graphdatabases
By Hamid Azzawe Data has the potential to provide transformative business insights across various industries, yet harnessing that data presents significant challenges. Many businesses struggle with data overload, with vast amounts of data that are siloed and underutilized. How can organizations deal with large and growing volumes of data without sacrificing performance and operational efficiency? Another challenge is extracting insights from complex data. Traditionally, this work has required significant technical expertise, restricting access to specialized data scientists and analysts. Recen...
Info World
By Simon Bisson Once you get past the chatbot hype, it’s clear that generative AI is a useful tool, providing a way of navigating applications and services using natural language. By tying our large language models (LLMs) to specific data sources, we can avoid the risks that come with using nothing but training data. While it is possible to fine-tune an LLM on specific data, that can be expensive and time-consuming, and it can also lock you into a specific time frame. If you want accurate, timely responses, you need to use retrieval-augmented generation (RAG) to work with your data. RAG: the h...
Info World
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