This week we feature articles from Agustinus Nalwan, and Stephen Wolfram.
Additional reading comes from Victoria Song, Nidhi Hebbar & Christopher Savčak, and Shayne Longpre & Sara Hooker.
News comes from Ontotext, Sinequa, DataStax & LangChain, and Altova.
All previous issues are available at https://gilbane.com/gilbane-advisor-index
Opinion / Analysis
The untold side of RAG: addressing its challenges in domain-specific searches
This is the best kind of case study, clearly written by Agustinus Nalwan, the lead executive and project manager, includes detailed use-case examples, resources used, challenges, learnings, and solutions to date. This will be especially valuable for those planning or building Retrieval Augmented Generation (RAG) applications. (29 min)
How to think computationally about AI, the universe and everything
If you are not familiar with Stephen Wolfram, his Ted Talk from a couple of weeks ago is a good place to start. You’ll need to put your abstraction hat on and be prepared to be awed, but you will learn something. For others, the talk or the transcript are a quick way to reacquaint yourself with this remarkable thinker. (transcript 12 min, Ted Talk 18 min)
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Content technology news
Ontotext GraphDB 10.4 enables users to chat with their knowledge graphs
The new release offers finer grained security, improved flexibility, easier cluster administration and monitoring, and natural language queries.
Sinequa integrates enterprise search with Google’s Vertex AI
The integration brings advanced Retrieval-Augmented Generation (RAG) capabilities to the workplace.
DataStax launches new integration with LangChain
Support for Astra DB Vector Database and Apache Cassandra now available out-of-the-box for LangChain users for retrieval augmented generation.
Altova announces version 2024 with AI assistants and PDF Data Mapping
XMLSpy boosts productivity for XML and JSON development tasks by generating schemas, instance documents, and sample data based on NLP prompts.
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The Gilbane Advisor is authored by Frank Gilbane and is ad-free, cost-free, and curated for content, computing, web, data, and digital experience technology and information professionals. We publish recommended articles and content technology news weekly. We do not sell or share personal data.