Amazon's household robot is exactly what I expected, but it's not what I wanted and it definitely isn't what anyone asked for. Instead of a multitasking mimicry of me that can empty the dishwasher, pick up my kids' shoes, feed the dog, and clean the house, Amazon's first attempt at a home bot is simply a souped-up Echo Show on wheels. It also has two cameras that it uses to find people and places in your home to deliver items, reminders, or timers. It can act as a security guard and patrol your home when paired with a Ring subscription, and it can fart and burp. In short, the Astro does everything Amazon's smart home products and services already do -- only on wheels. But the Astro is a robot. And that part is really cool.
Today, cybersecurity is in a state of continuous growth and improvement. In this on-demand webinar, learn how two organizations use a continuous AI feedback loop to identify vulnerabilities, harden defenses and improve the outcomes of their cybersecurity programs. The security risk landscape is in tremendous flux, and the traditional on-premises approach to cybersecurity is no longer enough. Remote work has become the norm, and outside the office walls, employees are letting down their personal security defenses. Cyber risks introduced by the supply chain via third parties are still a major vulnerability, so organizations need to think about not only their defenses but those of their suppliers to protect their priority assets and information from infiltration and exploitation.
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.
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.