Episode

Language Understanding and LLMs with Christopher Manning - #686

Podcast
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Published
May 27, 2024
Duration seconds
3370
Processing state
failed
Canonical source
https://twimlai.com/podcast/twimlai/language-understanding-and-llms/
Audio
https://pscrb.fm/rss/p/traffic.megaphone.fm/MLN7587334756.mp3?updated=1716953241
JSON
/v1/public/podcasts/twiml-ai-podcast/episodes/language-understanding-and-llms-with-christopher-manning-686
Markdown
/podcast/twiml-ai-podcast/language-understanding-and-llms-with-christopher-manning-686.md

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Summary

Today, we're joined by Christopher Manning, the Thomas M. Siebel professor in Machine Learning at Stanford University and a recent recipient of the 2024 IEEE John von Neumann medal. In our conversation with Chris, we discuss his contributions to foundational research areas in NLP, including word embeddings and attention. We explore his perspectives on the intersection of linguistics and large language models, their ability to learn human language structures, and their potential to teach us about human language acquisition. We also dig into the concept of “intelligence” in language models, as well as the reasoning capabilities of LLMs. Finally, Chris shares his current research interests, alternative architectures he anticipates emerging beyond the LLM, and opportunities ahead in AI research. The complete show notes for this episode can be found at https://twimlai.com/go/686.