This week, astronauts on the International Space Station got a new helper that goes by the nickname'Simon.' More formally known as Crew Interactive Mobile Companion 2 (CIMON 2), Simon was developed in a joint project by IBM's Watson team, Airbus, and the German Aerospace Center. The Crew Interactive Mobile Companion 2 (CIMON 2, pronounced'Simon,' pictured above) will help astronauts conduct experiments and talk through their feelings The robotic helper was delivered to the ISS on SpaceX's Dragon capsule launched from Cape Canaveral this week. Last year, an earlier model of CIMON was sent to the ISS, but the new version has been updated with AI enhancements that IBM says will make it more'emotionally intelligent.' 'The overall goal is to really create a true companion,' IBM's Matthias Biniok told ABC. 'The relationship between an astronaut and CIMON is really important.'

But while there continues to be much debate over the impact of AI technology on headcount, the more pressing question for HR and workforce managers is how intelligent software can be deployed to augment work today. HR Tech News has selected the year's most ground-breaking stories of AI in the workplace. Recruitment tech specialist HireVue, however, takes candidate screening to the next level by combining facial analysis with AI. The software behind the platform purportedly relies on 25,000 data points taken from the facial expressions, movements and tone of voice of past successful candidates then uses them as a benchmark for screening new applicants. These subtle clues from their interaction with the AI reportedly help determine their suitability to the role. Amid efforts to build a more diverse workforce, organizations still struggle against the influence of unconscious bias in hiring.

Our technical report provides an overview of the relevant parts of an ML lifecycle--selecting the right problem, the right data, and the right math and summarizing the model output for consumption--as well as questions that relate to those areas of focus. As the federally funded research and development center (FFRDC) known for AI engineering, and with its long experience in cybersecurity, the SEI has the expertise to advise you--the decision makers adopting these tools--on evaluating the adequacy of ML tools applied to cybersecurity. To that end, we structured the report around the questions you should ask about ML tools. We chose this framing, rather than proposing a detailed guide of how to build an ML system in cybersecurity, because we want to enable you to learn what a good tool looks like. When decision makers have difficulty identifying a good tool, the market will usually stop providing them.

AWS, Azure, Google Cloud, IBM Cloud, Oracle – they'll all vying to become the dominant force of gravity in the public cloud services market, and among the most fiercely fought over areas of cloud leadership is AI/machine learning enablement. Given that AI's TAM is roughly * and that the FAANGs are out ahead of everyone on AI expertise, it makes sense they would commercialize the technologies they use and that they've developed to attract enterprise AI customers to their platforms. A centerpiece of AWS's AI market strategy is SageMaker, a managed service that provides developers and data scientists who aren't necessarily ML experts with the tools to build, train and deploy ML models. Launched two years ago, AWS has designed SageMaker to lighten the heavy lifting from each step of the machine learning process. Since its inception, the product suite has been expanded into SageMaker Studio, which AWS CEO Andy Jassy, at the annual re:Invent conference in Las Vegas this week, described as an integrated, web-based IDE (interactive development environment) for machine learning that lets developers collect and store code, notebooks, data sets, settings and project folders in a single setting.

This epic list article has been updated to include 20 more digital marketing trends to help you get ready for next year! At one time, artificial intelligence, data-driven marketing and voice search engine optimization (VSEO) were ambitious concepts bordering on the ridiculous. Today, these innovative digital marketing trends are among the top priorities for most business owners in 2020. And why wouldn't they be? After all, if your business has any intention of remaining competitive in today's online landscape, you must adapt to the rapidly evolving changes in digital marketing. "Each business is a victim of Digital Darwinism, the evolution of consumer behavior when society and technology evolve faster than the ability to exploit it. Digital Darwinism does not discriminate. Make no mistake: We live in a time when marketing technology moves fast and consumer interests and behaviors are hard to predict. Marketers can no longer stick their heads in the sand and hope that educated guesses ...

The Age of Autonomy is upon us. Truly autonomous devices are quickly replacing those that are merely automated. This is a natural evolution of IoT due to autonomy becoming a necessity to handle the volume, velocity and veracity of real-time data being generated. The centralized solution architectures and services in our enterprise data centers today are not viable for the industry use cases that the Age of Autonomy brings so fundamental changes must be made. In this technical panel hosted by Kristof Kloeckner, experts in autonomy from IBM, The International Center of Automotive Research (ICAR), Vapor, Here, and W8Less will be discussing how the combination of Edge Computing, 5G and Micro-Positioning are quickly making the Age of Autonomy a reality.

Editor's note: To make Gartner's top technology trends more digestible, CIO Dive broke them into two parts. This is the second of two parts. You can read the first, which focuses on technology interacting with people, here. When "Minority Report" was released in 2002, it felt futuristic. Psychic technology would predict a crime before it was committed and Tom Cruise would go make the arrest.

Microsoft is pitching blockchain technology as a way to make artificial intelligence less scary for its corporate customers. Much like consumers who are wary of AI, enterprises are queasy about putting their full trust in a "black box" where machine learning algorithms are indiscriminately applied to vast data sets. But Microsoft, which helps thousands of firms manage their data, claims a blockchain can add trust and a degree of transparency, assuaging such concerns. Underpinning this is a new tool called Azure Blockchain Data Manager, which the software giant released at its annual Ignite conference in Orlando, Florida, but was overshadowed by the announcement of a platform for creating enterprise tokens. Blockchain Data Manager takes on-chain data and connects it to other applications.

Understanding the Quality of Experience (QoE) for visual media has been very important for optimal compression and content delivery for diverse video formats, and it has been a hot topic of research for the last decades. Researchers mostly studied this problem from a signal processing perspective using image and video processing tools, while learning-based methods have been increasing momentum recently. The popularisation of deep learning-based methods affected the whole signal and image processing community as a disruptive force, and visual QoE estimation is no different than others. Use of learning-based methods and especially deep learning methods open a new path for understanding the human visual system in the perception process and other QoE parameters. The objectives of this special session are twofold: first, to develop new metrics reaching beyond the performance of the legacy signal processing approaches for visual QoE estimation, and second, to understand the stages of human perception for visual media better utilising the learning-based methods and different analysis methods such as ablation studies.

Imagine your life being constantly disrupted by monkeys. Every day, growing in confidence and numbers, they come into your home or place of work, looking for food, creating a mess and sometimes becoming aggressive. For many people in India, this is an all too familiar occurrence. So, what would you do? One researcher, through a Microsoft AI for Earth grant, is using artificial intelligence (AI), cloud computing and her passion for the animal kingdom to help solve the problem.