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#100 Dr. PATRICK LEWIS (co:here) - Retrieval Augmented Generation
#100 Dr. PATRICK LEWIS (co:here) - Retrieval Augmented Generation
ratings:
Length:
26 minutes
Released:
Feb 10, 2023
Format:
Podcast episode
Description
Dr. Patrick Lewis is a London-based AI and Natural Language Processing Research Scientist, working at co:here. Prior to this, Patrick worked as a research scientist at the Fundamental AI Research Lab (FAIR) at Meta AI. During his PhD, Patrick split his time between FAIR and University College London, working with Sebastian Riedel and Pontus Stenetorp.
Patrick’s research focuses on the intersection of information retrieval techniques (IR) and large language models (LLMs). He has done extensive work on Retrieval-Augmented Language Models. His current focus is on building more powerful, efficient, robust, and update-able models that can perform well on a wide range of NLP tasks, but also excel on knowledge-intensive NLP tasks such as Question Answering and Fact Checking.
YT version: https://youtu.be/Dm5sfALoL1Y
MLST Discord: https://discord.gg/aNPkGUQtc5
Support us! https://www.patreon.com/mlst
References:
Patrick Lewis (Natural Language Processing Research Scientist @ co:here)
https://www.patricklewis.io/
Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks (Patrick Lewis et al)
https://arxiv.org/abs/2005.11401
Atlas: Few-shot Learning with Retrieval Augmented Language Models (Gautier Izacard, Patrick Lewis, et al)
https://arxiv.org/abs/2208.03299
Improving language models by retrieving from trillions of tokens (RETRO) (Sebastian Borgeaud et al)
https://arxiv.org/abs/2112.04426
Patrick’s research focuses on the intersection of information retrieval techniques (IR) and large language models (LLMs). He has done extensive work on Retrieval-Augmented Language Models. His current focus is on building more powerful, efficient, robust, and update-able models that can perform well on a wide range of NLP tasks, but also excel on knowledge-intensive NLP tasks such as Question Answering and Fact Checking.
YT version: https://youtu.be/Dm5sfALoL1Y
MLST Discord: https://discord.gg/aNPkGUQtc5
Support us! https://www.patreon.com/mlst
References:
Patrick Lewis (Natural Language Processing Research Scientist @ co:here)
https://www.patricklewis.io/
Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks (Patrick Lewis et al)
https://arxiv.org/abs/2005.11401
Atlas: Few-shot Learning with Retrieval Augmented Language Models (Gautier Izacard, Patrick Lewis, et al)
https://arxiv.org/abs/2208.03299
Improving language models by retrieving from trillions of tokens (RETRO) (Sebastian Borgeaud et al)
https://arxiv.org/abs/2112.04426
Released:
Feb 10, 2023
Format:
Podcast episode
Titles in the series (100)
CURL: Contrastive Unsupervised Representations for Reinforcement Learning by Machine Learning Street Talk (MLST)