Accelerate Programme for Scientific Discovery

📢 New blog! Find out how Research Assistant Radzim Sendyka has been working with Neil Lawrence, Diana Robinson and Jonathan Tenney to explore the use of machine learning to gain new insights in Assyriology. Using data science in this project has revealed new connections across tablets and has demonstrated potential time savings for researchers in the field which with up to 10,000 tablets and each tablet taking 3-5 minutes to input is significant for generating new insights. Read the full post: https://bit.ly/3ZKgdgD

Want to start a new project using AI in 2025? AI Clinic sessions in January are open for booking. Our free clinic offers support from our Machine Learning Engineers on all aspects of using AI in your research. Initial online sessions are 30 minutes, with opportunity to schedule further sessions as needed. Open to PhD students & staff University of Cambridge. Book your slot now: https://bit.ly/4fG99J9

We are pleased to share the graphics from our AI for Science summit which took place in November. Check out the images for details from the talks and panel discussions! Thanks to Scriberia for capturing the event!

We are pleased to announce that booking is now open for our training courses next term! Courses are open to all PhD students and staff University of Cambridge - sign up now to develop your AI skills and apply them in your research. From an introduction to Large Language Models or Diffusion Models to opportunities to use your AI skills on real world data in our hands on workshops, our courses offer a range of material to suit all levels of experience. Find out more and book: https://lnkd.in/eYZeWq-W

This year, in addition to the 13 projects funded through our 2024 call, we are delighted to announce 4 projects funded through our impact funding scheme. This scheme has run as a trial for projects previously funded through the Accelerate - Cambridge Centre for Data-Driven Discovery call to translate promising approaches or prototypes developed by projects into real-world impact. With the support of this scheme: 📰 Dr Anne Alexander (Cambridge Digital Humanities), Irving Huerta and collaborators will build capacity in the use of machine learning for public interest journalism. 💊 Dr Ed Harding (Institute of Metabolic Science-Metabolic Research Laboratories) will develop a digital platform to increase the accessibility of research into pre-clinical phenotyping and drug discovery. 🩺 Dr Ines Prata Machado and Ellie Wolmark (Cancer Research UK Cambridge Centre, Department of Oncology) will convene patients, academics and policy makers to develop resources that communicate the current state of AI research in medical sciences to the public and UK policy makers. 🧑⚖️ Professor Felix Steffek (Cambridge Faculty of Law) and Holli Sargeant will engage legal professionals with their technical work using AI to predict the outcome of court cases.

We are delighted to announce the 2024 Accelerate Science - Cambridge Centre for Data-Driven Discovery funded projects. Projects will catalyse discoveries to accelerate scientific progress & create AI tools capable of delivering benefits for science & society. Projects range from developing tools to automate and optimise scientific workflows to applied research exploring the impact of LLMs on student learning and the use of machine learning to reduce illegal hunting in sub-Saharan Africa. Details of all 13 projects can be found in the full announcement: bit.ly/4ikKL1b Congratulations to all of our awardees: Alexandre Almeida, Department of Veterinary Medicine Boris B., Cavendish Laboratory - Department of Physics at the University of Cambridge Zhongying Deng, Department of Applied Mathematics and Theoretical Physics Charles A. Emogor, PhD and Anil Madhavapeddy, University of Cambridge Department of Computer Science and Technology Megan Ennion and Ros McLellan, Faculty of Education Máiréad Healy and Zoe Kourtzi, Department of Psychology Golnar Mahani Cancer Research UK Cambridge Centre, Early Cancer Institute, University of Cambridge Zidong Liu and Feryal Erhun, Cambridge Judge Business School Runhao Lu and Alex Woolgar, MRC Cognition and Brain Sciences Unit Alexis MacIntyre and Lidea Shahidi, MRC Cognition and Brain Sciences Unit Dr Anna Breger, working with Carola Schönlieb, Department of Applied Mathematics and Theoretical Physics Jakob Träuble Träuble and Gabriele Kaminski Schierle, Cambridge University Department of Chemical Engineering and Biotechnology Joe W. & Jack Atkinson Atkinson at the Institute of Computing for Climate Science (ICCS)

New blog! Eleanor Wolmark, Programme Manager of the Mark Foundation Institute for Integrated Cancer Medicine at the Cancer Research UK Cambridge Centre shares updates from the Integrated Cancer Medicine Symposium. Funded by Accelerate & @CambridgeC2D3, Eleanor & co-I Mireia Crispin hosted an event exploring AI in cancer care bringing together academics, clinicians and patients. Find out more: https://bit.ly/3BfiIiL

#AI has often struggled to connect technology to widespread social benefit. The result is a growing gap between AI’s technical capabilities and our ability to deploy these capabilities to deliver real-world public benefit. At a time when the UK has an opportunity to refresh its national approach to AI, how can we translate high-level policy ambitions into practical action? In partnership with the Minderoo Centre for Technology and Democracy and the Bennett Institute for Public Policy, our new policy brief takes stock of where further action could help create a world-leading UK AI ecosystem. In the next phase of AI policy development there is an opportunity to: 🔷 Connect to public interests and concerns 🔷 Build regulatory capacity for innovation 🔷 Design our public innovation infrastructure to tackle real-world problems 🔷 Grow the domestic base No matter which path is chosen, success requires a shift in how policy is implemented, so that any new interventions tackle the practical barriers to delivering widespread public benefit from AI. ⬇️ Find out more and read our report https://lnkd.in/dg9eSi4Q #CambridgeUniversity #AIforsociety Gina Neff | Neil Lawrence | Jessica Montgomery | Diane Coyle | University of Cambridge | CRASSH | Cambridge Digital Humanities | Department for Science, Innovation and Technology

Looking for support with an AI query or some advice on getting started using AI in your research? We have some remaining AI clinic slots this Thursday - book now for free expert advice from our Senior Machine Learning Engineer: https://bit.ly/4eYLUs7 Open to all University of Cambridge staff & PhD students, our clinic provides free support at all stages of using AI in your research. From a one off call to longer form collaboration, book a slot to find out how we can help you.

I wrote an op-ed for the Financial Times that describes how to bridge the gap between supply and demand in the Innovation Economy. https://lnkd.in/ecbt-n3Y More details at 17:30 today, Fitzwilliam College at the Bennett Public Policy Lecture. https://lnkd.in/eXfDyRvr