We investigate how language models leverage context, accounting for various level of language analysis from lexical, semantics and pragmatics viewpoints, and conclude with a discussion on the how context plays...
The current data stack is built on top of foundations laid down a decade ago for tabular data. But AI datasets are much more complex and workloads are much more...
Quantization is an excellent technique to compress Large Language Models (LLM) and accelerate their inference. In this session, lets explore different quantization methods and techniques, the common libraries used and...
Literature reviews are a critical component of evidence-based medicine, serving as a structured approach to addressing clinical questions by systematically analyzing the breadth of published academic literature. However, traditional methods...
This talk draws from the paper “LLMs Will Always Hallucinate, and We Need to Live With This” and presents a critical analysis of hallucinations in large language models (LLMs), arguing...
Demos
See More