Player FM 앱으로 오프라인으로 전환하세요!
#100 Dr. PATRICK LEWIS (co:here) - Retrieval Augmented Generation
Manage episode 355005155 series 2803422
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
149 에피소드
Manage episode 355005155 series 2803422
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
149 에피소드
모든 에피소드
×플레이어 FM에 오신것을 환영합니다!
플레이어 FM은 웹에서 고품질 팟캐스트를 검색하여 지금 바로 즐길 수 있도록 합니다. 최고의 팟캐스트 앱이며 Android, iPhone 및 웹에서도 작동합니다. 장치 간 구독 동기화를 위해 가입하세요.