| > I'm curious how we're even going to manage 420,000 pixels' worth (60,000 ommatidia, approximately 7 pixels each) of input with only a few hundred transistors, let alone do vector analysis on it. If you define the problem as importing 420,000 pixels, and target recognitions, and vector analysis, then you need a whole lot more computation than the organism uses. But presumably you're going to also get better results. We both know that's not exactly what's happening, I think. That is, we know we can solve similar tracking problems with a whole lot less state. > That's pretending 99.7% of the seven thousand synapses each neuron has are useless for our purpose Not really... I think we can imagine a whole lot of passives / linear operations involved, along with the big nonlinear processes we need transistors for. We're also assuming there's no net benefit to cognition that can happen using transistors, I'll note-- e.g. they have a ton of bandwidth compared to neurons, can be multiplexed more readily, etc.... > Humans have 86 billion neurons. Subtracting 22 gives us 64 billion, times 20 transistors per neuron gives us 1.28 trillion transistors. So about half the number packed onto Cerebras WSE-2 today. > even pretending we exactly understood how sapience worked in the first place. This is the big problem. |