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Message: <blockquote data-quote="DarkKestral" data-source="post: 4017112" data-attributes="member: 40100">The AI could work safely in environments impossible for humans, prosfilaes, and would be easily capable of improving it's own intelligence, as well as potentially working longer and more continuously, as well as be able to control and monitor more variables than a human, and likely be cheaper to train. That's kind of why companies are already building neural nets: they are cheaper than paying humans to do repetitive, high-calculation, or high-risk jobs and are generally far better at performing the job requirements anyway, and are far cheaper to make better. Need more reliability at a job? Spend thousands of dollars training humans for uncertain speedups, or spend 10s of thousands more to hire more, or spend only 2-3k and a minor extra electricity cost adding processors to the AI. To illustrate: the archetypal example of when to use an AI as opposed to a human is spaceflight. An AI in a high-gee rocket is going to be much less costly to train and equip for space operation than a human; the human explorer would have sentimental value, but the AI would train faster, be more efficient, be more difficult to destroy, and given something of a probe and a knowledge of it's own architecture, could potentially repair itself or make copies once at the landing site, enabling faster and cheaper exploration. Another example is nuclear power. When dealing with nuclear power, an AI is more attentive to reactor conditions and will be more efficient at preventing alarms, so investment there means a longer reactor lifetime and safer operating conditions for the humans involved.As far as worrying about Moore's Law not being valid over the next few years, given current transistor technology, we've got a lot of time before we hit the point at which it reaches it's physical minimum size, at least as far as manuacturing goes. So it's more a matter of figuring out how to manufacture ever smaller transistors en masse. I believe the absolute maximum was reached in a lab a few years ago, but it's several orders of magnitude smaller that what we use in major manufacturing. Therefore, it could be assumed that we'd hit the practical tipping point well before we run out of our 'more transistors' space, as the tipping point is several orders of magnitude closer than the practical limit of our technology. A far more practical concern is heat, but even that is getting worked on, in the form of smaller heat pipes and on-chip watercooling to keep cores from overheating.</blockquote>

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