Embedding Knowledge Spaces
Matteo discusses the innovative use of embedding models to create a robust knowledge space that encompasses not just academic publications but also patents and technological advancements. He emphasizes the potential to connect research expertise with patenting activities, ultimately linking these efforts to economic value. This approach aims to enhance understanding across various fields and their implications for future developments.In this clip
From this podcast
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
NLP for Mapping Physics Research with Matteo Chinazzi - #353
Related Questions
How do vector embeddings work in the context of the episode Mindscape 280 | François Chollet on Deep Learning and the Meaning of Intelligence and the clip Understanding Language Models?
How do vector embeddings work in the context of the episode Mindscape 280 | François Chollet on Deep Learning and the Meaning of Intelligence and the clip Understanding Language Models?
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