A Clear Definition of Machine Learning
There’s a lot of buzz about machine learning in government today, given its potential to improve operations, cut costs and produce better program outcomes. But what exactly is it?
There’s a lot of buzz about machine learning in government today, given its potential to improve operations, cut costs and produce better program outcomes. But what exactly is it?
Federal government agencies are faced with an immense amount of data, with more pouring in every second. With so much information, keeping track of it all can be extremely challenging, particularly when there are bad actors seeking to take advantage of the data overflow. AI and machine learning can help.
The terms ‘automation, ‘artificial intelligence,’ and ‘machine learning’ are hot topics in a lot of government technology conversations. These terms are often used interchangeably and sometimes incorrectly, which can be confusing. Let’s take a look at what this tech jargon means.
Data by itself doesn’t solve problems or bring value to an organization. We need to move beyond the data, and work on harnessing its value to the organization.
While AI provides significant advantages, it can be challenging to adopt without the right computing and development resources to enable it. Many government agencies, however, still struggle with legacy and outdated IT infrastructures. That’s why a trusted and robust cloud infrastructure is a critical component of the DoD’s journey to AI and machine learning.
The Federal Data Strategy will help the U.S. government’s workforce better manage vast amounts of information.
Algorithms play an important part of our every day lives and will continue to grow and expand. Here’s what algorithms and the future of government could look like.
You want to hear a secret? City governments are still at the beginning stages of understanding how best to optimize the use of machine learning (ML) algorithms to make city services more efficient. Here’s why.
The advent of spatial technology has automated spatial problem solving. As a result, we are seeing a rebirth in the age of discovery.
Agency leaders and program management professionals must seek practical, secure, and effective methods to extract the valuable information captured in their data repositories — from legacy systems to real-time data streams.