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Thursday, November 7, 2024 Not much time to write today and tomorrow. # Linkblog items for the day. I assumed that Trump and Netanyahu were bosom buddies. politico.eu NewsBlur's native macOS App offers news notifications directly on your desktop. newsblur.com AI search could break the web. technologyreview.com With this latest deal, Flipboard looks to build a news ecosystem beyond X. techcrunch.com Trump's second administration "seems" focused on hiring loyalists. npr.org Trump's Win Driven by Targeted Communications. politicalwire.com Donald Trump to face many California legal challenges. sfstandard.com 7 Out of 10 Pro-Choice Amendments Passed. Trump Could Override Them All. jezebel.com Secondhand EVs will flood the market in 2026, JD Power says. arstechnica.com Kamala is Gone-a-La. threads.net I missed this piece by Dan Gillmor in October about the 30th anniversary of Scripting News. Dan was the first journalis...

23ai Vector Search & RAG Nov 7, 2024 · 10 min read Introduction In my previous post, 23ai Vector / Semantic Search in APEX , I described how to incorporate 23ai Vector Search into your APEX Applications. In this post, I will take this solution further and explain how to combine Vector Search with Generative AI to build a Retrieval-Augmented Generation (RAG) solution. 💡 I recommend you read the previous post before this one. What is RAG? Retrieval-augmented generation (RAG) is a technique in natural language processing (NLP) that combines retrieval-based methods with generative models to produce more accurate, contextually relevant, and up-to-date responses . The core idea behind RAG is to enhance the capabilities of large language models (LLMs) by providing access to external knowledge sources during the response generation process (this is where 23ai comes in). For this post, we will create a RAG solution for APEX Developer Blogs. We will use 23ai Vector Sear...