Genes, the brain, and artificial intelligence in evolution

Three important systems, genes, the brain, and artificial intelligence (especially deep learning) have similar goals, namely, the maximization of likelihood or minimization of cross-entropy. Animal brains have evolved through predator-prey interactions in which maximizing survival probability and transmission of genes to offspring were the main objectives. Coordinate transformation for a rigid body necessary to win predator-prey battles requires a huge amount of matrix operations in the brain similar to those performed by a powerful GPU. Things (molecules), information (genes), and energy (ATP) are essential for using Maxwell’s demon model to understand how a living system maintains a low level of entropy. However, while the history of medicine and biology saw molecular biology and genetics disciplines flourish, the study of energy has been limited, despite estimates that >10% all human genes code energy-related proteins. Since there are a large number of molecular and genetic diseases, many energy-related diseases must exist as well. In addition to mitochondrial disease, common diseases such as neurodegenerative diseases, muscle diseases, cardiomyopathy, and diabetes are candidates for diseases related to cellular energy shortage. We are developing ATP enhancer, a drug to treat such diseases. I predict that in the future, the frontier of medicine and biology will involve energy and entropy, and the frontier of science will be about the cognitive processes that scientists’ brains use to study mathematics and physics. That will be understood by comparing the abilities that were necessary to survive battles between predators and prey during evolutionary history.