‘Moonshot’ ventures to transform semiconductor and biomanufacturing industries

‘Moonshot’ ventures to transform semiconductor and biomanufacturing industries

Two initiatives have received £100,000 in seed corn funding from the Department of Science, Innovation and Technology (DSIT)

  • By ICN Bureau | April 02, 2024

Two new research ventures will develop cutting-edge technologies for the semiconductor and biomanufacturing industries, if they can secure government, industrial, philanthropic and venture capital backing.

CybergenX, out of the University of Edinburgh, is pioneering intracellular technology which could accelerate the potential of engineering biology to replace fossil fuels in manufacturing.

And the Edinburgh Venture builder for AI-hardware (EVA) will push the frontiers of next-generation semiconductor technologies for artificial intelligence.

In a new funding model, called the Research Venture Catalyst (RVC) programme, the two initiatives have received £100,000 in seed corn funding from the Department of Science, Innovation and Technology (DSIT) to develop detailed technical plans and partnerships with industry, philanthropy and venture capital. If successful, DSIT will match whatever they raise with up to £25 million each.

CybergenX: Unleashing the potential of engineering biology

Describing CybergenX, academic lead Professor Filippo Menolascina, an entrepreneur and pioneer in the field of cybergenetics, from Edinburgh’s School of Engineering, said: “Engineered cells will be the factories of the future, producing the materials, medicine and food we use every day. However, our current ability to engineer and control cells is hampered by a fundamental gap: unlike the internal dynamics of man-made systems, we know very little of what happens inside a cell.

“CybergenX, our Focused Research Organisation, will address this problem by developing a technology that will increase by 1000 times the depth and frequency of the intracellular signals we can measure. We will then use this data to train a new type of AI foundation model that takes inspiration from the transformers used in ChatGPT and specialises them to biological systems.

“This is a moonshot for engineering biology, which could revolutionise manufacturing across all sectors, and significantly reduce our reliance on fossil fuels.”

EVA: Innovating sustainable semiconductor technologies

Professor Themis Prodromakis, Regius Chair of Engineering and academic lead for the second RVC, EVA, plans to co-locate researchers and investors with commercial and government users, as Nokia did with their famous ‘Bell-Lab’ R&D model.

Professor Prodromakis said: “Our aim is to stimulate innovation in emerging semiconductor technologies and drive energy-efficient AI processing capabilities, whilst exploiting intellectual property across a diverse range of applications and markets.

"AI is undergoing an era of explosive growth, but this comes at a significant environmental footprint, which is constraining its sustainable development. EVA will deliver technologies that address five key challenges for future compute systems:  scale, speed, sustainability, size and social responsibility.

"We feel that this can only be delivered when expertise in emerging semiconductor technologies, nanoelectronics design and artificial intelligence come together under a single roof.

"We are looking for investors and private and public sector partners to join us in this exciting venture builder journey.”

Dr Andrea Taylor, interim CEO at Edinburgh Innovations, the University’s commercialisation service, which will be supporting the development of the RVC partnerships, said: “This new funding model sets out to drive the innovative partnerships we believe are fundamental to meeting the challenges the world faces today, in the domains of climate, data and health. That two of these future-focussed collaborations are led by the University of Edinburgh is testament to our expertise and entrepreneurial support. This is an opportunity to realise the huge potential of engineering biology and next-generation semiconductors for AI on a global scale.”

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