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<blockquote data-quote="Amiga500" data-source="post: 1165322" data-attributes="member: 56767"><p>AI can not easily recognise when a piece of fruit is sufficiently ripe, or diseased, or needing a change in diet - as lighting conditions are not similar in the real world.</p><p></p><p>That does not begin to cover the process of say, removing shoots off plants through the growth process. So there is (i) recognising the shoot [not trivial for a computer, sometimes not trivial for a human!] then (ii) manipulating the plant such that the shoot can be removed without damaging the main plant [often not trivial for a human to detangle, significantly complex for a computer], (iii) cutting the shoot from the main plant and (iv) removing the now detached shoot from the main plant without damaging it [can be different to (ii)].</p><p></p><p>That is just one example of where AI isn't there, because you'll never be able to make a simple learning model for steps (ii) and (iv) - there are many possible routes to a success and even more possible routes to a failure. The learning model would almost be in a chess environment, except there are no fixed rules for the game or opponent.</p></blockquote><p></p>
[QUOTE="Amiga500, post: 1165322, member: 56767"] AI can not easily recognise when a piece of fruit is sufficiently ripe, or diseased, or needing a change in diet - as lighting conditions are not similar in the real world. That does not begin to cover the process of say, removing shoots off plants through the growth process. So there is (i) recognising the shoot [not trivial for a computer, sometimes not trivial for a human!] then (ii) manipulating the plant such that the shoot can be removed without damaging the main plant [often not trivial for a human to detangle, significantly complex for a computer], (iii) cutting the shoot from the main plant and (iv) removing the now detached shoot from the main plant without damaging it [can be different to (ii)]. That is just one example of where AI isn't there, because you'll never be able to make a simple learning model for steps (ii) and (iv) - there are many possible routes to a success and even more possible routes to a failure. The learning model would almost be in a chess environment, except there are no fixed rules for the game or opponent. [/QUOTE]
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