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This Oxford spinout nets £4.5M to make AI tools that help design semiconductors quickly

Machine Discovery team
Picture credits: Machine Discovery

Headquartered in Oxford, Machine Discovery is a software company, which uses machine learning technology to accelerate compute-intensive optimisation and simulation tasks. 

Now, the company has netted £4.5 million in funding led by BGF, one of the UK’s largest investors that recently backed Kooth and LISSUN, and East Innovate, alongside Foresight WAE Technology Funds, UK Innovation and Science Seed Fund (UKI2S), independently managed by Future Planet Capital (Ventures) Ltd and Oxford Technology.

With the latest influx of capital, Machine Discovery will grow its engineering and business development teams in the UK and the USA. Also, it will focus on delivering AI tools for semiconductor design and other sectors. 

Bijan Kiani, CEO of Machine Discovery, said: “Machine Discovery is pioneering the use of machine learning to reduce product development cycles in a variety of sectors. We thank our partners for their continued support at a key stage of the company’s development, enabling us to expand the number of users utilising our Discovery Platform and drive forward the company’s future innovations.” 

Luke Rajah, investor at BGF, said: “With cutting-edge machine learning technology and a management team with deep industry expertise, we believe Machine Discovery is poised for rapid adoption and growth. Early customer results in analog semiconductor design have shown the potential of the technology to massively accelerate the time to develop new products, which will enable leading semiconductor players to differentiate themselves in the market.”

Delivers AI tools for semiconductor design

Machine Discovery was spun out of the University of Oxford by researchers in the physics department by co-founders Muhammad Kasim, Brett Larder, Gianluca Gregori, and Sam Vinko. 

Its AI platform offers the ability to manage complex collaborative projects across large teams, with a high number of simulation runs. The platform’s novel emulation technology creates, from conventional simulation outputs, neural-network-based models for real-time prediction. The platform’s optimisation engine uses AI algorithms for optimisation and sampling and combines simulation and neural-network model outputs to enable the exploration of a significantly larger design space at a record speed.

Its first core application in analogue semiconductor design, delivers instant prediction capability for integrated circuit design as a companion to existing tools and simulators. With its technology, Machine Discovery eyes to cut the analogue semiconductor product development cycle in half by 2026. 

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