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 blog.vespa.ai
Using approximate nearest neighbor search in real world applications | Vespa Blog
| | blog.reachsumit.com
Generative Retrieval for End-to-End Search Systems - Sumit's Diary
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| | Welcome to Sumit Kumar's Personal Blog!
| | 0x65.dev
Indexing Billions of Text Vectors
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| | Optimizing memory-usage for approximate nearest neighbor search
| | weaviate.io
Vector Search Explained | Weaviate
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| | Learn about vector search, a technique that uses mathematical representations of data to find similar items in large data sets.
| | jalammar.github.io
The Illustrated Retrieval Transformer - Jay Alammar - Visualizing machine learning one concept at a time.
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| Discussion: Discussion Thread for comments, corrections, or any feedback. Translations: Korean, Russian Summary: The latest batch of language models can be much smaller yet achieve GPT-3 like performance by being able to query a database or search the web for information. A key indication is that building larger and larger models is not the only way to improve performance. Video The last few years saw the rise of Large Language Models (LLMs) - machine learning models that rapidly improve how machines process and generate language. Some of the highlights since 2017 include: The original Transformer breaks previous performance records for machine translation. BERT popularizes the pre-training then finetuning process, as well as Transformer-based contextualized...