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Yes, everyone’s hyping the fly brain. So we gave a human-connectome model two sabers and RUSH E. 🧠⚔️ The wiring comes from a published human structural connectome derived from diffusion MRI tractography. Each node corresponds to a brain region, represented here by one simplified computational unit. We’re working at... show more
12,924 views • 9 days ago •via X (Twitter)
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How is this possible? You realize H01 (the connectome also produced by @GoogleAI) is around 1.4PB - thats Petabytes. It represents a slice of about 160,000 neurons. Is there a simplified connectome you have found?

The paper is attached on the comment. As we mentioned, we are not using single neurons for this model. We are considering each brain region/subregiom as a node and also its real whitematter connectome for its connections (plus the euclidean distance for the cortico-corical). The idea was to show how extraordinary the human brain is if just by simplifying it in this way, we still have a good reservoir network... imagine if we simulate all neurons. Have a look into the paper attached, it is a really good one.

To keep sense of the scale of the human brain: each cortical node represents a whole region—not a single biological neuron. With 1,000 cortical regions, that works out to roughly 16 million biological neurons per node on average—over 100 times the neuron count of the adult FlyWire brain. In this experiment, we compress each region into one simplified computational unit. Here for the ref behind the model

And now that you are here: Check out our whitepaper, deck, roadmap, and more

This is the future of the virtual world!

Nice, I trained them how to fight in MMA

No grappling!?!?

it will come, the'll learn 😂 just the training is taking time

Crazy

Moving from simulated environments to physical movement is a massive leap for connectome-based robotics, and we actually went deeper on this here:

since neurons forming is an emergent phenomena from individual cell interactions,Can a ai procedurally generate where neurons should be given previous scans of human neurons.

Everyone copying @BioLLM_ come up with your own ideas

@BioLLM_ What are you even talking abt? Go read our wp and roadmap
