HPC has long been the foundation for accelerating enterprise innovation, driving economic competitiveness, and bringing products and services to market faster. The convergence of HPC with AI takes the power of HPC even further, helping enterprises address some of their most complex challenges. We are supporting this convergence with an unmatched end-to-end portfolio of technologies and products – all supported by a broad software ecosystem – to help enable solutions to address your company's unique challenges. We hope you will join us at Supercomputing 2019 to learn more about the ways HPC AI can advance your organization! Please visit the Intel SC19 website for more information, and be sure to download the Intel SC19 mobile agenda to keep up to date on speakers, keynotes, celebrations, and more.

"It's something that's a growing concern in the machine learning and AI community, especially because these algorithms are being used more and more," says Daniel Lowd, assistant professor of computer and information science at the University of Oregon. "If spam gets through or a few emails get blocked, it's not the end of the word. On the other hand, if you're relying on the vision system in a self-driving car to know where to go and not crash into anything, then the stakes are much higher." Whether or not a smart machine malfunctions, or is hacked, hinges on the very different way that machine learning algorithms'see' the world. In this way, to a machine, a panda could look like a gibbon, or a school bus could read as an ostrich.

Patients' wellbeing should be the central focus of healthcare. Studies show that doctors spend almost half their time on data entry and more than half of their workdays managing records instead of caring for patients. Add this lost time to the fact that healthcare in the United States is already understaffed – averaging 2.5 healthcare practitioners to every 1,000 patients – and it's easy to see that something's got to give to bring focus back to what really matters: actual patient care. Automation technologies, such as Robotic Process Automation (RPA), offer a chance to relieve overburdened healthcare practitioners of the time-intensive administrative work detracting from time spent with patients. RPA software allows users to configure "bots" to take on repetitive tasks by emulating and integrating the actions of a human within digital systems to perform a business process, eliminating often repetitive tasks from a person's workload.

Organizations are looking to AI to improve processes, reduce costs and achieve better results. However, AI workloads pose a different set of challenges than business workloads supported by corporate IT. If businesses don't pay attention to the unique requirements of AI infrastructure, they can be faced with increased deployment time, higher costs and delayed insights. NetApp and NVIDIA are helping organizations avoid these pitfalls with a new suite of solutions that make accessing and acquiring AI-ready infrastructure easier than ever – the ONTAP AI-Ready Data Center. Significant portions of AI budgets are allocated to solving two problems: designing a well-functioning system and outfitting a data center to house it. Because of this, investment in AI infrastructure can be daunting.

Marketers and businesses are increasingly using AI to automate functional processes as well as customer interactions. AI has been shown to help brands understand their audience better, reach them at the right times, improve the accuracy of marketing campaigns, and enrich user experience, ultimately leading to cost savings and better ROI. The question marketers are failing to ask, however, is "Are consumers satisfied with the buying experience?" The paradox of today's data-driven, AI-driven marketing is that despite a large number of channels that provide information and customer service (Hello, chatbots!), consumers are craving more human experiences. In a report titled Are You Listening?

Our mission at Reply.ai is to remove frustration and save people's time when interacting with a business. One of the ways that we can impact customer experience is by making customer support agents happier and more efficient. We would love to share with the ML community how we used Deep Learning to make a real-time Assistant to increase the efficiency of Customer Service teams. Support agents do a lot of repetitive work when answering tickets and chats in customer service platforms like Zendesk, Kustomer and Khoros. Instead of writing unique, personalized responses, they have to classify tickets, add specific tags, route tickets to other teams, and select templates, among other responsibilities.

Kevin Ross is the chief executive of Precision Driven Health, a research partnership that is applying machine learning models to health data in order to improve outcomes and personalise medicine. Kevin will be speaking at this year's Orion Health UK and Ireland Customer Conference 2019, and ahead of the event he spoke about its work, the tools that are now being made available to Orion Health customers, and why he is looking for like-minded organisations to "tune" models for their own populations. What is Precision Driven Health? Precision Driven Health is a research partnership that applies machine learning to data sets in order to improve health outcomes by delivering a more personalised experience for patients. It was formed when Orion Health, the University of Auckland and Waitematā District Health Board recognised that we all had capabilities that we could bring together.

Technology spending in the banking and securities sector in Australia is expected to reach A$18.5 billion in 2020, an increase of 5.2% from 2019, according to Gartner, Inc. Behind this growth are new investments in modern business intelligence (BI), augmented analytics and robotic process automation (RPA) software. Globally, the banking and securities industry spends the most on information technology products and services. In Australia, it is the second-largest-spending industry after communications, media and services, representing 19.2% of total enterprise IT spending. "The banking and securities industry continues to spend in pursuit of digitalization, whether through digital business optimization or transformation," said Neha Gupta, research director at Gartner. "The introduction of open banking in Australia is also driving new technology investments."

Facial recognition systems are all the rage among government agencies around the world, as they seek to automate services and keep tabs on their citizens. If there's a picture of you somewhere, you could potentially be identified in photos and videos from public camera feeds. Now, Facebook has devised a way to thwart this technology. Its face de-identification tech, developed by three AI researchers who work with the company, modifies your face slightly in video content, so that facial recognition systems can't match what they see in the footage with images of you in their databases. You can see this in action in this video (screenshot above), in which certain details are tweaked, such as the shape of a person's mouth, or the size of their eyes.

The pace of change in underwater warfare has become palpable. There are signs that the long-promised dawn of underwater robots is upon us. Barely a month after China revealed its first large underwater robot, another country has stepped into the arena with an even more ambitious project: a submarine-hunting unmanned underwater vehicle (UUV). That county may not be the one you are expecting. The South Korean Navy's Anti-Submarine Warfare Unmanned Underwater Vehicle (ASWUUV) appears larger ... [ ] than U.S. Navy and Chinese Navy large displacement UUVs.