The Future of AI Will Be Physical. Are You Ready?
Physical AI is moving from concept to reality, which means leaders will soon face innovations that feel uncomfortably close to home.
Physical AI is moving from concept to reality, which means leaders will soon face innovations that feel uncomfortably close to home.
In this video interview, Mike Gilger with Modus Operandi discusses how agencies can improve their AI outcomes with more reliable, contextual data.
Financial agencies are overwhelmed with information — stacks of paper that must be kept by law and massive amounts of digital data needed for daily mission work. With millions of documents to sort through, many teams still rely on time‑consuming manual processes that slow everything down and increase costs. These outdated workflows make it difficultRead… Read more »
When residents ask AI systems questions, the answers are often wrong. That’s because AI systems read webpages differently than humans do.
As AI becomes more common in daily life, residents increasingly expect government to follow suit. Research shows growing support for AI in local government — when it’s secure, transparent, and accessible. With clear usage policies and strong communication, agencies can adopt AI responsibly while improving service delivery and meeting evolving resident expectations.
Recent fraud regulations are creating a powerful catalyst for transformation. Agencies can leverage these changes to modernize policy and processes.
The evolution of AI coding tools has raised the prospect of “disposable software” that would reduce the need for expensive, long-term maintenance. But although appealing, this paradigm shift would be challenging for government to implement. A SpecOps approach, though, may solve the problem.
Upgrading an existing data center for AI/ML needs can be done, but there are many factors to consider.
In this video interview, Jonathan Hasak and Aaron Hunter with Coursera discuss how to overcome barriers to fostering an AI-knowledgeable workforce.
AI systems have become a source of truth for many constituents, but public-sector communication often is poorly designed for AI use and citation. Agencies may need to think about both human and AI audiences.