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One area of AI is pattern recognition. If a machine could reasonably understand AVERAGE people speaking commands, we could find that many (most?) service jobs would dissapear. All those McDonnald's cashiers could be replaced with a machine. Likewise, really reliable pattern recognition could make grocery checkout automated; put your stuff on the conveyor belt and it gets scanned and summed automagically. Construction machinery could be automated, and so on.
In other words, people wouldn't be needed in jobs that depend on our understanding of commands and visual recognition of items.
While I can see the up side of this, I personally hope it doesn't happen for a LONG time. Like the industrial revolution, many folks will be displaced, and have to look for careers somewhere else. When retail stores divest themselves of all but one or two humans, when the last manual farm jobs are replaced by recognizing machines, will that be a utopia or a disaster?
In other words, people wouldn't be needed in jobs that depend on our understanding of commands and visual recognition of items.
While I can see the up side of this, I personally hope it doesn't happen for a LONG time. Like the industrial revolution, many folks will be displaced, and have to look for careers somewhere else. When retail stores divest themselves of all but one or two humans, when the last manual farm jobs are replaced by recognizing machines, will that be a utopia or a disaster?
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hi everyone,
ai depends on something called fuzzy logic which which are basically comparators with positive and negative feedbacks. This enables the comparator to learn a very simple task thus acting like one brain cell. Thus if you look at the human brain there is the vision part, hearing part, speech part and motion part. The only part that has not been solved is the capability to integrate all these systems to work together thus enabling a robot that can behave and learn like a human.
Yours Sincerely
Richard West
ai depends on something called fuzzy logic which which are basically comparators with positive and negative feedbacks. This enables the comparator to learn a very simple task thus acting like one brain cell. Thus if you look at the human brain there is the vision part, hearing part, speech part and motion part. The only part that has not been solved is the capability to integrate all these systems to work together thus enabling a robot that can behave and learn like a human.
Yours Sincerely
Richard West
I haven't kept up with research in neural nets, but it seems like most of the research is made in how to simulate a single neuron, and how to feed-back correct answers so they can learn.
But in real brains, it sure seems like the interconnections are the big deal. After all, if we have neurons and cats have neurons, why don't cats learn like we do? It isn't likely that just having MORE neurons makes you smarter. It isn't likely that our neurons are 'better' then theirs. It seems more likely that ours are interconnected better, or that we have neurons devoted to tasks that they don't have, and 'devoted' implies the arrangement, not the quantity.
But in real brains, it sure seems like the interconnections are the big deal. After all, if we have neurons and cats have neurons, why don't cats learn like we do? It isn't likely that just having MORE neurons makes you smarter. It isn't likely that our neurons are 'better' then theirs. It seems more likely that ours are interconnected better, or that we have neurons devoted to tasks that they don't have, and 'devoted' implies the arrangement, not the quantity.
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