George Church believes that enhancing human intelligence will stay ahead of artificial synthetic intelligence.
George Church believes that enhancing human intelligence will stay ahead of artificial synthetic intelligence.
George Church is Professor of Genetics at Harvard Medical School and Professor of Health Sciences and Technology at Harvard and MIT. He is Director of the U.S. Department of Energy Technology Center and Director of the National Institutes of Health Center of Excellence in Genomic Science. George leads Synthetic Biology at the Wyss Institute, where he oversees the directed evolution of molecules, polymers, and whole genomes to create new tools with applications in regenerative medicine and bio-production of chemicals. He helped initiate the Human Genome Project in 1984 and the Personal Genome Project in 2005. George invented the broadly applied concepts of molecular multiplexing and tags, homologous recombination methods, and array DNA synthesizers. His many innovations have been the basis for a number of companies including Editas, focused on gene therapy, Gen9bio, focused on Synthetic DNA, and Veritas Genetics, which is focused on full human genome sequencing. And with that, lets get into our conversation with George Church.
George believes that human intelligence is a moving target.
Clock speed might be less relevant than energy economy.
We can make DNA memory storage that is a million times more energy efficient. It can be copied for a few joules. Roswell Biotechnology is a startup that could make trillions of parallel devices to read and write to DNA.
There is an assumption in the AGI Singularity that computers will improve nearly constantly at Moore’s Law pace and human intelligence would stay static. However, George Church believes that human intelligence will be improved with biotechnology.
If the first AGI is on the economic and computational scale of a supercomputer such that we imagine that were still just leveraging really, really big amounts of data and we havent made extremely efficient advancements and algorithms such that the efficiency jumps a lot but rather the current trends continue and its just more and more data and maybe some algorithmic improvements, that the first system is just really big and clunky and expensive, and then that thing can self-recursively try to make itself cheaper, and then that the direction that that would move in would be increasingly creating hardware which has synthetic bio components.
We could move the goalposts where human intelligence moves from our current average to Albert Einstein at his peak year in 1905.
We already are seeing some aging drugs, small molecules that are in clinical trials. George Church’s lab just published a combination gene therapy that will hit five different diseases of aging in mice and now its in clinical trials in dogs and then hopefully in a couple of years it will be in clinical trials in humans.
Were not talking about centuries here. Were talking about the sort of time that it takes to get things through clinical trails, which is about a decade. And a lot of stuff going on in parallel which then after one decade of parallel trials would be merging into combined trials. So a couple of decades.