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AI drug discovery is so last year, even though it hasn't accomplished much yet

In order to move more semiconductor manufacturing onshore, the US needs to depend less on foreign-sourced materials. Now, the government is giving an Alphabet spinoff $500 million in CHIPS Act funds to find domestic minerals, molecules, and chemicals needed for this process.

SandboxAQ (that’s AI and Quantum, for those wondering), which spun off from Alphabet in 2022 under the chairmanship of former Google CEO Eric Schmidt, announced the award Wednesday. The company won’t be doing any manufacturing – this is just an R&D grant to turn the startup's AI simulation software toward discoveries necessary to build a domestic chip industry.

According to SandboxAQ, the $500 million awarded to it by the Department of Commerce will go toward developing “novel molecules and formulations for semiconductor manufacturing," including chip production materials that are free of PFAS ("forever chemicals"), new semiconductor fabrication catalysts, magnets that don’t rely on foreign-sourced neodymium and other rare earths, and fab-powering batteries that don’t rely on majority foreign-sourced materials like lithium.

The CHIPS and Science Act, signed into law by President Biden in 2022, was designed in part to dole out $52 billion to US firms to reignite domestic semiconductor manufacturing, which has mostly fled the country for more favorable production environments overseas. Four years on, the government’s many investments have seen some payoff, like the acquisition of a 10 percent stake in Intel to help keep the company afloat, but there’s still a lot of work to be done to reduce dependence on foreign supply chains and manufacturers. 

SandboxAQ relies its own large quantitative models (LQMs), which it describes as “AI systems trained on the laws of physics, chemistry, and biology, not human language.” That, the company asserts, means they’re well-suited to discover new materials needed to eliminate harmful PFAS and foreign-sourced materials from the semiconductor supply chain. 

The hope is that the LQMs will be able to generate their own material predictions that researchers then test in the lab – essentially the same process that’s undergirded the years-long effort to use AI to help synthesize new drugs. 

Despite AI industry leaders prognosticating we’d be popping AI-designed drugs in 2025, AI has yet to design a functional medicine, according to the US National Institutes of Health. Why, then, should we presume an AI will succeed at replacing critical battery and chip manufacturing components where drug research has failed?

In fact, according to SandboxAQ’s announcement, its LQMs aren’t even necessarily grounded in real-world data. They rely in part on synthetic data, which is then fed into the company’s LQMs and used to train their design-make-test workflows.

A company spokesperson told The Register in an email that it still uses real-world data where possible.

“Where experimental data exists, we incorporate it,” SandboxAQ told us. “Where it doesn't, we can still move forward and solve the problem.”

When asked whether an error in the reasoning process could compound, leading to considerable lost time for researchers and a lack of results, the company admitted that such a potential is exactly what “any rigorous AI-driven materials program has to answer.” 

“Our models are trained on the laws of physics and chemistry, so they are anchored to physical reality, rather than free to drift,” the spokesperson told us, adding that lab testing is the final check on AI accuracy. “A material either performs in the lab, or it doesn’t, and that validation gate is precisely what prevents a chain of reasoning from running away with itself.” 

SandboxAQ added that it is not starting from zero in any of the four target areas, having done previous work on catalysts, battery materials, alloy discovery, and PFAS breakdown that will be incorporated into its CHIPS Act-funded work. 

“In commercial deployment, we’ve already cut development timelines from months to weeks” at the candidate screening stage, the SandboxAQ spokesperson explained. SandboxAQ said that some of the work it's doing, like PFAS mitigation, could be rolled out to existing fabs, as could new batteries and the like, but it admitted that the various verticals will operate on different timelines.

“Qualification in the semiconductor industry is genuinely rigorous and does take time – we wouldn’t minimize that – but the path runs through validation and industrial qualification with existing manufacturers, not through standing up new fabrication capacity from scratch,” SandboxAQ told us. ®