A recent attempt to fully map a mere cubic millimeter of a human brain took up 1.4 petabytes of storage just in pictures of the specimen. A collaborative effort between Harvard researchers and Google AI experts took the deepest dive yet into neural mapping with the recent full imaging and mapping of the brain sample, making puzzling discoveries and utilizing incredible technology. We did the back-of-napkin math on what ramping up this experiment to the entire brain would cost, and the scale is impossibly large — 1.6 zettabytes of storage costing $50 billion and spanning 140 acres, making it the largest data center on the planet.
The study is full of mind-numbing stats. To image a human brain, the researchers needed to utilize Google's machine learning tech, shaving estimated years off of the project. Scientists first sliced the sample into 5000 wafers orders of magnitude thinner than human hair. Electron microscope images were taken of each slice, which were recombined to count around 50,000 cells and 150 million synapses, the connection points where neurons meet and interact. To recombine these images and map the fibers and cells accurately, Google's AI imaging tech had to be used, digitally working out the routes of the gray matter.
