[silisili]

I've been trying to avoid controversy lately, but hey, here's one to downvote.

Have we considered AI and ML as a general brain replacement is a failed idea? That we humans feel we are so smart we can recreate or exceed millions of year evolution of a human brain?

I'd never call AI a waste, it's not. But getting it to do human things just may be.

Even a child can tell the difference between a human of any color and an ape. How many billions have been spent trying, and failing, to exceed the bar of the thoughts of a human child?

[SilverRed]

No it isn't a failed idea at all. The products out today are remarkably useful even if not perfect. I have tested out the google lens thing on google photos and it is astounding.

I took a photo of the water pump from a car windscreen wiper and google was able to correctly identify what it was. I took a photo of a generic PCB which showed the back of a driver board for an LCD and google was able to bring up the exact type of board it was with the names of the ICs on it.

In these examples, google photos ai has far exceeded what the average human can achieve. We just have to keep in mind that these systems are not perfect and only a best guess which should be verified by a person later.

The problem here is not that the mistake was very costly or disruptive to the function of the feature, but that the mistake was highly offensive which is something very hard to avoid.

[silisili]

The problems it solved for you are immensely useful to you, but not remarkable IMO.

The problem it's solving is that it can do things that somebody with zero experience cannot. If you had an auto parts pro, or an EE, they probably could have done the same for you.

So, in general, AI is helpful because it has a much larger breadth of knowledge. Granted.

But I want examples of it doing depth, too.

My wife uses Lens when we fish. It's way, way worse than a fisherman with any experience at all.

[SilverRed]

Regardless, it is still far beyond a "failed idea" since it provides genuine value and achieves at a higher level than the average human for many topics. It isn't as you say better than an expert but the fact that for free I get something that works well is remarkable to me considering this is cutting edge technology.

[silisili]

Please read my premise again. I only called it a failed idea in the sense it could act as well as a human brain.

I said it's not a waste. Not at all, I use it in a lot of the ways you describe.

[ShamelessC]

> Have we considered AI and ML as a general brain replacement is a failed idea?

Yes. It is currently known to fail at this prospect. It is an open research question as to whether current methods can be merely "scaled up" using more compute to achieve "general brain replacement". I personally am skeptical about that considering basic problems such as concept drift (but I am by no means an expert).

You define what constitutes as valuable to be arbitrarily difficult/inconceivable with current methods (because it's an area of open research) and then say we should divert course merely because we don't know it's possible?

> never call AI a waste, it's not. But getting it to do human things just may be.

It already can do things thought to be previously exclusively "human" (such as beating Go). Recently it also helped make significant advancements for protein folding which are sure to yield benefits to medical science at least indirectly. I believe this statement is either incorrect, or you're expecting people to have some strange definition of "exclusively human", which is of course also open research and unanswered.

[3grdlurker]

Couldn’t you apply the same way of thinking to finding a cure for AIDS, or doing interstellar travel, or P = NP, or pretty much any problem that we haven’t solved yet? Just because we can’t solve a problem within our lifetime doesn’t mean it’s not solvable at all. This is one of the most basic principles by which knowledge, and therefore, technology, progresses.

[silisili]

Not at all. If a child could solve the AIDS issue and science couldn't, then maybe.

Humans and machines are so different today. Of course machines beat us at number calculations and such. But we have organs that computers don't and can't have. And our brains are much more in tune with using those than power of 2 bit twiddling.

As we ourselves don't understand how it works, how can we ever write a machine that does?

[3grdlurker]

Well how do you know that the image recognition error is a fault of the ML algorithm (because we can’t capture how organic minds learn, as you are suggesting) and not of the learning sample?

[e_proxus]

Given the complexity of the solutions employed in this space and the task we’re trying to get them to solve (or perhaps, the solutions we’re looking for problems to) I’m not that surprised.

Taken to the extreme, AI code is essentially something like:

  add(M, N) {
    return M + N + rand();
  }

In addition, being tested with a (in relation to the complete set) very small set of input data.