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With thousands of new AI papers published monthly, many are quickly set aside and never advance beyond the labs where they originated, while others gain significant recognition and are cited extensively. Meanwhile, classic approaches like graph theory, Monte Carlo methods, ranking and search algorithms remain integral to AI solutions deployed in real-world applications every day. In this talk we will try to identify ideas from the world of GenAI that will have the most profound impact on enterprises and our daily lives.

Since the release of ChatGPT late last year, the world has finally embraced vector embeddings and many organisations (from hedge funds to giant retailers) have been experimenting with vector databases. This is because vector embeddings, a component at the heart of large language models, open-up the ability to not only compress information but also to drastically transform search and knowledge retrieval. In this session we will put a spotlight on the embedding revolution that has taken over natural language processing, computer vision, network science and explain how enterprises can build better systems to understand, interact with, and sell to their customers.