> Machine Learning is driving all of the ad placement on major ad platforms
And the results are, as far as I can see, horrible. I mean yes, if I make a mistake to search for shoes on Google, half of the internet will be showing me shoe ads for the next 6 months (how many feet do you think I have? Do you think I buy shoes in dozens?) - but presenting it as the triumph of ML is IMHO an overreach.
> personalization on all top social/media apps
From what I see, the same apps struggle to not get sued because of the said personalization regularly pushes sex content on kids, triggers on snowflakes and election interference on potential voters. Or at least that's what I hear every time next round of censorship is introduced into the social media. Somehow I am still not seeing a cause for celebration here.
> search ranking for google
Same as above, plus one shouldn't use Google search anyway. Use DuckDuckGo.
> translation, speech recognition
OK, here it got pretty good results, though sometimes it is as good as a very drunk chimp who got into a dictionary store, but in many other times it's decent. You get this one.
> finance, fraud detection
As a consumer, haven't noticed it. 100% of fraud on my cards have been detected by me reviewing my credit card statements. 100% of fraud alerts by banks have been false positives. I do not begrudge that specifically, I'd better have false positives than more fraud, but not seeing much ML-driven progress there tbh.
> In the next decade it will start taking over computer graphics, medicine, manufacturing, surveillance, hardware / software and every other aspect of our lives.
Not sure what "computer graphics" means, medicine probably not, surveillance maybe, but that's exactly the opposite of what I'd want, software definitely not even close, for the rest I'm not even sure what you're talking about.
> here's a ton of recent research showing that you can use machine learning to beat human crafted heuristics in hardware, scheduling, compiler design and query planning.
I'll believe it when I see ML-driven code generator doing something useful without tight supervision by humans. I can believe ML doing specific heuristics better (heck, doing exactly that has been part of my job recently) but there's a huge difference between "figure out exactly how much sugar makes the specific cookie recipe taste the best" and "invent whole cookie recipe from scratch and bake the cookie". I am sure ML would be useful for the former, for the latter... I'll believe it when I see it.
Machine learning is interesting in computer graphics for denoising path traced images för example. There also some uses in game developmemt where graphicsl artefacts might be detected during automated test runs instead of having an army of QA people.
Pretty sure ML have shown promising results in cancer classification in images (such as xray, etc). Not sure how this will pan out but the limited scope seems ideal .
Having worked in this industry for a while I just want to point out that the vast majority of fraud detection is done for the merchant, not the customer.
And the results are, as far as I can see, horrible. I mean yes, if I make a mistake to search for shoes on Google, half of the internet will be showing me shoe ads for the next 6 months (how many feet do you think I have? Do you think I buy shoes in dozens?) - but presenting it as the triumph of ML is IMHO an overreach.
> personalization on all top social/media apps
From what I see, the same apps struggle to not get sued because of the said personalization regularly pushes sex content on kids, triggers on snowflakes and election interference on potential voters. Or at least that's what I hear every time next round of censorship is introduced into the social media. Somehow I am still not seeing a cause for celebration here.
> search ranking for google
Same as above, plus one shouldn't use Google search anyway. Use DuckDuckGo.
> translation, speech recognition
OK, here it got pretty good results, though sometimes it is as good as a very drunk chimp who got into a dictionary store, but in many other times it's decent. You get this one.
> finance, fraud detection
As a consumer, haven't noticed it. 100% of fraud on my cards have been detected by me reviewing my credit card statements. 100% of fraud alerts by banks have been false positives. I do not begrudge that specifically, I'd better have false positives than more fraud, but not seeing much ML-driven progress there tbh.
> In the next decade it will start taking over computer graphics, medicine, manufacturing, surveillance, hardware / software and every other aspect of our lives.
Not sure what "computer graphics" means, medicine probably not, surveillance maybe, but that's exactly the opposite of what I'd want, software definitely not even close, for the rest I'm not even sure what you're talking about.
> here's a ton of recent research showing that you can use machine learning to beat human crafted heuristics in hardware, scheduling, compiler design and query planning.
I'll believe it when I see ML-driven code generator doing something useful without tight supervision by humans. I can believe ML doing specific heuristics better (heck, doing exactly that has been part of my job recently) but there's a huge difference between "figure out exactly how much sugar makes the specific cookie recipe taste the best" and "invent whole cookie recipe from scratch and bake the cookie". I am sure ML would be useful for the former, for the latter... I'll believe it when I see it.