Do you know that without human intervention the Generative AI responses would be too toxic after training the model from the garbage on Internet? Do you know that OpenAI hired Kenyan workers to make ChatGPT less toxic? To throw in some jargon, this is called RLHF (reinforcement learning with human feedback). Not sure who Microsoft hired to cleanse copilots, but apparently they went overboard. Here…
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As I mentioned in my Power BI and Fabric Capacities: Thinking Outside the Box, memory limits of Fabric capacities could be rather restrictive for large semantic models with imported data. One relatively new option to combat out-of-memory scenarios that deserves to be evaluated and added to the list if Fabric is in your future is semantic models configured for Direct Lake storage. The blog covers…
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Here is table that is getting more and more difficult to find as searching for Fabric capacity limits returns results about CU compute units (for the most part meaningless in my opinion). I embed in a searchable format below before it vanishes on Internet. The most important column for semantic modeling is the max memory which denotes the upper limit of memory Fabric will grant…
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Atlanta BI fans, please join us in person for the next meeting on Monday, September 3th at 6:30 PM ET. Your humble correspondent will show you how to use Large Language Models, such as ChatGPT, to create your own copilots for Text2SQL and Text2DAX. I'll also help you catch up on Microsoft BI latest. I will sponsor the event which marks the 14th anniversary of…
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I’m conducting an assessment for a client facing memory pressure in Power BI Premium. You know these pesky out of memory issues when refreshing a biggish dataset. They started with P1, moved to P2, and now are on P3 but still more memory is needed. The runtime memory footprint of the problematic semantic model with imported data is 45 GB and they’ve done their best…
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