[deleted]
ML is not that good at predicting consumers' choices
21–30 of 228 posts
Re: ML is not that good at predicting consumers' choices
#22You just bought a washing machine... could I interest you in a washing machine?
Re: ML is not that good at predicting consumers' choices
#23So 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.
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.
Re: ML is not that good at predicting consumers' choices
#24While not exactly aligned to the research, I've been surprised how poor Nest Thermostat's learning feature is. The main selling point for Nest is having a "learning thermostat". Perhaps my schedule is just not predictable enough, but the auto-generated temperature schedules it generates after its "learning" period is not even close to what I would manually set up on a normal thermostat. Maybe I'm just an "edge case"…
It is bad. I dislike most "smart" things though, so take my agreement with a grain of salt.
Re: ML is not that good at predicting consumers' choices
#25While not exactly aligned to the research, I've been surprised how poor Nest Thermostat's learning feature is. The main selling point for Nest is having a "learning thermostat". Perhaps my schedule is just not predictable enough, but the auto-generated temperature schedules it generates after its "learning" period is not even close to what I would manually set up on a normal thermostat. Maybe I'm just an "edge case"…
I also hate how Nest only let me download at most 7 days of "historical" data. They have the rest of my historical data, but I can't get a copy of my own data.
Presumably they don't want the average consumer to be aware of that fact.
Re: ML is not that good at predicting consumers' choices
#26This review omits techniques from reinforcement learning (especially bandits) that have been used successfully in industry for years now.
Re: ML is not that good at predicting consumers' choices
#27> Currently, we are still far from a point where machines are able to abstract high-level concepts from data or engage in reasoning and reflection
Of course when an AI does that, we then say its just doing statistics, not reasoning.
Until you have built a recommendation engine from scratch, it is hard to appreciate the complexity. I don't mean the complexity of the code or algorithm (ALS and Spark are straightforward enough) but the contextual problem. Models end up being large collections of models in a complex hierarchy, with hyperparams to tune higher level concepts such as "surprise" or business targets such as "revenue", "engagement" etc. TikTok have nailed this, as has Spotify.
Re: ML is not that good at predicting consumers' choices
#28So 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.
Re: ML is not that good at predicting consumers' choices
#29I can personally vouch that Amazon, Twitter, and YouTube all do horrible horrible jobs predicting my taste. And they have got worse over the years, not better
Re: ML is not that good at predicting consumers' choices
#30While not exactly aligned to the research, I've been surprised how poor Nest Thermostat's learning feature is. The main selling point for Nest is having a "learning thermostat". Perhaps my schedule is just not predictable enough, but the auto-generated temperature schedules it generates after its "learning" period is not even close to what I would manually set up on a normal thermostat. Maybe I'm just an "edge case"…
Things like this are exactly why I went with less "intelligent" smart thermostat. (Honeywell T9) The only learning feature it has is figuring out how long it takes to heat or cool the house given the current weather. Before a schedule change, can heat or cool the house so it hits next target temperature on time. This seems to work extremely well. Everything else like schedule and away settings are configured by the u…
Building my own thermostat so I have total control was a fun project, I learned a lot about electrical engineering and built a circuit with some TRIACs to control the HVAC lines. Though I still need to give it an interface so I can program it some way other than uploading the program as a JSON blob to my raspberry pi!