Lol. My dude, I’m a developer who specializes in AI.
It would cost trillions
I have no clue how you came to that number. I could (and partially have) whipped up a prototype in a few days.
half the battery life
Hardly. Does Google assistant half battery life? No, so why would this? Besides, you would just need to listen to the mic and record audio only if the sound is above a certain volume threshold. Then once every few hours batch process the audio. Then send the resulting text data (in the KBs) up to a server.
The average ad data that’s downloaded for in-app display is orders of magnitude larger than what would be uploaded.
there are plenty of people that can find shit in the noise on wireshark
How are they going to see data that’s encrypted and bundled with other innocuous data?
Litarally all your questions are answered in the link i pointed out twice now. Try it. Hey google doesnt take much 1k wake words a lot more… your math doesnt add up anywhere close to reality.
I don’t have any questions. This is something I know a lot about at a very technical level.
The difference between one wake word and one thousand is marginal at most. At the hardware level the mic is still listening non-stop, and the audio is still being processed. It *has" to do that otherwise it wouldn’t be able to look for even one word. And then from there it doesn’t matter if it’s one word or 10k. It’s still processing the audio data through a model.
And that’s the key part, it doesn’t matter if the model has one output or thousands, the data still bounces through each layer of the network. The processing requirements are exactly the same (assuming the exact same model).
Seems you don’t, and started your line with a question and continued to do so despite being provided with answers repeatedly . Is there some kink of roleplaying AI dev? You don’t really seem to have done your homework to do so.
Despite what some believe, keyword detection like “Hey Google” is only used to wake up a device from a low power state to perform more powerful listening, it’s not helpful for data tracking. 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 and therefore defeats the purpose. Your battery would drain very noticeably if your phone was always listening for thousands of possible words.
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.
Lol. My dude, I’m a developer who specializes in AI.
I have no clue how you came to that number. I could (and partially have) whipped up a prototype in a few days.
Hardly. Does Google assistant half battery life? No, so why would this? Besides, you would just need to listen to the mic and record audio only if the sound is above a certain volume threshold. Then once every few hours batch process the audio. Then send the resulting text data (in the KBs) up to a server.
The average ad data that’s downloaded for in-app display is orders of magnitude larger than what would be uploaded.
How are they going to see data that’s encrypted and bundled with other innocuous data?
Litarally all your questions are answered in the link i pointed out twice now. Try it. Hey google doesnt take much 1k wake words a lot more… your math doesnt add up anywhere close to reality.
I don’t have any questions. This is something I know a lot about at a very technical level.
The difference between one wake word and one thousand is marginal at most. At the hardware level the mic is still listening non-stop, and the audio is still being processed. It *has" to do that otherwise it wouldn’t be able to look for even one word. And then from there it doesn’t matter if it’s one word or 10k. It’s still processing the audio data through a model.
And that’s the key part, it doesn’t matter if the model has one output or thousands, the data still bounces through each layer of the network. The processing requirements are exactly the same (assuming the exact same model).
This is the part you simply do not understand.
Seems you don’t, and started your line with a question and continued to do so despite being provided with answers repeatedly . Is there some kink of roleplaying AI dev? You don’t really seem to have done your homework to do so.
Despite what some believe, keyword detection like “Hey Google” is only used to wake up a device from a low power state to perform more powerful listening, it’s not helpful for data tracking. 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 and therefore defeats the purpose. Your battery would drain very noticeably if your phone was always listening for thousands of possible words.
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 on your side in pretending you’re smart? You have no idea who I am or what I know.
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.