So you’ve heard about Symphony™ – MITRE’s automated provisioning framework that rapidly builds secure analytic cells for geospatial, AI, and machine learning applications. Have you tried explaining it to a college student?
Welcome to the second installment of the Knowledge-Driven Podcast. In this series, Software Systems Engineer Cameron Boozarjomehri interviews technical leaders at MITRE who have made knowledge sharing and collaboration an integral part of their practice.
Welcome to the first installment of the Knowledge-Driven Podcast. In this new series, Software Systems Engineer Cameron Boozarjomehri interviews technical leaders at MITRE who have made knowledge sharing and collaboration an integral part of their practice.
Science is “the systematic study of the structure and behavior of the physical and natural world through observation and experimentation.” Since its emergence during the late renaissance, scientific progress has been made primarily through the aptly named scientific method.
How do we prepare for the inevitable change in the world today? How do we take into account not just the way the world is now – but the way it looks in the future?
Somewhere on a whiteboard in a classroom at the Universities of Shady Grove, swims a fish. Drawn in black marker, complete with a fedora, sunglasses, and a goatee, the sketchy-looking ichthyoid intones into a word bubble…
Is artificial intelligence (AI) the way of the future… or already the way of the present?
Applications of AI surround us in our daily lives – ever use an app to get around traffic? How about checking your social media feeds? As our society integrates AI into our daily lives, it’s important to note that the upcoming generation has always lived with AI.
The process of neural interactions and visual interpretation happens every time your brain wants to identify literally anything you look at.
The Emerging Technologies program is now a major undertaking for MITRE. It draws upon contributions from staff at all levels of the company, including many who were not mentors or student investigators.
Imagine waiting 30 minutes or longer to get through to a customer service center and when your call is finally answered, you can’t understand what the service representative is saying because you have a hearing impairment. Or you place a call to your doctor but aren’t able to communicate your needs to the medical staff because your speech is impaired. Or you are a child with autism and being in a classroom and interacting with your teacher and classmates overwhelms you with anxiety.
MITRE believes that data is the next medical innovation in health. How might connecting people and data reinvent the health experience? To find out, a team of researchers developed Home Assessments for Prompt Intervention (HAPI), a serious game that uses Microsoft Kinect-based joint tracking to detect critical changes in patients with cerebral palsy…
Applications in Data Science: Anti-Fragility in Action…
Data Science Practitioners…
There’s thinking about, talking about, and doing, and they all have a time and place in any domain. With data science, though, doers rule. A big bucket of ostensibly random stuff in the hands of a skilled practitioner becomes the stuff of art. Yup, even data about a fire hydrant.—Editor
In her previous post, Technical Challenges in Data Science, Amanda Andrei discussed the need for technical vigilance and with experts Dr. Elizabeth Hohman, statistician and group leader within MITRE’s Department of Data Analytics, and Dr. Eric Bloedorn, senior principal artificial intelligence engineer. Tools and models, however carefully managed, tell, of course, only part of the story. Data scientists are people, and they and the tools they use reside within organizational cultures, which may require as much training as the data to hand.—Editor
As Amanda Andrei mentioned in her previous post, Defining, Applying, and Coordinating Data Science at MITRE, we are generating 2.5 million terabytes of data a day, and the need for data science teams and individual contributors is crucial for moving what we find up the spectrum to knowledge that we might usefully….
For a long time I have thought I was a statistician, interested in inferences from the particular to the general, wrote mathematician….
I believe that knowledge management as a discipline developed because technology enabled the deluge of data we began experiencing about 20 years ago. The ways that we used to organize and share our information were no longer adequate to the task and we needed something new. I’ve spent the last five or six years focusing on data, more specifically on helping organizations treat their data as a strategic asset that requires the same stewardship afforded any other valuable resource within the organization.