A Celebrated AI Has Learned a New Trick: How to Do Chemistry

upstart writes:

This capability could unlock new possibilities in medicine:

Artificial intelligence has altered the practise of science by enabling researchers to examine the vast volumes of data generated by current scientific instruments. Using deep learning, it can learn from the data itself and can locate a needle in a million haystacks of information. AI is advancing the development of gene searching, medicine, medication design, and chemical compound synthesis.

To extract information from fresh data, deep learning employs algorithms, often neural networks trained on massive volumes of data. With its step-by-step instructions, it is considerably different from traditional computing. It instead learns from data. Deep learning is far less transparent than conventional computer programming, leaving vital concerns unanswered: what has the system learnt and what does it know?

[...] For fifty years, computer scientists have unsuccessfully attempted to solve the protein-folding issue. Then in 2016, DeepMind, an AI subsidiary of Alphabet, the parent company of Google, launched its AlphaFold programme. It utilised the protein databank, which contains the empirically determined structures of over 150,000 proteins, as its training set.

In fewer than five years, AlphaFold had solved the protein-folding issue, or at least the most important aspect of it: identifying the protein structure from its amino acid sequence. AlphaFold can not explain how proteins may fold so rapidly and precisely. It was a tremendous victory for AI since not only did it earn a great deal of scientific reputation, but it was also a major scientific breakthrough that may touch everyone's life.

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