While most people are familiar with 3D printing as something your engineer neighbor messes around with in their basement to produce small models, the applications of the technology can be much more significant than a hobbyist's weekend activity. The technology is being used in some mission critical and massive scale projects across government.
An early, small-scale application of 3D printing in the construction industry was recreating historical fixtures for renovations. Historical buildings, many of which house government agencies and government-run museums, have light fixtures, molding, door knobs, etc. that may need replacing. Finding actual replacements for centuries old materials is incredibly difficult and building them from traditional materials is time consuming and costly. 3D printing has proven to be a valuable solution to maintaining the historical look quickly and at a much reduced cost.Continue reading →
Agility has been a key attribute for success over the past year and a half. Everyone had to quickly adapt in their personal and professional lives to do things in new ways to keep business and society running. Even the great bureaucracy of government found itself pivoting and quickly changing "how it's always been done" to meet the needs of the day. This should not end with the return to what feels like pre-pandemic normal. In the form of Agile methodology, Agility will play a huge role in the government's ability to continue the fast-forwarded digital push as a result of the pandemic.
Just as government pushed agencies to try Cloud with the "Cloud First" initiative, some are suggesting the same approach for Agile. An "Agile-First" evolution would have a huge impact on IT modernization efforts, accelerating the move from legacy processes and technology to a modern digital approach. The response to COVID-19 showed that the government can move quickly in changing how they do work (across all areas of government). An Agile-first "mandate" could institutionalize that speed and make it the rule rather than the exception.
With so many high-profile hacks this year, it's easy to want to throw up your hands and say, "Is there nothing that can be trusted?!" Interestingly, that lament is what is driving the latest approach to cybersecurity -- zero trust. Zero trust is what it sounds like, a security approach centered on the belief that organizations should not automatically trust anything accessing their systems either inside or outside their perimeters. Instead, all people and devices must be verified before access is granted. To the untrained eye, this seems untenable. How, in this day and age, when we depend on digital information and connection to do most anything, can we use a process where we have to constantly verify identity and access permissions? Luckily, the practice of zero trust is more sophisticated than its premise.
FirstNet is a nationwide wireless broadband network for first responders being built and deployed through a first of its kind public-private partnership. FirstNet was borne out of the September 11, 2001 tragedy where it became clear that the radio systems police, fire, and paramedics relied on did not easily operate across agencies. First responders also could not rely on land and mobile phone lines as they were overwhelmed by a high volume of calls. The 2004 9/11 commission report cited this lack of connectivity as a fundamental problem for first responders and pushed for solutions to be developed quickly to support everyday public safety activities as well as response to catastrophes.
The development of FirstNet began in 2012 when the First Responder Network Authority was established and a law was put in place that allocated 20 megahertz of spectrum and $7 billion to establish a broadband network dedicated to the nation's first responders. FirstNet was launched in 2018.
Natural Language Processing (NLP) is a computer science practice that aims to give computers the ability to understand text and spoken words in the same way humans can. NLP is a key feature of Artificial Intelligence (AI) as understanding the language that we use to "teach" computers is critical to evolving the accuracy of the AI tasks we are asking of them.
The most familiar application of NLP is speech recognition--taking the spoken word and converting it to text. Speech recognition also is part of any application that follows voice commands.To work properly, the technology has to be knowledgeable of accents and frequently understand context (semantics) to differentiate words with a similar sound but have various meanings or spellings. NLP is also closely tied to several tasks that work in the background of applications we use everyday, including spam detection, foreign language translation, virtual assistants, chatbots, social media sentiment analysis, and text summaries/abstracts for long documents.