Adam Marblestone wants to make the brain machine-readable. So he worked out the physical limits of what’s possible in recording brain activity and is now using that knowledge to set technology strategy at Kernel, a startup with $100 million in funding that’s building neural interfaces for humans.
As a PhD student, Marblestone was a lead author of a paper now considered a foundational strategic document for researchers building technology to read brain activity. Using the mouse brain as a model, he identified the engineering problems we’ll have to solve to simultaneously measure the activity of every neuron in the brain.
“It’s all about how do we, in the approaches that we take to studying the brain, somehow try to match the complexity of the brain itself?” he says.
As chief strategy officer at Kernel, he’s marshalling a network of leading researchers to identify the most promising approaches for making neural interfaces that can help us understand and treat neurological diseases. One day they could even make it possible to merge our brains with machines.