This post contains a list of the AI-related seminars that are scheduled to take place between 23 January and 29 February 2024. All events detailed here are free and open for anyone to attend virtually. What to expect of Europe's ubiquitous digital identification infrastructure Speaker: Thomas Lohninger Organised by: The Digital Humanism (DIGHUM) Initiative Zoom link is here. Planning and Acting to Learn Speaker: Paolo Traverso Organised by: Italian Association for Artificial Intelligence Watch live on YouTube here. Understanding Cellular Biology across multiple scales using machine learning Speaker: Mohammad Lotfollahi Organised by: Cambridge Centre for AI in Medicine Sign up to the mailing list to receive invite to attend.

This post contains a list of the AI-related seminars that are scheduled to take place between 9 January and 28 February 2023. All events detailed here are free and open for anyone to attend virtually. Machine learning beyond the data range: extreme quantile regression Speaker: Sebastian Engelke (University of Geneva) Organised by: University of Lisbon Register here. Title to be confirmed Speaker: Mauro Maggioni (Johns Hopkins University) Organised by: University of Minnesota Check the website nearer the time for the Zoom link to join. Title to be confirmed Speaker: Alhussein Fawzi (DeepMind) Organised by: University of Lisbon Register here.

Accurately predicting how an individual's chronic illness is going to progress is critical to delivering better-personalised, precision medicine. Yet there is an enormous challenge in accurately predicting the clinical trajectories of people for chronic health conditions such as cystic fibrosis (CF), cancer, cardiovascular disease and Alzheimer's disease. AI technology developed by the Cambridge Centre for AI in Medicine and their colleagues offers a glimpse of the future of precision medicine, and the predictive power which may be available to clinicians caring for individuals with the life-limiting condition cystic fibrosis. "Prediction problems in healthcare are fiendishly complex," said Professor Mihaela van der Schaar, Director of the Cambridge Centre for AI in Medicine (CCAIM). "Even machine learning approaches, which deal in complexity, struggle to deliver meaningful benefits to patients and clinicians, and to medical science more broadly. Off-the-shelf machine learning solutions, so useful in many areas, simply do not cut it in predictive medicine."

Artificial intelligence (AI) is in the process of transforming a variety of models in the global financial services industry, a global survey jointly conducted by the Cambridge Centre for Alternative Finance (CCAF) at the University of Cambridge Judge Business School and the World Economic Forum suggests. The study, supported by EY and Invesco, demonstrates that AI is changing how financial institutions generate and utilize insights from data, which in turn propels new forms of business model innovation, reshapes competitive environments and workforces, engenders new risk dynamics and poses novel challenges to firms and policy-makers alike. The survey, which gleaned responses from 151 financial institutions, including both incumbent firms and FinTechs hailing from more than 30 countries, confirms AI as a crucial business driver across the industry in the short term. Notably, AI adopters do not appear to have specific modi operandi for implementing AI; instead, 64% expect to become mass adopters within two years, proving the growing potential of AI to stimulate innovation and growth across a wide range of business functions. FinTechs and incumbents alike are moving from mainly using AI to reduce costs to utilizing its capabilities for revenue generation, albeit pursuing different AI strategies to achieve this. Most incumbents primarily use AI to enhance existing products and services, whereas many FinTechs use it to create new value propositions, as shown in the chart below.

A new survey released by the World Economic Forum and the Cambridge Centre for Alternative Finance (CCAF) finds nearly two-thirds (64%) of financial services leaders expect to be mass adopters of Artificial Intelligence in two years compared to just 16% doing so today. These firms plan to expand AI use to purposes beyond cost reduction, using AI for revenue generation, process automation, risk management, customer service and client acquisition. In Transforming Paradigms: Global AI in Financial Services Survey, over 150 senior financial services executives in both fintech and incumbent financial institutions responded to a range of questions on the impact AI will have on the industry, concluding that there will be a significant gap between firms that quickly implement AI and firms that lag behind. Currently, 60% of firms invest less than 10% of their R&D resources on AI despite evidence of accelerating returns. Pay offs have shown to be especially strong between investment levels of 10% and 30% as well as investment levels of 30% and 40%.