The agency's first-ever director of artificial intelligence lays out ambitious plans to leverage AI toward improved care.
The office is focused on an integrated award environment and a common acquisition platform.
AI leads focus on "low-hanging fruit" closely aligned with departmental needs and goals.
Various agencies are finding success in early use cases for AI, machine learning and RPA.
DHA and GSA executives provide updates and insights on federal agency IT modernization projects and training.
Leaders and stakeholders across federal government agencies weigh the implications of artificial intelligence.
A new National Academy of Public Administration book analyzes the intersection of the technology on public administration.
This year's executive plan is all about "action and impact" for IT modernization, according to Federal CIO Suzette Kent.
The administration’s new American AI Initiative drew attention mostly for its cyber operations and security plans, but it also focused on healthcare and the need to infuse AI.
Government officials from the Executive Office of the President and the Defense Department discuss the state of AI adoption and implementation.
Genome analysis can now be done offline and on the spot, thanks to an algorithm researchers have adapted to perform accurate analysis with less computer memory than current programs.
Agencies look to make electromagnetic-spectrum sharing more efficient as the number of connected devices grow.
Representative Will Hurd continues to advocate for federal IT reform, including for AI, cybersecurity and telecommunications, in 116th Congress.
DARPA's Information Innovation Office experiments with MediFor program platform to combat visual media manipulation.
DARPA's Information Innovation Office seeks to balance hardware specialization and programmability in new program.
Some programs look toward advancements that could affect other government uses of AI, including law enforcement, emergency response and medical uses.
DARPA wants to use AI to detect AI attacks before they can do damage.
The adoption of machine-learning techniques is contributing to a worrying number of research findings that cannot be repeated by other researchers.