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It is not a bubble, in the sense that once it is bound to abruptly "pop". It is also not a scam, in the sense that there is no value. It _IS_, however, on the

It is not a bubble, in the sense that once it is bound to abruptly "pop". It is also not a scam, in the sense that there is no value. It _IS_, however, on the Gartner hype cycle (look it up in Google Images if you don't know it), and way to the left of the "plateau of productivity" where technologies like Java and python and smartphones and solar panels are. It is probably near the "Peak of Inflated Expectations", headed for the "Trough of Disillusionment". Which does not make it a bubble or a scam. Just overhyped. Part of the learning curve is figuring out where it is useful and appropriate, and that is mostly in areas where decades of conventional, non-ML efforts have not paid off.

elisharobinson 7y ago
its an interesting argument you are proposing. but i feel AI/ML is not a normal tech trend because they are non deterministic systems. A normal tech trend would hit "plateau" after the "magic" or mystery fades away . But non deterministic systems there is a good chance your walking of a on a misty mountaintop with a very high chance of irreparable damage where the cornerstone of agile quick fix build patch is not possible. or you stumble upon the a stairway to heaven where the possibilities and potential for growth seem limit less.
- rossdavidh 7y ago
  One of the most fundamental lessons one has to learn with AI/ML, is that it will never be 100%. Of course, that is true with conventional programming as well, but when a failure is found that particular bug is fixed, and one has the illusion that the problem which was just fixed was the last one, and _now_ it is 100% reliable. But, with ML, it will never, ever be 100%. In some potential applications, this is ok, or in any case the alternatives are 100% _not_ working so it's the best there is. But in other potential applications, this is a deal-breaker, actually or politically. Part of finding the "plateau of productivity", is that organizations learn lessons like this, about where you can and cannot use it effectively.

elisharobinson 7y ago

its an interesting argument you are proposing. but i feel AI/ML is not a normal tech trend because they are non deterministic systems. A normal tech trend would hit "plateau" after the "magic" or mystery fades away . But non deterministic systems there is a good chance your walking of a on a misty mountaintop with a very high chance of irreparable damage where the cornerstone of agile quick fix build patch is not possible. or you stumble upon the a stairway to heaven where the possibilities and potential for growth seem limit less.

rossdavidh 7y ago
One of the most fundamental lessons one has to learn with AI/ML, is that it will never be 100%. Of course, that is true with conventional programming as well, but when a failure is found that particular bug is fixed, and one has the illusion that the problem which was just fixed was the last one, and _now_ it is 100% reliable. But, with ML, it will never, ever be 100%. In some potential applications, this is ok, or in any case the alternatives are 100% _not_ working so it's the best there is. But in other potential applications, this is a deal-breaker, actually or politically. Part of finding the "plateau of productivity", is that organizations learn lessons like this, about where you can and cannot use it effectively.