Sam Rodriques' startup, FutureHouse, launched ether0, an AI model designed specifically for chemistry. This open-source model, trained on a set of 500,000 questions, can generate drug-like molecules based on user-defined criteria. Unlike prior models, ether0 tracks its reasoning process in natural language, allowing deeper insights that are typically hard to attain. While some researchers express excitement at its capabilities, they also caution about potential implications of such advanced tools in scientific research.
Researchers have expressed a mixture of excitement and concern about FutureHouse's advance. 'I think it's very cool what they pulled off,' says Kevin Jablonka, a digital chemist at the University of Jena in Germany. When playing around with a preview version of ether0, Jablonka found that the model could draw meaningful inferences about chemical properties that it wasn't trained on. 'That's impressive and [something] models before couldn't do,' he says.
Ether0, which is open source and publicly available from today, joins a host of other efforts aimed at automating the scientific process, including at Google and the Japanese company Sakana AI.
The model, called ether0, is a large language model (LLM) that's purpose-built for chemistry, which it learnt simply by taking a test of around 500,000 questions.
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