This is the first webinar in the four-part series called "AI in innovation: Unlocking R&D with data-driven AI."
Join a panel of AI and data experts as they explore the perils, pitfalls and promise of generative AI for R&D. From poor data to the frame problem, RAG and vector-based IR, they'll outline the issues that can derail your AI projects. They’ll also answer your questions about how Elsevier licenses, delivers and updates data for use in generative AI.
Don’t miss the insights of these data science and AI experts who specialize in R&D applications. You’ll end this session with a practical checklist to foresee and forestall project blockers.
Wednesday, November 8, 2023 · 3:00 p.m.
Duration: 1 hour
Who can attend
Dial-in available? (listen only)
Implementing AI: Journey of experimentation
Evolving with AI: How generative AI has opened new opportunities
Director of Data Science & Professional Services, SciBite
Joe’s academic background sits in compbio and the application of ML based analytics to semantic knowledge graphs, particularly in the context of drug repositioning. Since leaving academia Joe has focussed on applying SoTA technology to a wide...
Zen’s academic background is in Environmental Science, with a focus on modelling and policy. He has contributed to UK, EU and industry consultations on the commercial, statutory, IP and privacy implications of data science and artificial...
Jane leads the Ontologies technical and services team at SciBite. She holds a PhD in Genetics from Cambridge University and has 20 years’ experience working with biomedical ontologies, including at EMBL-EBI and the Wellcome Sanger Institute. She...
Vice President of Data Science, Life Sciences, Elsevier
Mark has been an active player in multiple waves of digital transformation throughout his 20+ year career in Elsevier. He was part of the team that developed and implemented Elsevier’s journal and book data standards, powering the transition from...