So this machine learning and deep learning hype has shown that it is a gimmick isn't it? After years of surveilling, collecting and training on user data it still doesn't work or gets attacked very easily over spoilt pixels and many other attacks?
What a complete waste of time, money and CO2 being burned up in the data centers.
I don't know.... I think back on google search back in the ~2014 era. It was good. Like scary good. Like I'd type "B" and it would suggest "Btu to Joules conversion" and things like that. Actually it was better than that... it would anticipate things I hadn't even searched for before with very very little prompting. It seemed to adapt to context whether I was at work, on my phone, at home, etc. The results were exactly what I was looking for.
Then it got taken over by ads and SEO and corrupting influences and it's just not that good anymore. IMO, the problem with DL isn't the tech. It's the way its being used. The reality is: For 99% of things advertised to me, I don't want to buy the goddamn product, and no amount of advertising will make me want to buy it. It's gotten to the point where if I see an ad for a product I think I'm more likely to buy a competitor whose ad I haven't seen because I assume the competitor is investing more in the product than the marketing.
And everyone seems to have forgotten about hybrid approaches of ML and human beings that, IMO, are really good. But alas, "they don't scale".
But at the same time, it's really interesting. For as much data as facebook should have about me, their ad rec's really suck and always have. (Perhaps it's because my only ad clicks ever are accidental ones?) I'm kind of astounded at how poor that result is. That said, I'm always very impressed by spotify's recommender system. I think it's one of the best on the net.
Another thing I find interesting is that non-vote-based social media feed systems all really suck. Once they ditched chronological ordering it stopped appealing to me, and I don't know exactly why that is. Evidently I'm on some tail of the curve they don't care about.
No, it just isn't a silver bullet for every problem under the sun. But quite a few record holders on various problems are ML solutions and that is unlikely to change for the foreseeable future.
It's just that as soon as you start out on every problem with 'ML will solve this!' that you're going to end up with a bunch of crap. The right tool for the problem wins every time.
What a complete waste of time, money and CO2 being burned up in the data centers.