Rapid prototyping is a process that quickly develops, experiments with, and learns how software technologies might further prove that a concept is advantageous for a mission, business, or user. It is about accepting and embracing an uncertain world that rapidly evolves – and for software systems to rapidly evolve with it.
The nature of federal work is changing, and OPM wants to ensure that agencies can adequately equip federal workers to adapt.
Smart investments today are key to achieving stable footing and maximizing cybersecurity for the future. As you consider the risks and opportunities ahead, artificial intelligence (AI) offers real potential to strengthen cybersecurity operations and defend computer networks.
AI World Government gathers leaders from across government, technology innovation, business and research to present the state of the practice and state of the technology to assist the public sector in leveraging advanced intelligent technologies to enhance government services.
Ensuring that you implement artificial intelligence into your mission in a responsible manner can be a daunting task. While there is no silver bullet, being aware of the trade-offs empowers leaders to navigate the grey in a way that aligns with the values of the organization.
The role of a data analyst is evolving in the era of emerging artificial intelligence (AI). So much so, we might need to relabel this role as Analyst 2.0. Here’s a look at what Analyst 2.0 means for the next-gen data guru helping organizations use data for better decision-making.
Between policy, guidelines, past experience and data, getting the answer to simple questions is a significant drain on precious time and resources. Can AI help?
It’s been 20 years since the Global Positioning System (GPS) changed the game for civil, military and intelligence communications. Today, the secret sauce in GPS-enabled solutions is Positioning, Navigation, and Timing (PNT) information.
Advanced AI solutions require robust data pipelines to transform raw data into business value. Here’s how.
Successful AI adoption requires forethought and preparation. Although AI itself requires a culture open to experimentation and learning from mistakes, when it comes to ethics, risk, and compliance, you can’t simply wing it.