This article was originally published on the Manchester Prize website on 17 June 2024.

Chair of the Manchester Prize judging panel and Vice-Chancellor and President of Loughborough University, Professor Nick Jennings, shares his reflections on the 10 finalist teams and their trailblazing innovations.

The inaugural Manchester Prize, which launched in December 2023 and is set to conclude in March 2025, supports UK-led teams to overcome challenges in the fields of energy, environment and infrastructure through groundbreaking AI innovation. As an AI researcher with over 30 years experience, it is a topic close to my heart, and it is fantastic to see the importance of this work being recognised by the government, with a clear commitment to support those engaged in the application of AI for public good. 

I am delighted and honoured to be the inaugural chair of the Prize, and relish this opportunity to shine a light on some of the nation’s brightest minds. Our goal with the Manchester Prize is to create a prestigious award that highlights the positive impact AI can have on society, and I am particularly enthusiastic about the idea of a Prize that actively contributes to the development of new solutions, rather than merely rewarding past achievements. 

Through the application of pioneering new work, we can drive change and make a real difference to the world around us. While much attention has – rightly – been placed on the safety and risks of AI, we must also ensure we make the most of the significant potential that this technology holds to improve lives when used responsibly. In the coming years, we will see ever more fascinating and impactful applications of AI come to the fore. These applications will profoundly affect our lives, our society, and our planet. 

Building on feedback received from a wide range of stakeholders, a tailored package of non-financial support has been created to navigate the complexities of the intellectual property of AI, prepare the teams for future investment, and support with business strategies that are both sustainable and ethical. The prize also offers computational resources, matchmaking opportunities and other essential assistance to help the finalists succeed. For example, on top of the £100,000 grant received by each of the ten finalists, the teams will be reimbursed up to £90,000 for spending on compute to develop or test their AI systems. 

The benefits of a multidisciplinary approach

When the entry period ended, we had almost 300 eligible innovations for the prize, with an impressive 425 entrants represented across the various teams. Entries to the Prize came from across the UK, with nearly 20% coming from the North East and North West of England. Of the 240 entries which passed the initial eligibility screening, 65% came from solo organisations, 18% from a group of organisations, 12% from a group of individuals and 5% from sole individuals. 

These ten finalists have the potential to significantly improve life in the UK by addressing critical issues in energy, environment, and infrastructure. Projects like Aiolus and Quartz Solar AI Nowcasting aim to enhance renewable energy efficiency and improve air quality for future generations, while AssetScan and TraffEase are set to revolutionise infrastructure maintenance and urban planning, which could help to make people’s day-to-day journeys more comfortable and safe. Collectively, these AI-driven solutions promise to create more sustainable, efficient, and resilient communities, and have the potential to dramatically improve the lives of millions. 

It’s been exciting to see how teams have taken a multidisciplinary approach to their innovations, with organisations coming together from different fields to collaboratively produce their entries. For example, Phytoform Labs is an agricultural biotech startup which brings together 13 PhDs and professionals in genome engineering, data science and agriculture to work on their project, CRE.AI.TIVE. Similarly, Quartz Solar AI Nowcasting is led by Open Climate Fix, a non-profit product lab focused on reducing greenhouse gas emissions as rapidly as possible, in partnership with data science and AI powerhouse, The Alan Turing Institute.

A multidisciplinary approach is crucial for tackling the complex issues in energy, environment, and infrastructure, particularly when integrating AI. By combining expertise from an array of fields such as engineering, environmental science and data analytics, we can develop comprehensive solutions that address the multifaceted nature of these problems. This collaborative method ensures that AI applications are not only technologically advanced but also practical, sustainable, and socially responsible, leading to more robust and innovative solutions that can effectively address the challenges of our time.

The next steps 

A pattern that emerged from the selected finalist applications was the optimism they showed for the future of UK AI development. As judges, our role was to assess how these developments might translate into tangible and viable long-term societal benefits. The AI solutions selected are forward-looking, and present novel ways to overcome the most pressing challenges facing society, whether that relates to waste systems, the energy grid, food supply chains or transportation. 

Over the next seven months, the 10 teams will be working with key stakeholders including problem-holders, potential adopters and investors, to develop their solutions ahead of a prototype demonstration workshop in January 2025. I am incredibly excited to monitor their progress and see how far they develop their innovations by the start of next year. 

While securing the £1 million Grand Prize is the ultimate goal, all teams should be striving to make the most of the profile and opportunities presented to them by this initiative. The experience they will gain over the next few months, from networking opportunities to tailored support sessions, will be invaluable, and is why the Manchester Prize will be a beacon for excellence in AI innovation in the UK. 

The 10 finalist teams:

Energy solutions

Four of the 10 finalists are addressing the key issues in the energy sector, from managing solar resources, to revolutionising battery manufacturing. 

• Quartz Solar AI Nowcasting uses generative AI to decarbonise the UK’s energy grid through better forecasting of cloud movements. By leveraging satellite imagery and live solar generation data, it can help better manage solar energy resources and balance a renewables heavy grid.
• AIOLUS uses Deep Reinforcement Learning for improving wind farm efficiency, simultaneously boosting energy capacity, lowering the average cost of electricity, and accelerating the UK towards its Net Zero target.
• Polaron uses generative AI to optimise energy material manufacturing, using algorithms to rapidly analyse potential material designs and identify the best manufacturing processes to maximise performance.
• EvoPhase Explore provides an AI-driven approach to optimising industrial equipment for economic and environmental impact. It leverages evolutionary algorithms to reduce energy consumption, minimise waste, and enhance overall efficiency in manufacturing processes. 

Environmental solutions

Four of the 10 finalists aim to provide solutions to problems facing the environment, from future-proofing crops, to improving the UK’s quality of water. 

• CRE.AI.TIVE learns about the genome of plants and accelerates the search for useful mutations to increase the resilience of crops, helping to reduce the threat of global food insecurity. 
• Greyparrot leverages AI and image processing to improve the traceability of consumer packaged goods, supporting the value chain to improve packaging design, policy making and recycling rates.
• Sapphire reduces water pollution from storm overflows, agriculture, and urban spaces in order to improve water quality, by integrating observed data and computer model outputs into an AI platform, incorporating more sources of pollution, and producing faster results than traditional methods
• gAIn Water uses deep learning models & adaptive reinforcement learning agents to forecast water demand, provide alerts about system failures, and identify potential supply shortages.

Infrastructure solutions

Two of the 10 finalists are focussing on the issues facing UK infrastructure, and aim to improve mobility and more efficiently maintain our nation’s buildings. 

• AssetScan identifies defects in UK buildings and large infrastructure assets from photographic datasets to target effective maintenance at the earliest opportunity.
• TraffEase supports net-zero and inclusive mobility targets through the creation of digital transportation twins.