A robot with true artificial intelligence is about to invade space. The large, round, plastic robot head is part of SpaceX's latest supply delivery to the International Space Station. Friday's pre-dawn liftoff also includes two sets of genetically identical female mice, 20 mousestronauts that will pick up where NASA's identical twin brother astronauts left off a few years ago. Super-caffeinated coffee is also flying up for the space station's java-craving crew. As intriguing as identical space siblings and turbo-charged space coffee may be, it's the German robot -- named Cimon, pronounced Simon, after a genius doctor in science fiction's "Captain Future" -- that's stealing the show.

A robot with true artificial intelligence is about to invade space. The large, round, plastic robot head is part of SpaceX's latest supply delivery to the International Space Station. Friday's pre-dawn liftoff also includes two sets of genetically identical female mice, 20 mousestronauts that will pick up where NASA's identical twin brother astronauts left off a few years ago. Super-caffeinated coffee is also flying up for the space station's java-craving crew. As intriguing as identical space siblings and turbo-charged space coffee may be, it's the German robot--named Cimon, pronounced Simon, after a genius doctor in science fiction's "Captain Future"--that's stealing the show.

The next shipment headed to the International Space Station packs nearly three tons of research and resupply materials. You know, the typical stuff: sediment studies, a plant thermometer, a replacement hand for the giant robotic Canadarm. Oh, and also a floating robot designed as a helpmeet for astronauts--scientifically, logistically, and emotionally. The bot's full name is Crew Interactive Mobile Companion: Cimon. It looks like one of those spherical pool speakers, if you replaced the speaker with a screen that displays a line-sketch face that talks back.

Digital transformation is the profound transformation of business and organizational activities, processes, competencies and models to fully leverage the changes and opportunities of a mix of digital technologies and their accelerating impact across society in a strategic and prioritized way, with present and future shifts in mind. While digital transformation is predominantly used in a business context, it also impacts other organizations such as governments, public sector agencies and organizations which are involved in tackling societal challenges such as pollution and aging populations by leveraging one or more of these existing and emerging technologies. In some countries, such as Japan, digital transformation even aims to impact all aspects of life with the country's Society 5.0 initiative, which goes far beyond the limited Industry 4.0 vision in other countries. In the scope of this digital transformation overview, we mainly look at the business dimension.

A robot with true artificial intelligence is about to invade space. The large, round, plastic robot head is part of SpaceX's latest supply delivery to the International Space Station. Friday's pre-dawn liftoff also includes two sets of genetically identical female mice, 20 mousestronauts that will pick up where NASA's identical twin brother astronauts left off a few years ago. Super-caffeinated coffee is also flying up for the space station's java-craving crew. As intriguing as identical space siblings and turbo-charged space coffee may be, it's the German robot -- named Cimon, pronounced Simon, after a genius doctor in science fiction's "Captain Future" -- that's stealing the show.

This paper presents a Bayesian nonparametric latent feature model specially suitable for exploratory analysis of high-dimensional count data. We perform a non-negative doubly sparse matrix factorization that has two main advantages: not only we are able to better approximate the row input distributions, but the inferred topics are also easier to interpret. By combining the three-parameter and restricted Indian buffet processes into a single prior, we increase the model flexibility, allowing for a full spectrum of sparse solutions in the latent space. We demonstrate the usefulness of our approach in the analysis of countries' economic structure. Compared to other approaches, empirical results show our model's ability to give easy-to-interpret information and better capture the underlying sparsity structure of data.

Bayesian methods in machine learning, such as Gaussian processes, have great advantages compared to other techniques. In particular, they provide estimates of the uncertainty associated with a prediction. Extending the Bayesian approach to deep architectures has remained a major challenge. Recent results connected deep feedforward neural networks with Gaussian processes, allowing training without backpropagation. This connection enables us to leverage a quantum algorithm designed for Gaussian processes and develop new algorithms for Bayesian deep learning on quantum computers. The properties of the kernel matrix in the Gaussian process ensure the efficient execution of the core component of the protocol, quantum matrix inversion, providing a polynomial speedup with respect to classical algorithm. Furthermore, we demonstrate the execution of the algorithm on contemporary quantum computers and analyze its robustness to realistic noise models.

"For agencies that are looking to leverage predictive analytics and machine learning, you have to be willing to share information, and you will get better results over time," Julius Chang, program director of the System and Support Division at GrantSolutions.gov, said at a June 27 Government Executive event. "At GrantSolutions, we are doing a pilot on machine learning and data analytics that can yield predictive analytics capabilities that will improve the workflow and results through our systems." Machine learning can be used to determine which applications are likely to be accepted or rejected, Chang said. With a machine learning program that reviews applications when they come in, grants officers could spend more time on "good applications," and the "likely rejected applications" could be handled by a lower level specialist. The machine learning system can predict with 96 percent accuracy whether applications will be rejected because they are poorly written, Chang said.

In the wake of Alexandra Ocasio-Cortez's primary win, Oakland Democrat Barbara Lee is considering a bid to replace House Minority Leader Nancy Pelosi, who is 78. Joseph Crowley, was previously considered a frontrunner for the position. Lee is popular among progressives for her consistent voting record.

While security as a percentage of IT spend continues to grow at a robust rate, the cost of security breaches is growing even faster. Organizations are spending close to $100 billion on a dizzying array of security products. In fact, it is not uncommon for CISO organizations to have 30 to 40 security products in their environment. However, if you ask chief information security officers how they feel about their security risk, they will express concerns over being highly exposed and vulnerable. Artificial intelligence (AI) and machine learning (ML) can offer IT security professionals a way to enforce good cybersecurity practices and shrink the attack surface instead of constantly chasing after malicious activity.