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Best Practices for Building the AI Development Platform in Government 


The US Army and other government agencies are defining best practices for building appropriate AI development platforms for carrying out their missions. (Credit: Getty Images) 
By John P. Desmond, AI Trends Editor 
The AI stack defined by Carnegie Mellon University is fundamental to the approach being taken by the US Army for its AI development platform efforts, according to Isaac Faber, Chief Data Scientist at the US Army AI Integration Center, speaking at the AI World Government event held in-person and virtually from Alexandria, Va., last week.  
Isaac Faber, Chief Data Scientist, US Army AI Integration Center
“If we want to move the Army from legacy systems through digital modernization, one of the biggest issues I have found is the difficulty in abstracting away the differences in applications,” he said. “The most important part of digital transformation is the middle layer, the platform that makes it easier to be on the cloud or on a local computer.” The desire is to be able to move your software platform to another platform, with the same ease with which a new smartphone carries over the user’s contacts and histories.  
Ethics cuts across all layers of the AI application stack, which positions the planning stage at the top, followed by decision support, modeling, machine learning, massive data management and the device layer or platform at the bottom.  
“I am advocating that we think of the stack as a core infrastructure and a way for applications to be d …

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