Merck teams for AI semiconductor process development

December 08, 2021 // By Peter Clarke
Merck, Palantir partner to ease semiconductor process development
Merck is forming a joint venture with big data company Palantir Technologies in the US to pool data and analytics on semiconductor manufacturing.

German materials giant Merck is forming a joint venture with Palantir Technologies to pool data and analytics on semiconductor manufacturing.

The company, Athinia, will be headquartered in the US with Laura Matz, chief science and technology officer of Merck, as CEO. It will use the combination of AI and big data to help solve semiconductor challenges for clients. The collaborative analytics platform will also improve supply chain transparency and help guarantee material supplies and prevent them impacting chip manufacturing.

Merck is making the move through its electronics materials subsidiary EMD Electronics. Matz declined to say how much capital is being put up to create Athinia nor whether the company has any chip makers, materials suppliers or research institutes signed up to the platform. "We are just starting the company now and will have first adopters in 2022," she said.

The plan is for Athinia to bring multiple materials suppliers, including rivals to Merck, together with semiconductor manufacturers and have them share, aggregate, and analyze data to unlock efficiencies. The data will be kept private using Palantir's big data expertise.

Palantir was founded in 2003 by Peter Thiel and others and is best known for its platforms called Gotham, Metropolis and Foundry. Palantir Gotham is used by counter-terrorism analysts with the US intelligence community and the US Department of Defense. Palantir Metropolis is used by banks and the financial community while Palantir Foundry is used by corporate clients including Merck, Airbus and Fiat-Chrysler, now part of Stellantis.

"Already materials suppliers and semiconductor makers are seeing an increasing impact on yield," said Matz and said that at the leading-edge processes can be so sensitive that materials within nominal specification can produce variable yields. "Traditional parameters don't necessarily predict the fab-process interaction," she added. "A key aspect of the offer is privacy and Athinia will provide that by coding and anonymizing the data. The result of working with Athinia is that companies will get better data quicker."

The Athinia platform is powered by Palantir Foundry, which enables users to structure and analyze data from disparate sources, generate powerful insights and support operational decisions, all while helping to ensure that sensitive data is processed in accordance with applicable data privacy rules, regulations and norms.

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