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Food and Beverages Tech Review | Friday, May 31, 2019
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FREMONT, CA: Supply chains have been an essential part of the physical goods world as companies invest a lot of capital on continuously optimizing and improving the supply chain. Five percent of transportation cost saving is a huge deal.
As the advances in AI begin to reshape the digital world via infusion of AI into goods handling services and processes, it will need a specific supply chain on its own, creating a mind-boggling amount of data. The collection of data should be carried out continuously by gathering, processing, redefining, and reassembling to produce the required intelligence.
Research in Big Data and analytics has showcased a similar phenomenon. But, in the case of AI, the magnitude of information is high. As the march towards enriched AI-based world has started, the big question among business leaders is whether to build an AI-specific supply chain that is owned by the companies or to be a consumer of another’s supply chain?
The consideration of an application that all organizations utilize as an example: ERP, software that manages back end processes such as accounting, project management, procurement, and manufacturing. These backend systems are the support structure of the organizations, and infused AI functionality will not only make a significant impact across the fundamental business processes but also increases profitability.
Several standard processes form a part of any given industry, but a specific set of best practices are often followed rather than creating a unique, creative solution. Cloud Software vendors have begun with the exploitation of these features by the provision of easy-to-use, AI-infused ERP applications, combining them in the minimalistic forms to power on internal data with previously trained models.
Several parts of the digital supply chain, which demanded AI are readily available today in the most user-friendly forms, thanks to technological improvements in cloud computing. Data Enrichment as a service, Self-training models, automation of Data pipeline, conversational UIs, and security is all prepped for deployment.
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