Fernando Lucini is a managing director of Applied Intelligence and the Global Data Science & ML Engineering Lead, Accenture. He joins me on the Tech Talks Daily podcast to discuss synthetic data.
We explore how privacy concerns and process issues are still holding businesses back from developing advanced analytics initiatives – and how synthetic data (artificially generated by an AI algorithm) might be able to help.
We discuss how the technology has potential across a range of industries. Synthetic data’s most obvious benefit is that it eliminates the risk of exposing critical data and compromising the privacy and security of companies and customers.
With synthetic data, a company can quickly train machine learning models on large data sets, accelerating the processes of training, testing, and deploying an AI solution. While the benefits of synthetic data are compelling, realizing them can be difficult.
Generating synthetic data is a highly complex process, and to do it right, an organization needs to do more than plug-in an AI tool to analyze its data sets. We discuss how the task requires people with specialized skills and truly advanced knowledge of AI.
In order to scale AI effectively, there are three critical steps or success factors, you should consider: align your AI strategy to your business strategy, make sure you have the right people and capabilities, and ensure you have strong governance processes and responsible AI frameworks in place. Learn more Here.
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