In our new episode of Machine Learning, Artificial Intelligence, and Data Science in the Knowledge-Driven Enterprise, we discuss business drivers, future vision, technologies, and the framework supporting proactive user experiences in information technology.
Mentoring the Workforce of the Future and Reverse-Mentoring the Workforce of the Present, with Steffani Silva
In this installment of the MITRE Knowledge Driven Podcast, Data Analytics Engineer Steffani Silva, gives us an inside look at the inner workings of Generation AI Nexus, a collaboration among MITRE, universities, and government that educates students, as well as professors, on the power of artificial intelligence and accessible data.
Have you ever wondered how Google Maps works? How does the application calculate the fastest route for you, and how does it do this so quickly? The answer might surprise you – at the backbone of these navigational applications and software is graph theory.
According to the independent website Government Technology, “Many government agencies have an unstructured data nightmare, with bits and bytes scattered across servers, clouds and hypervisors.” Vernor Vinge calls this so-called nightmare “data glut.” In an era of Internet of Things (IoT), the data glut may not get better, and, in fact, is likely to get worse.
Considered the first Internet of Things (IoT) device, the toaster John Romkey created could be turned on and off over the Internet during the October ’89 INTEROP conference! Since then, more people have begun to use IoT devices. Simply put, IoT connects devices with the Internet, from things as simple as smart light bulbs and coffee makers to things as complicated as robots and drones.
As data science has exploded in popularity and use, so have the tools used to solve problems in the domain. Some of these open source programs and programming suites have become extremely popular, and thus developers have designed a whole host of code that might be referred to as add-ons, extensions, and packages to improve functionality and save time for users, both experienced and new.
A computer scientist looks at a refugee crisis to model a pandemic.
How does that connection work exactly and why? If it appears to resemble a scenario in which a farmer learns how to plant an apple orchard by examining the supply chain for manufacturing orange juice, well, you may actually be onto something. The novel coronavirus has presented unprecedented medical, social, and economic challenges, which means that the thoughtful people responding have no choice but to innovate. However, in 2020, innovation doesn’t mean going where no one has gone before. It means harvesting everything that has come before in a disciplined way to see what might bear fruit.
“Science,” “collaboration,” and “serving the best interests of the wider community” are cherished values at MITRE, as is the concept of continuous learning. At MITRE, citizen science is thus a volunteer and civic activity, a hobby, a tool for research, a source of learning, a professional and social networking opportunity, and a means of giving back to the scientific community.
In November 2019, a customer of Apple Card complained when he and his wife separately applied for Apple Card credit, and his wife was given a credit limit twenty times lower than his despite the fact that they jointly owned all assets in a community property state. According to Neil Vigdor in an article in the New York Times, an Apple Card representative checked into the matter and came back with the explanation that “It was the algorithm.”
MITRE has taken on a challenge: to shape America’s future workforce and economy by alerting college students to the power of artificial intelligence (AI). That vision is now taking shape at schools across the country through an initiative known as Generation AI Nexus (Gen AI).
A woman who has always identified as Ashkenazi Jewish received a DNA testing kit from one of the ancestry services and participates on a whim. Surprise! Turns out her father was actually a non-Jewish sperm donor. It’s one of many fascinating and recent cases of renegotiating identity, along with stories about an adopted child finding their true birth family, or even individuals tracing their ancestry back to someone practicing witchcraft.
Ali Zaidi is a MITRE data scientist tackling an interesting challenge for MITRE as part of his work for Generation AI Nexus. As the fields of machine learning and data science have grown, the need for machine learning education has become a necessity of many fields few would associate with computer science.
Jesse Buonanno, a Cyber Security Engineer at MITRE, focuses on cyber operations. Jesse spends his spare time learning about blockchain and cryptocurrencies.
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.
Clinical diagnostic support. Loan approval. Predictive policing and parole. These are all examples of consequential systems, meaning that they are systems with immediate, long-term, impactful consequences on people within them.
Artificial intelligence (AI) is getting better all the time. You can see it all around you, from Alexa and Siri keeping your appointments and shopping lists, to news articles about self-driving cars, to a program called AlphaZero (Silver et al., 2018) that will probably never lose to any human in chess or GO.
The process of neural interactions and visual interpretation happens every time your brain wants to identify literally anything you look at.
Chances are, you’ve interacted with an embedded system today. Did you use a thermostat? How about a car? Or maybe a mobile phone? Or a television, a game console, an elevator, a train, a pacemaker?…
Blockchain has essentially created a new type of internet in which information can be widely distributed without relying on traditional centralized architectures…