On the other hand, there’s a lot of real problems that real people actually deal with that just need a logistic regression to save million bucks here and there. I like that space more.
Writing TFX code at Google is like having your soul-sucked through your rear-end! Imagine TF1 with all the broken APIs, but now it's all distributed! Fun.
I laugh-snorted reading that! I am stealing that phrase.
I don't think the FAANGs will ever come up with AGI and I am glad for that. If the private sector gets there first, I am going to "accidentally" die of hypothermia on a hiking trip because I will do anything not to live in their world.
A common thing I do is say company X has a fleet of Y assets. They repair them every N years. A good solution would be to predict which ones need repairs. Do those ones more often. Do the healthy ones less often. Pay more attention to the ones that are valuable.
Better outcomes, millions less spending. Probably don’t even need a live model in prod. Just a semi annual manual export run to excel for some planner guy who’s been keeping the schedule for 2 decades
For those of us who don't work at such scale, can you (maybe with a little fuzziness to avoid telling too much about an internal project) give a few examples of the kind of projects where a fairly simple model can have a 1M+ impact?
Interesting examples, and yes, they're all the kind of thing that might not justify the effort for an ML model (and might not have enough data to train) for a small website or operation, but can easily justify the cost and effort when you have a huge number of transactions.
On another note, this is why I often like lightening talks. So many people think that what they're doing falls below the threshold for what is an interesting presentation, when in fact it's the most relevant thing a lot of people will see at a conference.
What I refer to for my work is the low hanging fruit. Old problems that businesses solve with manpower or overly unspecific rules. Something where just a little clarity can help them hone their efforts on the 80/20 of it all. I made a slightly more detailed post in an adjacent response