So I was trying to think how I’d implement it, and I agree if it’s simple then it really only needs to set the brightness level once, then remember if the user adjusts it, and reuse that adjustment for every lux reading.
Hence the example I gave:
Take the ambient light level (lux).
Set brightness to 5.
Log that the user has made it 1 level or 10% darker.
Next time it senses the same lux level, set the brightness 1 level lower
If we’re very generous with definitions it’s like a threeish neuron neutral network. Camera outputs might level. It’s very similar to an optic nerve. Idk. It makes sense in my head. But again, very generous with definitions.
That’s just an Android feature. And not at all something that requires a neural network.
Well shucks, I guess Samsung lied to me! I see adaptive brightness was released as part of Android Pie in 2018.
Yeah, I was thinking it could be machine learning in that it takes the average of all your changes over time and the different ambient light levels.
But deffo no need for neural networks.
Nope, I’ll bet it is like five IF statements and the best part is that it is consistent!
So I was trying to think how I’d implement it, and I agree if it’s simple then it really only needs to set the brightness level once, then remember if the user adjusts it, and reuse that adjustment for every lux reading.
Hence the example I gave:
If we’re very generous with definitions it’s like a threeish neuron neutral network. Camera outputs might level. It’s very similar to an optic nerve. Idk. It makes sense in my head. But again, very generous with definitions.