[13/09/23] Bayes Centre News: AIMday Digital Frontiers breaks new ground for industry challenges

The event was held at the Bayes Centre, the University of Edinburgh's Innovation Hub for Data Science and Artificial Intelligence.

 

Organiser Hjalmar Eriksson of Edinburgh Innovations, the University’s commercialisation service, said:

This was an opportunity for partners to set the agenda and discuss novel ways to find solutions to their business problems.

Before the meeting, private companies as well as Scottish Government and NGOs submitted challenges they face in areas such as AI, data analytics, robotics and electronics, and academics from across disciplines volunteered their expertise in response. There are advantages for both sides in working together.

 

Attendee Dr David Greig of Leonardo, a worldwide aerospace company, said:

We were pleasantly surprised by the approaches to our challenge presented by the academics and we are keen on further exploration together. We are also very excited about the potential for us to jointly access translational funding to make this project happen.

 

David Wood is CTO and Co-founder of Moonsift, a curated shoppable mood board tech business who is co-located at the Bayes Centre, said:

We started with quite a technical question, but the expertise in the room gave us a chance to discuss the wider user experience and provided a strategic perspective to the challenge. We came away with a new understanding of the potential project and a completely unexpected opportunity arose that involves engaging with students.

Emily Lekkas is Business Development Manager at the Bayes Centre. She observed: 

The AIMday format allows multiple academics and technical teams from across the social sciences, science and engineering to provide multifaceted solutions that pave the way for new relationships with industry and each other.

 

Advancing innovation

Fruitful discussions included using satellite data and AI to assess biodiversity and carbon storage, automatically analysing calls to police to better serve demand, low power options to deploy digital technology in field conditions, and how to use new AI tools while preserving privacy.

Harry Schone is Data Science Co-ordinator at Police Scotland. He said:

We had a really good discussion, there was a broad diversity of perspectives from a wide range of academics. I am hoping we can tap into some of the more technical expertise that’s on offer across the University of Edinburgh and that this will lead to a follow up project where we can work with an academic team. We attended the last AIMday on Quantum Computing which was very successful for us. We are now running a joint Resource Optimisation project with the School of Maths, who were able to obtain funding as a result.

Possible projects emerging, which might access the fund available through the University of Edinburgh’s EPSRC Impact Acceleration Account, include prioritising and presenting relevant data to frontline police officers and early adoption of machine learning and artificial intelligence techniques in STMicroelectronics' research and development process.

The day’s conversations occasionally solve a problem quickly, but more often lead to industry collaborations and long-term partnerships. The partnership with Babcock, leading to the establishment of FastBlade, the world's first regenerative fatigue test facility at Babcock’s site in Rosyth was accelerated through participation in AIMdays and subsequent follow on projects supported by Edinburgh Innovations..

The Bayes Centre and Edinburgh Innovations teams are now working together, following up on introductions and collaborations coming out of the day.

 

Emily Lekkas concluded:

The University of Edinburgh has world-leading research in AI and digital technologies such as blockchain, microelectronics, and natural language processing. The AIMday sessions gave the organisations the opportunity to consider novel approaches to address or unpack complicated challenges facing industry, accessing funding to kickstart the translation of these methodologies into solutions, and ultimately enable the use of data science and digital technologies to drive forward productivity gains.

 

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