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5 Hard Truths About Generative AI for Technology Leaders

Monte Carlo

That quick check of the box feels like a step forward, but if you aren’t already thinking about how to connect LLMs with your proprietary data and business context to actually drive differentiated value, you’re behind. Hard truth #3: RAG is hard. Data teams are scrambling to answer the call. That’s not hyperbole.

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5 Skills Data Engineers Should Master to Keep Pace with GenAI

Monte Carlo

Organizations need to connect LLMs with their proprietary data and business context to actually create value for their customers and employees. Right now, RAG is the essential technique to make GenAI models useful by giving an LLM access to an integrated, dynamic dataset while responding to prompts. Who can deliver?

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A guide to Generative AI terminology by Colin Eberhardt

Scott Logic

The neural network functions by propagating values through the layers of network, with the parameters governing how these various values are combined. Training - a process whereby large quantities of data are presented to the neural network, with the quality of its output evaluated in some way.