Earlier quoted context omitted.
> AI is nonsense. Dijkstra was right. Define AI first. One of the first few lines on Wikipedia about AI: The scope of AI is disputed: as machines become increasingly capable, tasks considered as requiring "intelligence" are often removed from the definition, a phenomenon known as the AI effect, leading to the quip, "AI is whatever hasn't been done yet."
I believe that intelligence is more than quantifiable. Von Neumann machines, no matter how complex, will never achieve intelligence. Again, to be completely clear, I’m not claiming machine intelligence is impossible, just that what we see presently isn’t it in any honest sense.
The rise of 'pseudo-AI': how tech firms quietly use humans to do bots' work
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Re: The rise of 'pseudo-AI': how tech firms quietly use humans to do bots' work
#22Does this include Uber's human drivers?
Re: The rise of 'pseudo-AI': how tech firms quietly use humans to do bots' work
#23Just the latest incarnation of the good old Mechanical Turk: https://en.wikipedia.org/wiki/The_Turk
One of the services that you can use to implement pseudo-AI is also called that. See https://aws.amazon.com/documentation/mturk/
Re: The rise of 'pseudo-AI': how tech firms quietly use humans to do bots' work
#24Re: The rise of 'pseudo-AI': how tech firms quietly use humans to do bots' work
#25Not sure guardian understands how training AI works.
There is a difference between labeling training data and just using humans to do the work. Some things cannot be achieved yet even with lots of labeled training data but companies are pretending they have solved hard ML problems at a high level of performance when the technology and research aren't there yet.
Of course, the privacy concerns are there, but then again, if it's a real "AI", then it may be worse for the computer to read your data than for a random low paid worker ;)
Re: The rise of 'pseudo-AI': how tech firms quietly use humans to do bots' work
#26Earlier quoted context omitted.
I believe that intelligence is more than quantifiable. Von Neumann machines, no matter how complex, will never achieve intelligence. Again, to be completely clear, I’m not claiming machine intelligence is impossible, just that what we see presently isn’t it in any honest sense.
What do you even mean by "Von Neumann machines, no matter how complex, will never achieve intelligence."? If you mean machines that self-replicate, then there're plenty counterexamples around already ( https://www.xkcd.com/387/ ). If you mean computers using the von Neumann architecture, then that's weirdly specific, since modern computers are at best vaguely inspired by that model, and GPUs in particular work very d…
Re: The rise of 'pseudo-AI': how tech firms quietly use humans to do bots' work
#27Earlier quoted context omitted.
There is a difference between labeling training data and just using humans to do the work. Some things cannot be achieved yet even with lots of labeled training data but companies are pretending they have solved hard ML problems at a high level of performance when the technology and research aren't there yet.
But why should it matter for customers who does the job? I mean, if you don't tell anybody, and pretend it's 100% AI then it's bad, but if it "will eventually become AI", and your investors and everybody interested in the technical details know how it's actually done, then what's wrong? A true "AI" should be able to pass a Turing test, so for the customer, it should be indistinguishable, and shouldn't matter. Of cour…
Re: The rise of 'pseudo-AI': how tech firms quietly use humans to do bots' work
#28AI is nonsense. Dijkstra was right. I'm not saying that silicon/mechanical intelligence isn't possible. I'm unaware of any physical law that precludes it. But what we currently call "AI" is just the pathetic fallacy run wild. All that said, multidimensional data-driven linear recognizers are pretty impressive.
Re: The rise of 'pseudo-AI': how tech firms quietly use humans to do bots' work
#29Re: The rise of 'pseudo-AI': how tech firms quietly use humans to do bots' work
#30Great to see the Guardian referencing back to Spinvox here, whose speech-to-text service turned out to be largely run be sweatshop workers in the Phillipines; and a warning from history: This shtick works as long as you can transition to AI. If not, then the service will become increasingly flaky until the business collapses.
The business model "use low-paid labor to service wealthy clients" seems a little more inherently stable than that. In most cases, nobody expects a collapse. Why in speech-to-text?