“This computational work represents a stunning advance on the protein-folding problem, a 50-year-old grand challenge in biology. It has occurred decades before many people in the field would have predicted. It will be exciting to see the many ways in which it will fundamentally change biological research”.
Professor Venki Ramakrishnan – Nobel Laureate and President of the Royal Society
“We trained this system on publicly available data consisting of ~170,000 protein structures from the protein data bank together with large databases containing protein sequences of unknown structure. It uses approximately 16 TPUv3s (which is 128 TPUv3 cores or roughly equivalent to ~100-200 GPUs) run over a few weeks, a relatively modest amount of compute in the context of most large state-of-the-art models used in machine learning today.”
“Recent studies have shown that stigmergy is not necessary to explain concerted construction: Green et al. showed that worker aggregation rather than the previously suspected presence of cementation pheromone localized excavation work sites in termites, and Bruce found no behavioural response to freshly excavated soil that would contain a digging pheromone were it an organizing factor in excavation in leafcutter ants. Eciton army ants, which self-assemble into bridges to cross trail gaps, gauge the necessity to reinforce or leave these structures based purely on the rate of physical contact with passing workers with no evidence of stigmergic processes.”