Chicago ML at 1871

Chicago ML and Why of AI are joining forces to co-host this event at 1871. We're delighted to present two talks, both covering LLMs. The first is a case study of ML engineering and the second an analysis of how LLMs are changing the way we program.

Improving Radiology with LLMs
Angelina Leigh and Narasimha Kamath Ardi present their work on an LLM implementation to improve efficiency of CT scans and MRIs in medical applications. They show an end-to-end pipeline that saves radiologists hours in the protocol assignment process, improving the speed and quality of critical imaging services to patients.

AI Product Stack - What’s Working, What’s Not, and Where We Go From Here
This talk will explore the state of the large language model space. We’ll start by exploring stack considerations for modern LLM-based applications. After reviewing a case study in data science automation, we’ll examine the underlying subtext: How far can we take modern LLMs? What are the current limitations of RAG? How might we think about the impact of downstream influences on the behavior of complex LLM systems? We’ll conclude with some philosophical remarks and considerations for evaluating the success of future intelligent applications.

About the speakers

Angelina Leigh is a former Data Scientist at Hitachi who specialized in NLP for Healthcare leveraging John Snow Labs. For the past two years, she has been working as a Solutions Architect at Databricks within the Healthcare and Life Sciences vertical. She works closely with customers to understand their specific data challenges and requirements, then designs and deploys solutions that harness the power of the Databricks platform.

Narasimha Kamath Ardi is a former Applied Machine learning Scientist at W.W. Grainger, Inc. Nara specialized in NLP for Manufacturing leveraging Databricks at W.W. Grainger, Inc. He has been associated with Databricks for the past 1 year as a Delivery Solutions Architect, catering customers from Healthcare and Life Sciences industry. He has been working with the customers to help accelerate their use cases and drive Databricks platform adoption.

Hayden Lewis is an Innovation Specialist at TRG, an advertising and brand marketing agency. In his role, Hayden experiments with builds with emerging technologies and develops innovative solutions for clients and internal teams. His interest in AI took root in graduate school at the University of Missouri, where his masters thesis looked at how AI is portrayed in the media. He lives in Chicago and has a BJ/MA from the University of Missouri.

About the sponsors

Why of AI® helps organizations identify, prioritize, and design the best AI use cases for their business and customers. Why of AI exists to help professionals and organizations understand AI, develop successful AI strategies and navigate this ever-changing landscape successfully.