LQG 2024/06/04 – 18:30 – Whither AI? – Gary Kazantsev – at Bloomberg – IP *OLO* Hybrid

Whither AI?

Alternative title:  Investing in Uninvestable Markets

Seminar by Gary Kazantsev

2024/06/04 – In-Person and On-Line – Hybrid!

The LQG is very grateful to Bloomberg for hosting this in-person and on-line hybrid LQG.

AI is changing the financial industry, and indeed, the world, at an ever accelerating pace. The current generation of AI models is different from the previous state of the art in important ways. Large transformer models are broadly capable – exhibiting state-of-the-art, and even human-level performance, on many tasks without problem-specific training – and uniquely accessible, allowing non-experts to interact with them using natural language. Nonetheless, they also have important limitations. What is real, and what is hype? What are they capable of, and what can’t they do? In this talk, we will explore the current state of the art in AI applications, discuss the challenges of AI adoption in the enterprise, and talk about the risks and future directions of AI development.


Gary Kazantsev

Adjunct professor at Columbia University
Head of Quant Technology Strategy in the Office of the CTO at Bloomberg

Gary is the Head of Quant Technology Strategy in the Office of the CTO at Bloomberg. Prior to taking on this role, he created and headed the company’s Machine Learning Engineering group, leading projects at the intersection of computational linguistics, machine learning and finance, such as sentiment analysis of financial news, market impact indicators, statistical text classification, social media analytics, question answering, and predictive modeling of financial markets.
Prior to joining Bloomberg in 2007, Gary had earned degrees with distinction in physics, mathematics, and computer science from Boston University.
He is engaged in advisory roles with FinTech and Machine Learning startups and has worked at a variety of technology and academic organizations over the last 20 years. In addition to speaking regularly at industry and academic events around the globe, he is a member of the KDD Data Science + Journalism workshop program committee and the advisory board for the AI & Data Science in Trading conference series. He is also an adjunct professor at Columbia University, and a co-organizer of the annual Machine Learning in Finance conference at Columbia University