[crazygringo]

...Google Translate? Photos search? Gmail autocomplete? YouTube recs? Heck, Waymo?

I can't think of any other company that has produced more ML that I actually use daily. (Well, I don't use Waymo... yet.)

So I really don't know what you're talking about. And presumably they're not jumping into public versions of chat and image synthesis like ChatGPT and Stable Diffusion because they're busy figuring out how to apply them in ways that will actually make boatloads of money.

Oh, and pretty sure Search uses tons of ML as well... they just don't go around talking about it because they don't really need to.

[temikus]

Google Translate / Waymo is fair, I totally forgot about those ones.

Gmail Autocomplete, Photos Classification, YouTube recommendations are (relatively) simple models and don’t differentiate from the market much.

The thing that bothers me is that Google has been promising market-beating ML-as-a-service for ages which never materialised despite billions being poured into it.

Google Prediction API has been a great start in the area. Then Google stopped improving it and killed it with very little notice and without providing an alternative.

[Karunamon]

I think we're probably really stretching the definition of ML with things like YouTube recommendations. I don't know about you but I find them to be transparent in how they work and actively useless (either irrelevant to my interests or the video I just watched, or a swathe of other stuff I've already seen) most of the time.

Algorithmic and ML are two different things.