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Most solar plant operators running soiling sensors have noticed it at some point — the sensor reports 0.8%, but the performance ratio tells a different story. The instinct is usually to blame the sensor, schedule a calibration visit, and move on. But the gap rarely closes, and the uncertainty quietly accumulates in every report that goes to your asset owner or lender. The issue is not the equipment. It is that these two instruments were never measuring the same thing to begin with — and knowing why is more useful than replacing either one.

Will you lose your job in 10 years, thanks to AI? Throughout history, there have been many moments where technology has caused industry disruption and job losses. Perhaps like never before, the breadth of what AI can do has the ability to significantly impact the employment landscape. But with change also comes opportunity. If you’re staying at the forefront of AI technology, you’re likely to uncover key opportunities for job enhancement vs. replacement.

ChatGPT and other generative AI technology relies on large language models (LLMs) to process billions or even trillions of data points in order to deliver outputs. Is building a proprietary or forking an open-source based LLM feasible for your business? Alternatively, the major tech players like Microsoft and Google are investing in private source models that your business can explore hooking into. We’ve outlined a few considerations in this article.

Is your business currently evaluating generative AI use cases? Or, do you need some guidance on where to start? At DataLux, we’re helping businesses optimize their operations and customer experiences with generative AI. We wrote this blog article to provide a brief history of AI and discuss its practical applications. Please give it a read and reach out with any questions!