DeepMind's robot chef cooks up 'novel' materials with a side of controversy – Chemists dispute research claiming millions of recipes for inorganic crystalline compounds

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Google DeepMind and UC Berkeley's research into a robot cooking up new materials predicted by AI algorithms is being called into question by a group of chemists.

The initial study, published in November in Nature, garnered attention for deploying a robotic lab system, A-Lab, to automatically synthesize novel compounds predicted by Google DeepMind's model GNoMe.

A machine learning algorithm inspected the experimental patterns and compared them to predicted models to confirm whether the compound was made successfully.

"Unfortunately, we found that the central claim of the A-Lab paper, namely that a large number of previously unknown materials were synthesized, does not hold," they wrote in their analysis released on ChemRxiv [PDF].

Many of the outputs were poor fits to the diffraction patterns predicted by models, and they cannot be reliably used as proof of a compound's structure or purity, the group said.

Gerbrand Ceder, a lead author of the original A-Lab paper and Professor of Materials Science and Engineering at UC Berkeley, told The Register in a statement: "The work of Dr Palgrave is not peer reviewed and we believe it has multiple errors in it.

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