Machine Discovery, a software company which uses machine learning technology to accelerate compute-intensive optimisation and simulation tasks, has secured £4.5 million of funding.
Spun out of the University of Oxford by researchers in the physics department, co-founder and CSO Muhammad Kasim invented the machine learning technology that underpins the company’s work, while co-founder and CTO Brett Larder developed the first prototype of its Discovery Platform.
Other co-founders including Professor Gianluca Gregori and Professor Sam Vinko are continuing with their contributions in an advisory capacity while connecting the company to the research community.
The company is led by its CEO Bijan Kiani and non-executive chair Janet Collyer, who each have over 20 years of experience in the electronic design tools space.
The investment round was led by BGF 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.
This latest round of funding will allow the company to grow its engineering and business development teams in the UK and the USA, driving commercial adoption of its technology across the semiconductor design space and in other markets.
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“Machine Discovery is pioneering the use of machine learning to reduce product development cycles in a variety of sectors,” said Kiani.
“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.”
Machine Discovery’s 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, while its 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.
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.”
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