More AI & Automation Articles
The Bureau of the Fiscal Service is expanding its blockchain and robotic process automation projects.
As the federal government looks to embrace the Technology Business Management framework, Apptio believes intelligent automation and analysis can speed those efforts.
An extensive database powered by AI can help agencies accurately evaluate job candidates, assess their “behavioral DNA” and issue an instant report to human resource managers.
Relevant scientific and mathematical knowledge built into core systems may help the Defense Department overcome challenges implementing artificial intelligence applications.
Despite the advantages to robotic process automation and artificial intelligence, agencies often lack the resources and expertise that must be invested up front.
Artificial intelligence can be leveraged to predict future health complications and the interventions that will reduce risk, thereby greatly increasing veteran health and fiscal efficiency.
Governors can position their states as leaders in AV testing and adoption, a new report from the National Governors Association says.
The Department of Veterans wants an artificial intelligence solution to help minimize customer service delays by speeding information retrieval and improving the quality and accuracy of information provided.
As state and local agencies adopt automation, cloud and IoT technologies to improve their services and citizens' experience, they must also incorporate automated defenses to mitigate associated risks.
The Army will be using cloud-based machine learning software predict when Bradley Fighting Vehicles need maintenance.
The tax agency envisions a solution that can continuously learn, provide real-time monitoring of cyber threats across networks and process data across a range of IT sources and devices.
As drones are increasing being used to smuggle drugs, weapons or phones into prisons, officials are looking to technology to help them detect the unmanned aerial systems.
Defense Advanced Research Projects Agency's Learning with Less Labels program aims to reduce the amount of labeled data required to build a machine learning model.
The Air Force Research Laboratory wants to move away from printed maintenance instructions and toward projecting scaled visualizations of the task onto the machinery being serviced.
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