Driving Innovation With AI | Getting Ahead With DataOps and MLOps

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In these times of uncertainty – brought about by political turmoil, inflation, supply chain disruptions, and chip shortages – businesses have turned to digital solutions to claim firm ground for future operations. Machine Learning has been one of the most promising areas, with a higher level of automation and productivity and more transparency contributing to real business value. It is also one of the most exciting fields in Artificial Intelligence, given that the models, when set up correctly, are becoming increasingly independent from human guidance or input. However, borrowing from one of the findings of this survey, it is clear that only a fraction of companies considers themselves advanced in Machine Learning. Getting the most out of data requires stamina and the right approaches, with both DataOps and MLOps being crucial for ML success. At the same time, it is up to AI companies to enable their customers, not least through guidance on digital transformation strategies, intense collaboration, and, of course, sensible tools and solutions.