Author: kerry.turcsi

The JGI team had a great time at the AI UK national showcase of data science and AI hosted by The Alan Turing Institute. The team got to experience community talking points on stage, exhibitions that demonstrate innovation from UK academic and commercial organisations, and a range of workshops. You can read our previous blog post about the University of Bristol demonstrations at AI UK.

As a collective, the team had a fantastic time at AI UK and for some team members, AI UK 2025 was their first AI UK showcase. Find out more below about how each team member experienced AI UK and their own personal reflections on the sessions.

Charting the Future of Research in the UK panel discussion and Celebration of the Turing AI Fellowships, Patty Holley

I especially enjoyed a panel discussion on the UK’s research ecosystem, titled Charting the Future of Research in the UK. The panel included Sana Khareghani (Former Head of the UK Government Office for AI and KCL, panel host), Samuel Kaski (Manchester Centre for AI Fundamentals), Anna Scaife (Jodrell Bank Centre for Astrophysics), and Neil Lawrence (University of Cambridge). 

The panellists agreed that UK universities continue to lead global AI research. However, challenges remain in translating research into practical applications. Neil Lawrence was particularly critical of the funding and support directed toward Artificial General Intelligence (AGI). He argued that efforts should instead focus on working with communities to identify real-world problems and develop human-centric AI systems. He pointed to the Global South as a model, where mobile AI systems have been successfully deployed to support farmers. 

I also attended the celebration of the Turing AI Fellowships, marking the culmination of the first five years of this funding program. The first cohort of Fellows included Tim Dodwell (University of Exeter), Yarin Gal (University of Oxford), Neil Lawrence (University of Cambridge), Anna Scaife (University of Manchester), and Maria Liakata (Queen Mary University). This funding has provided a strong foundation for AI research in the UK. It has supported initiatives ranging from the creation of a company exploring AI for fusion—now employing over 50 people—to the development of tools for safe AI. Beyond supporting individual researchers, the fellowships have also helped build capacity by funding early-career researchers. 

Overall, the event was successful in highlighting the UK’s strong position in AI research and the importance of continued investment, collaboration, and ethical responsibility in shaping the future of AI. 

AI Openness in the Age of Deep Seek’s R1, Emmanouil Tranos

The most interesting session I attended was the ‘AI Openness in the Age of Deep Seek’s R1’. I was particularly intrigued by Laura Gilbert’s point about governmental organisations opening up the code they develop for public scrutiny. I do appreciate that this is not an easy nor a widely supported choice to make. But, it certainly adds greater value to the work of these organisations. Of equal interest was the fallacy that a company used their code to re-sell a packaged software product back to the government.

Debates at AI UK, Leo Gorman

I really enjoyed AI UK. Not being an academic conference, it was a chance to hear decision-makers talk about the big picture. Here’s my take on some of the major themes. Almost all speakers said they thought the UK punched above its weight academically, but there were debates about how the UK should position itself in relation to AI research. Debates such as: Is BlueSky research critical for the next AI breakthroughs, or should UK research be working on challenges that are not yet sufficiently profitable for industry, and bring them to sufficient scale? Should the UK focus on researching the impact/use of AI, rather than trying to compete with the US on AI development? Don’t expect to emerge with a consensus, but if you’re interested in these broader types of debates, I definitely recommend going!

Sessions on defence and critical national infrastructure, Richard Lane

AI UK covered a wide range of topics, from the role of research institutions to the environmental impact of emerging technologies. Many discussions focused on how these technologies are being applied across different sectors, and what steps are needed to ensure they deliver practical value. There was plenty of debate around infrastructure, energy use and how we balance innovation with long-term sustainability. Several sessions also touched on the challenges of ensuring wider access to tools and benefits- particularly in areas like education, healthcare, and local services- rather than focusing solely on commercial applications.

The sessions on defence and critical national infrastructure brought some of the more grounded and practical conversations. In defence, there was a clear emphasis on improving back-office systems, accelerating decision-making, and thinking through how automation might reshape responsibilities while also raising questions around oversight and accountability. The importance of regulation and clear ethical standards came up throughout. On critical infrastructure, the focus was on system resilience: not just preventing attacks, but designing systems that can detect, adapt, and recover. There was also discussion around the limitations of purely technical solutions, and the need to consider human factors, long-term planning, and better feedback mechanisms.

Overall, the week highlighted both the opportunities and the complications that come with deploying new technologies at scale; especially in public systems where reliability, transparency, and sustainability matter just as much as capability.

The future they want: lessons from the Children’s AI summit, Huw Day

The session involved listening to a series of talks from children and young people on learnings from the Children’s AI Summit in February, which brought children from across the UK together to share their messages with world leaders at the Paris AI Action Summit. The Children’s Manifesto for the Future of AI was produced as part of the Children’s AI Summit.

The speakers who ranged from ages 10 to 17 (and who were some of the best at the entire conference!) touched on topics such as the role of AI in education, the sustainability issues associated with AI and what young people expect from world leaders. A key point was a desire to have their voices listened to and respected, particularly given that the world we make now is the one that young people will be living in the longest.

A wide perspective of AI UK, Conor Houghton

There was a lot to enjoy at AI-UK. For a start there were people from all sorts of backgrounds, the academy, enterprise and government which made for lots of interesting conversations; the stands were good too, particularly the whale language one from Northeastern University on the research side and the Prolific stand from the corporate side. The keynote session by Tania Duarte, Andrew Fitzgibbon, Lauren Beukes pretending to be a set of AI-UK talks from the future, seemed like a goofy idea but made for some provoking and contrasting talks; Andrew’s talk from the near future was optimistic and interesting, the other two, pretending to come from many decades hence from were wilder, but, strangely, didn’t seem to take account of the wild implications AI has for our sense of our human-ness. A few people, people who didn’t know I was involved with the Bristol stands, commented on how impressive they were and seemed excited by how big a splash Bristol had made, so I was super happy about that.

Implications of AI from the future of research to bridging the skill gap, Isabelle Halton

This was my first time at the AI UK conference and overall, I thought it was well organised, and had a wide breadth of exhibition stands, talks and workshops which made the conference more inclusive. The standout talks I attended were ‘Charting the future of research in the UK’, ‘Bridging the skills gap: regional approaches to AI upskilling’ and the ‘Environmental implications of AI’.

Across the three talks, a common theme seemed to be the incredible possibilities of AI to solve the most local and national pressing issues, but there are many difficulties to scaling up AI solutions – whether this is logistically, financially, legally, environmentally – there seem to be so many barriers to AI solutions becoming an accessible resolution.

The skills AI gap seems to also be having a huge impact onto the future of the workforce. As more businesses require AI solutions and a staggering 52% of the population do not have the necessary skills for the workforce (according to one of the speakers; Liz Williams from FutureDotNow), this clash of circumstances will undoubtedly create gaps across sectors. This raises questions around the role of businesses, the government and local communities, and the broader challenge of digital poverty and inclusion.

There was a lot of food for thought and I came away feeling more knowledgeable about the wider AI landscape. It was great to connect with organisations across the UK, as well as catch up with the other Turing Liaison Managers from other UK universities.

The JGI team had a great time at the AI UK conference a few weeks ago. There were some fantastic University of Bristol demonstration stands at the conference that our Turing Liaison team coordinated. Read more about the demonstrations below and their experience of AI UK below.

AI for Collective Intelligence Hub, Informed AI Hub and PrO-AI (Practice-Oriented Artificial Intelligence) Centre for Doctoral Training

To address society’s most pressing challenges in health, sustainability and security, we must be able to reliably engineer important new kinds of systems that communicate, collaborate and co-ordinate successfully – Collective Intelligence. The AI for Collective Intelligence Hub, Informed AI Hub and PrO-AI (Practice-Oriented Artificial Intelligence) Centre for Doctoral Training teamed up to show how collective artificial intelligence (AI) systems working together to address complex challenges like flood response and urban traffic management.

Demonstrators:

• Sidharth Jaggi, Director of Informed AI Hub and Professor, School of Mathematics
• Peter Flach, Director, PrO-AI (Practice-Oriented Artificial Intelligence) Centre for Doctoral Training and Professor of Artificial Intelligence, School of Computer Science
• Vicky Walter, Senior Research Hub Manager, AI for Collective Intelligence Hub
• Harriet Lee, Hub Project Manager, Informed AI Hub
• Demos from the CDT:
  • OKUMA: A Digital Health Tool for Type 2 Diabetes in Nigeria – Tim Arueyingho, PG, Digital Health and Care (PhD)
  • Multi-Agent Systems for Sustainability – Daniel Collins and Yining Yuan, PhD students, School of Engineering Mathematics and Technology
  • Beyond Expected Patterns in Type 1 Diabetes – Isabella Degen, PG, Interactive Artificial Intelligence (PhD)
  • Visualizing AI: Exploring Large-Scale Image and Video Collections – Grant Stevens, EPSRC Doctoral Prize Fellow, School of Physics and Otto Brookes, PG, Interactive Artificial Intelligence (PhD)
  • AR for AI – Alex Davies, PhD Student, School of Computer Science
  • Multi-robot formations – Jan Blumenkamp and Kazi Ragib Ishraq Sanim, Researchers from the Prorok Lab

Summary from demonstrators:

We had a great time at AI UK, where our demonstrators did an excellent job presenting their research to attendees at the conference. Our stand “From Theory to Practice in Collective AI Systems” brought together different EPSRC funded AI initiatives led by the University of Bristol (AI for Collective Intelligence Hub, Informed AI Hub, Interactive AI CDT, PrO-AI CDT) highlighting the impressive range of AI research happening across the University.

Our schedule of demonstrations covered a range of AI applications;  from digital health tools for diabetes care to multi-agent systems for sustainability, interactive visualisations of AI models, and robotics research. The demonstrators handled a steady stream of visitors, explaining their work with enthusiasm and an impressive ability to communicate complex ideas to both technical and non-technical audiences. When not at the stand, we all took the opportunity to explore the conference, talk to colleagues in the sector, attend AI talks and explore different perspectives on the latest developments in the field.

Overall, it was a really valuable experience, and we’re looking forward to more opportunities to showcase our AI community in the future!

Isambard-AI national AI research infrastructure (AIRR)

Isambard-AI’s stand provided visitors a unique opportunity to interact directly with Isambard-AI via AI applications running directly on the supercomputer. Researchers can sign up for an account at the Bristol Centre for Supercomputing (BriCS) stand and try it out for use in your own research.

Demonstrators:

• Simon McIntosh-Smith, Professor in High Performance Computing, School of Computer Science and Project Lead, Bristol Centre for Supercomputing
• Emma Rose, Centre Manager, Bristol Centre for Supercomputing
• Emily Coles, Communications Manager, Strategic Communications and Marketing Management Team
• Fan Yang-Turner, AI Supercomputing Infrastructure Lead, Bristol Centre for Supercomputing
• Matt Williams, AI Supercomputing Infrastructure Specialist, Bristol Centre for Supercomputing
• Richard Gilham, AI Supercomputing Infrastructure Specialist, Bristol Centre for Supercomputing

Summary from demonstrators:

Colleagues from the Bristol Centre for Supercomputing (BriCS) were proud to showcase Isambard-AI at AI UK 2025, giving attendees a first-hand look at the UK’s fastest AI supercomputer. As part of the University of Bristol’s commitment to driving cutting-edge research in AI and high-performance computing (HPC), our stand became a bustling focal point for discussions on how Isambard-AI can accelerate innovation with positive impacts across science, industry, and society.

We were delighted to speak with a steady stream of researchers, academics, industry leaders and policy makers, eager to understand how BriCS and the University of Bristol are shaping the future of AI computing in the UK. With the sheer computational power of Isambard-AI, capable of supporting everything from training large-scale AI models to complex climate science and healthcare projects, there was plenty to talk about.

Day 1 of AI UK was particularly exciting as we welcomed Feryal Clark, Minister for AI and Digital, and Jean Innes, CEO of the Alan Turing Institute, to the stand. Both were keen to handle a chip identical to those powering Isambard-AI and discuss the potential use of waste heat water for local infrastructure.

AI UK 2025 was an exciting opportunity for BriCS to demonstrate both the capabilities of Isambard-AI and the unprecedented rate of its construction. What an opportunity to show how the University is living up to the accolade of AI University of the Year. The enthusiasm and engagement we saw at the stand was palpable and we look forward to building on new connections in the months ahead.

The University of Bristol runs an internal process to applying for time on Isambard-AI phase 1. The next application round is due to launch by late-March, for projects starting in early May. The application process will follow a similar format to Isambard 3; further details to follow. The national call for access to Isambard-AI phase 1 is run through UKRI. This expression of interest call is open to all researchers throughout the UK.

Towards Wearable Assistive AI

Footage captured from wearable cameras are the base of assistive technologies. By analysing this footage, the intention, skill and memory of the user can be recorded. This will enable assistance, improving one’s skill and augmenting one’s memory. Advanced research at the University of Bristol is making steps towards this future. This stand allowed visitors to experience the latest in Egocentric Vision covering hardware advances through their partnerships with major players like Meta and Apple.

Demonstrators

• Rhodri Guerrier, PhD student, School of Computer Science
• Siddhant Bansal, PhD student, School of Computer Science
• Michael Wray, Lecturer, School of Computer Science

Summary from demonstrators:

We all found the experience at the AI UK conference both enjoyable and valuable. The stand was setup for our arrival so we could get started straight away and focus on presenting, which was very nice. We found it really enjoyable being able to talk with so many people from so many different backgrounds. Not only did this help us improve our presentation skills, as we had to adapt to each new person, it also exposed us to different opinions and use cases of the technology that we would not normally be exposed to when just working within our lab. For example, we talked with lawyers, regulators, business leaders, government officials and many more. It is not often that we get to discuss our work outside the scope of purely research, so we found this both insightful and challenging. We also really liked the format as it allowed us to have a nice break during the talks before getting started again when more attendees emerged on the exhibition floor. Finally, we would like to say a huge thank you to the organisers for all their help and to the catering staff as well. The food was delicious.

All University of Bristol researchers (from PhD student and up) are entitled to a day of free data science support from the Ask-JGI helpdesk. Just email ask-jgi@bristol.ac.uk with your query and one of our team will get back to you to see how we can support you. You can see more about how the JGI can support data science projects for University of Bristol based researchers on our website.

We support queries from researchers across all faculties and in this blog we’ll tell you about some of the researchers we’ve supported from the Faculty of Arts, Law and Social Sciences here at the University of Bristol.

YouTube Comment Scraping

One researcher got in touch for advice about scraping data from the YouTube comment section. They were interested in collecting all the comments for a set of videos so that they could analyse sentiment and engagement with the videos’ content. While this wasn’t something we’d done before, we spent some time reading about the subject and found that the official YouTube Data API (https://developers.google.com/youtube/v3) was suitable for this work (no 3rd party tools needed!). We discussed this with the client, and based on their needs, suggested that we use the official Python client as a simple and flexible way to interact with this data source.

While the researcher was relatively new to Python, they expressed an interest in learning for the project. While we wrote the code and documentation for the comment scraping pipeline, the researcher went through some of the Python courses that the JGI offers (https://bristol-training.github.io/). This way, we were able to meet with them again after a few weeks to go through the code together, and make sure everything was understood and in a usable state.

Cross-platform comparison of social media posts quoting a Greek poet

One query we supported revolved around a cross-platform comparison of social media posts quoting a specific Greek poet. The study aimed to collect posts from TikTok, Tumblr, and Pinterest to identify the most popular poem quotes and analyse how frequently they were misattributed. While researchers working with platforms like X, Facebook, or YouTube can often find established data collection methods, niche platforms pose unique challenges. A key difficulty was determining the right data sample size across platforms. Three of them form unique social networks with different engagement metrics, making it unclear how many posts would be sufficient for a meaningful analysis. Through collaboration, we worked together to understand the research question better and adapted methodological aspects of this research design. We also explored alternative analysis approaches, including network analysis, to better understand how posts spread on these platforms and to assess the reach of these quotations.

Code review for cross-sectional survey on food insecurity

A PhD student working in anthropology and social policy attended some of the free coding courses the JGI offers (https://bristol-training.github.io/).  Since this initial encounter with R, they have been using R for their data analysis. As their supervisors do not work with R, the student found themselves in need of additional feedback on their R based project. Specifically, they wanted to make sure that their approach to and interpretation of Principle Component Analysis is on the right track. So the student contacted Ask-JGI for a second opinion on their analysis, and they wish to have their R code reviewed to make sure it was all working correctly. We are happy to have offered them the support they needed and to confirm that they were on the right track!

Fuzzy Matching for Job Postings Analysis

We assisted researchers from the Business School with the data collection process for their job postings analysis. This involved extracting and analysing job postings data to understand how companies invest in specific skill sets, especially those related to cutting-edge technologies like AI.

One of the initial hurdles we faced was matching company names from the provided list with those found in job postings. Even though this might sound straightforward, company names can vary significantly. We encountered abbreviations and slight variations in spelling. A simple exact match would not be sufficient. That’s where fuzzy matching came into play. We used algorithms that can identify similar strings, even with minor differences. This allowed us to accurately link our company list to job postings, even when the names weren’t perfectly aligned. This was crucial for capturing the broadest possible range of relevant data.

The sheer volume of job posting data presented another significant challenge. We were dealing with potentially millions of records, processing this data requires substantial computational resources. To tackle this, we utilized High-Performance Computing (HPC). HPC allows us to distribute the workload across multiple processors, significantly accelerating the data processing and analysis. This was essential for handling the massive datasets and complex algorithms involved in fuzzy matching.

Visualising historical networks of Chinese and Eurasian elites in the British Empire

We are working with a PhD researcher in the History department. In this case, the Ask-JGI team is offering assistance in exploring the use of network visualisation and analysis tools. These might be otherwise not as easily accessible to researchers when the methods are considered interdisciplinary in their home discipline. And Ask-JGI helps to bridge that gap. The PhD project involves mapping the network of powerful individuals in the British Empires across the late 19th and early 20th centuries. This network is complex, as individuals are connected with one another through different types of ties, such as family relations, alumni networks, business partnerships, and political organisations. Visualising these ties as a network of heterogenous nodes and edges helps the researcher to effectively communicate the subject of the research. Through our conversations, we bring clarity to concrete next steps in the analysis of the dataset. We also offered learning resources and advice on alternative analytical methods that can be applied to distil insights on how interpersonal connections and social capital might have translated to power in the historical context.