www.wired.com/2013/11/tech-time-warp-of-the-week-ibms-speech-savvy-computer-1986/ https://www.wired.com/2013/11/tech-time-warp-of-the-week-ibm... Human level thinking type AI is obviously still to come.