About this session
Machine language understanding and generation has been undergoing rapid improvements due to recent breakthroughs in machine learning (e.g. large language models like GPT and BERT). And while big tech and NLP engineers were quick to capitalize on these models, the broader developer community lags in adopting these models and realizing their potential in their business domains. This talk provides a gentle and highly visual overview of some of the main intuitions and real-world applications of large language models. It assumes no prior knowledge of language processing and aims to bring attendees up to date with the fundamental intuitions and applications of large language models. Hemant will also guide you through a demo of using Cohere SDK / playground.
Speakers
Hemant JainSoftware Engineer, Inference at Co:here
Hemant works on Machine Learning Inference at Cohere AI. Prior to this, he spent 3 years at NVIDIA developing Triton Inference Server, an open-source solution used to deploy machine learning models into production. He has a Masters in Data Science from the University of Washington.
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