But I am sure the aim of the demo was not to pass the Turing test, but to demonstrate the power of the software. A simpler chatbot replying to any IM after a pause of some 30 seconds with a selection of random phrases like “erm, sory iam busy at the moment” or “sorry, busy now, speak to u later”, “lagged, sorry”, or just “()-: “, would defeat even the most determined “hunter of bots”.

On the other hand I am sure the LL can easily detect un-official client text viewers if they really wanted – regardless of who is operating it, human or AI.

Still I am much exited about the possibilities. Well done David.

But I am sure the aim of the demo was not to pass the Turing test, but to demonstrate the power of the software. A simpler chatbot replying to any IM after a pause of some 30 seconds with a selection of random phrases like “erm, sory iam busy at the moment” or “sorry, busy now, speak to u later”, “lagged, sorry”, or just “()-: “, would defeat even the most determined “hunter of bots”.

On the other hand I am sure the LL can easily detect un-official client text viewers if they really wanted – regardless of who is operating it, human or AI.

Still I am much exited about the possibilities. Well done David.

Yeah, paging John Searle. I’m on the other side of that, though, myself; if in talking to a robot for awhile I found myself having to take the intentional stance toward it, I would freely (and even ecstatically) grant that it had intelligence, was a person (if it claimed to me), and all that sort of thing. The only point I’m making is that we’re very far from knowing how to do that yet (and that AIML, for instance, is a red herring, and not a step along the right road).

Yeah, paging John Searle. I’m on the other side of that, though, myself; if in talking to a robot for awhile I found myself having to take the intentional stance toward it, I would freely (and even ecstatically) grant that it had intelligence, was a person (if it claimed to me), and all that sort of thing. The only point I’m making is that we’re very far from knowing how to do that yet (and that AIML, for instance, is a red herring, and not a step along the right road).

That would indeed be a challenging thing to do, partly because it must be admitted that AI still fails quite dramatically to live up to the promises the industry has made since 1950, but also because of several other obstacles.

If you did not believe flying machines were possible, and I show you a working helicopter, you would sound a bit daft replying ‘oh that is just an imitation of flight. It is not REALLY flying’. On the other hand, if I present a robot or a chatbot that appears to have full intelligence, you could argue that it is all smoke-and-mirrors, a clever illusion. Nobody home, so to speak.

Critics are forever changing their mind as to what demonstrates intelligence, as and when AI succeeds in knocking down prior barriers. So, they said ‘no computer will ever play chess’. Then, when computers did play chess they said ‘oh. Well, no computer will ever play championship-level chess’. Garry Kasparov was defeated and the response was ‘well, obviously you do not need to be intelligent to play chess’. This suggests the future will not see the arrival of intelligent machines, but only the admission that nothing humans do actually requires intelligence;)

Whenever narrow AI succeeds in performing a task that once required a human, it stops being called AI and gets spun off into its own field. Because of this, people wonder whatever happened to AI, even though tens of thousands of AI applications are silently beavering away, making modern life possible.

All in all, I think people will still be denying the possibility of artificial general intelligence, long after the goal has finally be achieved.

That would indeed be a challenging thing to do, partly because it must be admitted that AI still fails quite dramatically to live up to the promises the industry has made since 1950, but also because of several other obstacles.

If you did not believe flying machines were possible, and I show you a working helicopter, you would sound a bit daft replying ‘oh that is just an imitation of flight. It is not REALLY flying’. On the other hand, if I present a robot or a chatbot that appears to have full intelligence, you could argue that it is all smoke-and-mirrors, a clever illusion. Nobody home, so to speak.

Critics are forever changing their mind as to what demonstrates intelligence, as and when AI succeeds in knocking down prior barriers. So, they said ‘no computer will ever play chess’. Then, when computers did play chess they said ‘oh. Well, no computer will ever play championship-level chess’. Garry Kasparov was defeated and the response was ‘well, obviously you do not need to be intelligent to play chess’. This suggests the future will not see the arrival of intelligent machines, but only the admission that nothing humans do actually requires intelligence;)

Whenever narrow AI succeeds in performing a task that once required a human, it stops being called AI and gets spun off into its own field. Because of this, people wonder whatever happened to AI, even though tens of thousands of AI applications are silently beavering away, making modern life possible.

All in all, I think people will still be denying the possibility of artificial general intelligence, long after the goal has finally be achieved.

I think we can all agree that bots used only for purposes of traffic fraud are not a good thing. And we have all been frustated by those automated call centers. But, you name me any technology that worked perfectly right from the start? How are we to perfect anything with an ‘oh this does not work now, so ban it!’ attitude?

‘Linear thinking is how machines and not real people think’.

Uhuh. Well, of course we can all point to kitchen utensils and argue quite persuasively that such things do not think or have consciousness. And we can all recite the differences between a Pc and a brain.

But what about future technologies? One area of R+D known as neuromorphic modelling seeks to design hardware/software that uses reverse-engineered principles of operation derived from living brains, or organs like the eye (which, actually, is part of the brain). As just one example, Joe Tsien is professor of pharmacology and biomedical engineering, director of the Centre for Systems Neurobiology at Boston University, and he explained:

‘we and other computer engineers are beginning to apply what we have learned about the organization of the brain’s memory system to the design of an entirely new generation of intelligent computers’.

Ranma may presume that ‘machines use linear thinking, period’. But the biological machine that is the human being already refutes this assumption, and NBIC does seem to have the potential to reverse engineer it and produce new generations of machines that blur the distinction between nature and technology.

Online worlds like SL represent the bare beginnings of this blurring.

I think we can all agree that bots used only for purposes of traffic fraud are not a good thing. And we have all been frustated by those automated call centers. But, you name me any technology that worked perfectly right from the start? How are we to perfect anything with an ‘oh this does not work now, so ban it!’ attitude?

‘Linear thinking is how machines and not real people think’.

Uhuh. Well, of course we can all point to kitchen utensils and argue quite persuasively that such things do not think or have consciousness. And we can all recite the differences between a Pc and a brain.

But what about future technologies? One area of R+D known as neuromorphic modelling seeks to design hardware/software that uses reverse-engineered principles of operation derived from living brains, or organs like the eye (which, actually, is part of the brain). As just one example, Joe Tsien is professor of pharmacology and biomedical engineering, director of the Centre for Systems Neurobiology at Boston University, and he explained:

‘we and other computer engineers are beginning to apply what we have learned about the organization of the brain’s memory system to the design of an entirely new generation of intelligent computers’.

Ranma may presume that ‘machines use linear thinking, period’. But the biological machine that is the human being already refutes this assumption, and NBIC does seem to have the potential to reverse engineer it and produce new generations of machines that blur the distinction between nature and technology.

Online worlds like SL represent the bare beginnings of this blurring.