AI Articles and Analysis in Consumer goods

Procter and Gamble (P&G) is an American multinational goods corporation. The company is well known for its fabric & home care, family care, beauty, healthcare, and grooming products. P&G owns several of the most well-known brand names in the world, including Pampers, Tide, Gillette, Always, Head & Shoulders, and many more. 

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Problems in different industries can look quite similar when looked at from the perspective of data. Though diverse business problems originate from distinct domains and needs, they often share a common thread and solution. 

Edge AI, also known as edge intelligence, is a term that refers to the convergence of two dynamic technological trends: edge computing and Artificial Intelligence. In today's tech landscape, the proliferation of mobile devices and advancements in communication technologies have fueled the rise of edge computing, which focuses on processing data at the network edge. 

Retail fraud and loss prevention have always been significant business concerns impacting profitability and customer trust. However, with the emergence of AI technologies, there is a newfound potential to combat these challenges more effectively. 

This article is sponsored by Riskified, and was written, edited and published in alignment with our transparent Emerj sponsored content guidelines.

Traditionally, responsible AI management practices are not just a matter of theoretical ethics debates but a practical matter of compliance. Financial sectors are highly regulated and monitored to ensure the safety and security of consumers and the overall economy. Many of those regulations are written so that responsible management practices are meant to avoid penalties. 

Episode summary: In this episode, we speak with Alan O'Herlihy, Founder and CEO of Ireland-based Everseen. Alan speaks to us about how machine vision systems can be used to detect theft or mistakes at a checkout counter (including forgetting to scan items, customers intentionally hiding items, and more). Alan not only explains where these technologies are in use today, but he also breaks down some of his own predictions about what these computer vision systems might make possible in the workplace of tomorrow.