The Sensors Division focuses on advanced sensor system technology, from airborne and surface-based radar and electronic warfare to underwater acoustics, EO/IR and hyperspectral imaging. This position is with the Electronic Warfare and Novel Capabilities Group in the STR Sensors Division. We focus on technology development for advanced sensor systems, in the areas of airborne/surface-based radar, electronic warfare, data communications, and hyperspectral imaging. We develop algorithmic and hardware components, conduct experiment campaigns, and prototype systems. Design, build, and test roles within the Group include RF analog/digital hardware, advanced electronic warfare algorithms and techniques, signal processing and machine learning algorithms, cognitive electronic warfare applications, tracking/fusion, and real-time embedded processor implementation.

This program uses artificial intelligence and data science to help develop … A lot of the machine learning algorithms that we use today were …

That says that anything you can do as a human being we can augment the intelligence positions through machine learning and machine processes."

Discover how John Deere's New Autonomous 8R Tractor uses machine learning and artificial intelligence to help farmers make key decisions and …

Deep Learning Toolbox provides a framework for designing and implementing deep neural networks with algorithms, pretrained models, and apps. You can use convolutional neural networks (ConvNets, CNNs) and long short-term memory (LSTM) networks to perform classification and regression on image, time-series, and text data. You can build network architectures such as generative adversarial networks (GANs) and Siamese networks using automatic differentiation, custom training loops, and shared weights. With the Deep Network Designer app, you can design, analyze, and train networks graphically. The Experiment Manager app helps you manage multiple deep learning experiments, keep track of training parameters, analyze results, and compare code from different experiments.

Are you a data scientist or machine learning engineer interested in learning more about how to analyze and improve the performance and trustworthiness of your machine learning models? Then this live online course is for you! AI Quality: Driving ML Performance and Trustworthiness is a free course taught live by five experts from leading universities, including a professor from Carnegie Mellon University and Stanford University. This offer is exclusively for corporate and government practitioners. All students completing the course receive a certificate, limited edition shirt, and access to the Slack community.

In financial services, it is important to gain any competitive advantage. Your competition has access to most of the same data as you, since historical data is available to everyone in your industry. Your advantage comes with the ability to mine that data better, faster, and more accurately than your competitors. With a rapidly fluctuating market, the ability to process data faster gives you the opportunity to respond faster than ever. This is where AI-first intelligence can help you.

Everyone loves Artificial Intelligence (AI) and data science (DS), and it's probably not going to change for the next decade or so. Still, most people only have a general idea of what data science is and what machine learning algorithms or AI can do. This is quite normal and a common phenomenon for all fields of expertise. Think about it: do you really know what DevOps, Support or NOC (Network Operation Center) actually do? Sure, as tech professionals we can probably explain it better than people who aren't part of the industry, but in most cases it's pretty hard to really understand what other people are doing if you've never done it yourself.

Microsoft just showed how artificial intelligence could find its way into many software applications--by writing code on the fly. At the Microsoft Build developer conference today, the company's chief technology officer, Kevin Scott, demonstrated an AI helper for the game Minecraft. The non-player character within the game is powered by the same machine learning technology Microsoft has been testing for auto-generating software code. The feat hints at how recent advances in AI could change personal computing in years to come by replacing interfaces that you tap, type, and click to navigate into interfaces that you simply have a conversation with. The Minecraft agent responds appropriately to typed commands by converting them into working code behind the scenes using the software API for the game.

Artificial intelligence in healthcare has come a long way. The use of computers has advanced significantly over the past few years. Today, sophisticated machines have been developed to perform human tasks like analyzing and interpreting data and assisting with problem-solving. While machine learning (ML) has been widely used in many industries, the use and application of Artificial Intelligence (AI) in healthcare is still relatively new. It is only recently that we have seen AI move from the world of academics and research laboratories to hospitals.