<a target="_blank" rel="noopener noreferrer nofollow" href="https://www.vectorpodcast.com/">https://www.vectorpodcast.com/</a>I had fun interacting with NotebookLM - mostly for self-educational purposes. I think this tool can help by bringing an additional perspective over a textual content. It ties to what RAG (Retrieval Augmented Generation) can do to content generation in another modality. In this case, text is used to augment the generation of a podcast episode. This episode is based on my blog post: <a target="_blank" rel="noopener noreferrer nofollow" href="https://dmitry-kan.medium.com/the-rise-fall-and-future-of-vector-databases-how-to-pick-the-one-that-lasts-6b9fbb43bbbe">https://dmitry-kan.medium.com/the-rise-fall-and-future-of-vector-databases-how-to-pick-the-one-that-lasts-6b9fbb43bbbe</a>Time codes:00:00 Intro to the topic1:11 Dmitry's knowledge in the space1:54 Unpacking the Rise & Fall idea3:14 How attention got back to Vector DBs for a bit4:18 Getting practical: Dmitry's guide for choosing the right Vector Database4:39 FAISS5:34 What if you need fine-grained keyword search? Look at Apache Lucene-based engines6:41 Exception to the rule: Late-interaction models8:30 Latency and QPS: GSI APU, Vespa, Hyperspace9:28 Strategic approach9:55 Cloud solutions: CosmosDB, Vertex AI, Pinecone, Weaviate Cloud10:14 Community voice: pgvector10:48 Picture of the fascinating future of the field12:23 Question to the audience12:44 Taking a step back: key points13:45 Don't get caught up in trendy shiny new tech

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Vector Databases: The Rise, Fall and Future - by NotebookLM

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