Zebrafish NN It’s pretty amazing to learn that efforts to map the fruit FLY connectome (brain synapses) were successful and its amazing to see the digital fly brain successfully complete a whole series of tasks, including complex navigation of open worlds. The fruit fly is 160,000 neurons and 10^7 synapses. Teams are currently doing the same thing with a zebrafish which has a similar scale neuron count but 10x more synapses. Fly was 100TB raw data and Zebrafish is 200TB, so about 2x the raw data. For context a rodent is 70m neurons and 10^11 synapses. Rodents will come later. But this method looks like it creates totally outsized results with absolutely miniscule models. Zebrafish NN is a vertebrae connectome, it has much of the same basic structure as other vertebrae, unlike FLY connectome. We are just about used to LLMs and coding, but AI is really just beginning and there is a lot more, and a lot weirder stuff coming down the pipe. These connectomes have already shown to be incredibly resilient, you can blind their sensors and injure their outputs and they still succeed. They are incredibly compact. A whole lot of inanimate objects are going to get complete autonomy, totally offline, air gapped autonomy. They will be delivering pizzas and fighting wars. Connectomics is an opposite approach to LLMs but you can of course use LLMs to help develop connectomes. It’s amazing that you can take a biologically evolved brain, map it, produce a digital twin, and then run it at machine speed. Imagine a human brain accelerated from 100Hz neuron fires to 3,200,000,000Hz that a typical CPU runs at. That’s 30 million times faster. But would need 1-2 exabytes to map. Anyway “Zebrafish” is next.