AUSTIN + ON-DEMAND | March 20-21, 2024

Hasham Ul Haq

Senior Machine Learning Engineer at John Snow Labs

Hasham Ul Haq is a Sr. Machine Learning Engineer at John Snow Labs. During his carrier, he has worked on numerous projects across various sectors, including healthcare. At John Snow Labs, his primary focus is training and integration of LLMs in the biomedical domain, so that they are reliable and hallucination-free. In particular, a key area of research is reduction of model size and complexity using distillation. Hasham also has an active research profile with publications in NeurIPS, AAAI, and multiple scholarship grants and affiliations. He has also been mentoring startups in applying generative AI for computer vision.

Watch in-person: March 20 @ 10:40 – 11:00am CT

Fueling the Data Engine: How LLMs Can Ignite Your Data Enablement Strategy

Large language models provide a leap in capabilities on understanding medical language and context – from passing the US medical licensing exam to summarizing clinical notes. They also suffer from a wide range of issues – hallucinations, robustness, privacy, bias – that pose major compliance and reputation risks. This talk shares currently deployed software, lessons learned, and best practices that John Snow Labs has learned while enabling academic medical centers, pharmaceuticals, and health IT companies to build LLM-based solutions. We’ll also cover benchmarks for answering two key questions when delivering state-of-the-art accuracy for Generative AI systems: First, How well do general-purpose LLMs performs versus healthcare-specific LLMs? And second, in what cases do LLMs under-perform small, task-specific models?