I’ve never understood cryptocurrency, and I’m still a bit baffled that it was really a thing. As far as I understand it (on a very simple level), cryptocurrency mining occurs when the blockchain asks a computer to perform complicated math in exchange for tokens.
A team of chemists has used this power for good, proving the potential usefulness of blockchain to solve scientific problems in less time and for less money than other options.
The team asked computers to generate the largest network of chemical reactions ever created, to understand which reactions may have given rise to prebiotic molecules on early Earth.
Researchers chose a set of molecules likely present on early Earth, including water, methane, and ammonia. They set rules for which reactions could occur between different types of molecules and then translated the info into a language that computers and the blockchain used for calculations. The model indicates that some primitive forms of metabolism may have emerged without enzymes.
The team, led by Bartosz A. Grzybowski, worked with chemists and computer specialists at Allchemy, a company using AI for chemical synthesis planning. They generated the network using Golem, a platform that orchestrates portions of the calculations over hundreds of computers across the world, which receive cryptocurrency in exchange for computer time.
The resulting network, named the Network of Early Life, or NOEL, started with more than 11 billion reactions. The team narrowed this down to a mere 4.9 billion plausible reactions. Of the 4.9 billion, only hundreds of those cycles were “self-replicating,” producing additional copies of themselves. Scientists believe this self-replication was central to the emergence of life.
“If you asked me two years ago, I’d be thinking we’d need years for this type of work,” says Grzybowski. “But for a fraction of the cost, in two or three months, we finished a task of 10 billion reactions, 100k times bigger than we did previously.”
Grzybowski believes that using blockchain can revolutionize how teams perform such complicated calculations and that institutions can harness their networks’ idle power to carry out such work without spending capital.
