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Sure, our models have close to no intelligence. They're just automating what we've trained them to do. But that power makes them extremely useful in the real world. Just not a panacea.
I see too many people taking the stance "ML does not magically solve every problem, therefore we shouldn't use it". Instead, engineers in every industry should be asking, "what can I do with ML?", while keeping in mind its limitations. Turns out, there's *a lot* you can do.
I agree! It would really help people to tell them that, even if ML for their application is only nibbling around the edges or can’t solve the one percent problem, it can be much better than nothing.
Totally agree, I think the "ML Bashing" in his large majority come in reaction of "ML, IA" overhyping. Stop to oversell for marketing, ML can already do wonderful things, you don't need to pretend "it pass the Turing test" or anything else to do something good with it.
The steam engine did not allow us to make a mechanical horse, yet by engineering the right systems around it, we created locomotives and railroads. Sometimes, the world requires re-engineering the problems to leverage better tools.
I disagree. Asking "what can I do with ML?" is a bad question to be asking. Similar to "what problem can I solve with this product?" The important thing is always to understand the problem. Finding what tool you need to solve it comes later. /1
If you start by choosing your tool and looking for problems, it's like "having a hammer and everything starts to look like nails". In many scenarios ML is an overcomplication and a simpler solution exists. When you do find a good use-case for it, then of course use ML!
I think many people also dismiss it because it does things that people don't want it to do. Sometimes the model should just say I don't know rather than being highly confident about the wrong answer.
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