Weaviate Podcast
Weaviate Podcast
Weaviate
Nils Reimers on Cohere Embedding Models
55 minutes Posted Jan 11, 2023 at 3:00 pm.
Cohere X Weaviate
Welcome Nils Reimers!
Origin Story
Learning Text Embeddings
Positive and Negative Sampling in Contrastive Learning
1 Billion Pairs for Text Embedding Optimization
Impact of Data Quality
New Cohere Multilingual Model!
Challenge of Debugging Multilingual Models
Intent in Search
Thoughts on ColBERT
Sparse Vectors in Search
Long Documents and Multi-Discourse
Entity Parsing in Query Understanding
Unknown Words and Distribution Shift
Re-Vectorizing with Fine-Tuning
More on Search Interfaces and Intent in Search
Thank you Nils!
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Show notes
Weaviate podcast #33.
Thank you so much for watching the 33rd Weaviate Podcast! This episode features one of the heroes of Deep Learning for Search, Nils Reimers! Nils' work on SentenceBERT is one of the foundational works for applying Deep Representation Learning to text search. This is the idea that personally inspired me to work in this field. Having seen the successes of Contrastive Representation Learning for Computer Vision, I was mind-blown by the possibility of this for NLP and text search. In addition to the scientific foundation, the software development of the Sentence Transformers library and BEIR benchmarks has been enormously impactful! It was an honor getting to ask Nils the questions I have about these things, from the role of Data Quality to Intent, Sparse Vectors, Long Document Encoding, Distribution Shift, and many more. I really hope you enjoy the podcast! We are so excited about the Cohere Multilingual embedding model and can't wait to see what else comes out of Cohere and their amazing team!
Cohere Multilingual ML Models with Weaviate: https://weaviate.io/blog/2022/12/Cohe...
Nils Reimers: https://scholar.google.com/citations?...
Mentioned in the podcast,
Cross-Encoders: https://weaviate.io/blog/2022/08/Usin...
How to choose a Sentence Transformer from HuggingFace: https://weaviate.io/blog/2022/10/How-...
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