Hala Nelson

Because historically Data and AI have evolved within relatively separate communities, their capabilities, benefits, and adoption strategies are valued differently by different work teams and investment decision makers.

With easier access to expert knowledge, we are in the midst of a significant shift in the technical education and publishing landscapes. Do these advancements propel us toward educational bliss or do they pose unprecedented threats to industry and academia?

I will describe my own journey from academia and mathematics to the worlds of AI and data, the treacherous waters that I encountered, and my attempt to remedy that by bridging the gaps between science, technology, engineering, mathematical modeling, computation, AI, and everything data.

In this talk, Hala will be making the case that the fastest way to get into the AI field and to apply it successfully is to study AI's underlying mathematical foundation, and to understand the symbiotic interdependence between AI and math.