Deep learning has changed our society as the most powerful AI tool. However, it is used without theoretical backgrounds since many techniques in deep learning are heuristics. This talk introduces some of the theoretical works on the effects of such techniques to the performance of deep learning.
Kazushi Ikeda got his B.E., M.E., and Ph.D. in Mathematical Engineering from University of Tokyo in 1989, 1991, and 1994. He joined Kanazawa University as an assistant professor in 1994 and became a junior/senior associate professor of Kyoto University in 1998 and 2003, respectively. He has been a full professor of NAIST since 2008.
As organisations increasingly adopt generative AI chatbots to navigate complex legal and policy driven environments—such as payroll, tax regulations, employment legislation, union agreements, employment contracts, and company policies—cybersecurity becomes a critical concern. This talk delves into the intersection of cybersecurity and AI within enterprise environments where chatbots and agentic systems provide assistance on sensitive and regulated information.
Richard Kenyon is the Associate Director of Datapay AI Labs. During his 25 years working in Software Engineering the power of automation has always been top of mind for releasing ‘latent capacity’ within teams. He started his career (back in the 1990s) doing post graduate research into the application of Neural Networks to Multivariate Data with application in the Biotechnology Industry for optimising Penicillin fermentations before moving into industry and has been following the advances in AI and ML ever since. He has worked on various ML based systems for analysing unstructured content including content secured in Government document management systems and is excited about the potential of GenAI and ML to build Enterprise Business Applications with Natural Language interfaces.
To be announced soon.