this post was submitted on 27 Apr 2025
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[–] CeeBee_Eh@lemmy.world 1 points 20 hours ago* (last edited 19 hours ago) (1 children)

keyword detection like “Hey Google” is only used to wake up a device from a low power state to perform more powerful listening

That's more applicable for something like a Google Mini. A phone is powerful enough, especially with the NPU most phones have now, to perform those detecting efficiently without stepping up the CPU state.

Is there some kink of roleplaying AI dev?

Is there some kink on your side in pretending you're smart? You have no idea who I am or what I know.

Increasing the number of keywords to thousands or more (which you would need to cover the range of possible ad topics) requires more processing power

Again, you're showing your lack of knowledge here. A model doesn't use more power if trained on one class or a hundred. The amount of cycles is the same in both instances.

It's usually smart speakers that have a low powered chip that processes the wake word and fires up a more powerful chip. That doesn't exist in phones.

Edit: just to hammer home a point. Your example of "hey Google" simply waking up the device for more complex processing just proves my point. The scenario we're talking about is the same as the wake word. We're not looking to do any kind of complex processing. We're just counting the number of times a word is triggered. That's it. No reasoning out the meaning, no performing actions, no understanding of a question and then performing a search to provide a response. It's literally a "wake-word" counter.

[–] LoveSausage@discuss.tchncs.de 1 points 8 hours ago (1 children)

No you are wrong. Seems your making things up on the go. More wake words to listen to more battery drain. Fact.

But sure lets play. Now that you used your "wake word counter" what use would that have ? You have ZERO context then. Completely useless .

[–] CeeBee_Eh@lemmy.world 1 points 6 hours ago

No you are wrong

Lol. "Nuh-uh" doesn't work with me.

https://stackoverflow.com/questions/64008486/effects-of-number-of-classes-on-inference-time-in-object-detection-api

Seems your making things up on the go

I speak from knowledge and experience. What do you bring to the table?

More wake words to listen to more battery drain. Fact.

1 trained class = 1 model

100 trained classes = 1 model

Tell me how running 1 model would drain more battery than running 1 model? I'll wait...

You have ZERO context then. Completely useless .

The person said "NIKE" a few times, show them ads for shoes. The person said "mechanic" "car" "fixed" around the same time, show them ads for local car repair shops.

You don't need the full context of what was said to get some context from just the words. The spacing in time and the revelations relationship between words can give you a whole lot of context. Plenty to target ads.

Now, either come back with something real, or go away and conceed you're out of your depth.