The innovations that follow the robotics advancements are worth watching. The pace at which robots are evolving is unprecedented. As some still fear the non-empathetic consequences of a machine, researchers are working their best to add human-touch to robots. In this regard, scientists are moving robots along on that continuum by developing robotic skin. This will help machines gain the sense of touch. Researchers from Munich to Japan to Boston are currently looking into how to give robots tactile sensation and in some cases, feel pain.

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. Deadly hornets from Asia that measure up to 2 inches long and can wipe out entire honey bee colonies within hours have been spotted for the first time in the U.S. These so-called "murder hornets" represent a threat to the honeybee population. The hornets-which have been blamed for 50 deaths a year in Japan--have been spotted in Washington, and according to the New York Times, can rip through a hive, killing a bee every 14 seconds.

To use spark, we can either run it on an AWS EMR cluster, or if you just want to try it out and play with it, you can also run it on your local Jupiter notebook. There have been many great articles on how to set up your notebook on AWS EMR to use PySpark such as this one. EMR cluster configuration will also largely affect your runtime, which I will mention in the last part. For preprocessing the data, I will be using the Spark RDD manipulation to perform exploratory data analysis and visualization. The rest of the Spark preprocessing code and Plotly visualization code can be found on the Github repo, but here are the graphs out of our initial exploratory analysis.

However, according to a study by Appian last year, 91 percent of respondents believe they need to fix problems rather quickly than thoroughly, as they need to focus on updating their business operations. The speed of updates and customizations using DevOps measure is measured in days rather than months or years. Frequently, IT operations cannot keep up with this pace, and digitization will fail in the long term. The solution to many of the associated DevOps challenges lies in a different kind of digital transformation - based on machine learning and artificial intelligence (AI). Although it is often portrayed as a threat to the public, it offers companies an excellent opportunity to improve their productivity and security.

The global healthcare industry is booming. As per recent research, it is expected to cross the $2 trillion mark this year, despite the sluggish economic outlook and global trade tensions. Human beings, in general, are living longer and healthier lives. There is increased awareness about living organ donation. Robots are being used for gallbladder removals, hip replacements, and kidney transplants.

Using Artificial Intelligence (AI), researchers have developed a quick test to identify which people with glaucoma are at risk of rapid progression to blindness. A new test can detect glaucoma progression 18 months earlier than the current gold standard method, said the study published in the journal Expert Review of Molecular Diagnostics. Glaucoma, the leading global cause of irreversible blindness, affects over 60 million people, which is predicted to double by 2040 as the global population ages. Loss of sight in glaucoma is caused by the death of cells in the retina, at the back of the eye. "Being able to diagnose glaucoma at an earlier stage, and predict its course of progression, could help people to maintain their sight, as treatment is most successful if provided at an early stage of the disease," said study first author Eduardo Normando from Imperial College London.

The cybersecurity skills shortage continues to plague organizations across regions, markets and sectors, and the government sector is no exception. According to (ISC)2, there are only enough cybersecurity pros to fill about 60% of the jobs that are currently open -- which means the workforce will need to grow by roughly 145% to just meet the current global demand. The Government Accountability Office states that the federal government needs a qualified, well-trained cybersecurity workforce to protect vital IT systems, and one senior cybersecurity official at the Department of Homeland Security has described the talent gap as a national security issue. The scarcity of such workers is one reason why securing federal systems is on GAO's High Risk list. Given this situation, chief information security officers who are looking for ways to make their existing resources more effective can make great use of automation and artificial intelligence to supplement and enhance their workforce.

We are seeing AI technologies increasingly deployed across many parts of society. Around the globe, governments are rushing to mobilize vast amounts of capital to invest into AI innovation. The COVID-19 pandemic prompts us to rethink what is considered high- or low-skill work. Whose skills, whose labor and whose hours, exactly, are of value to society? What and who do we value and deem essential, and how do we compensate these workers (e.g., care work or teaching)?

In February, after more than a year consulting with a range of experts, the Department of Defense (DoD) released five principles for ethics around artificial intelligence (AI). If AI doesn't meet these standards, the Department has said, it won't be fielded. "The United States, together with our allies and partners, must accelerate the adoption of AI and lead in its national security applications to maintain our strategic position, prevail on future battlefields, and safeguard the rules-based international order," Secretary Mark Esper said in the news release. The principles, which apply to combat and non-combat functions, are that AI must be the following: responsible, equitable, traceable, reliable, and governable. Such guidelines are relatively high level, though, leaving individual departments and agencies on their own to implement what each adjective means for a specific use case.

In February, after more than a year consulting with a range of experts, the Department of Defense (DoD) released five principles for ethics around artificial intelligence (AI). If AI doesn't meet these standards, the Department has said, it won't be fielded. "The United States, together with our allies and partners, must accelerate the adoption of AI and lead in its national security applications to maintain our strategic position, prevail on future battlefields, and safeguard the rules-based international order," Secretary Mark Esper said in the news release. The principles, which apply to combat and non-combat functions, are that AI must be the following: responsible, equitable, traceable, reliable, and governable. Such guidelines are relatively high level, though, leaving individual departments and agencies on their own to implement what each adjective means for a specific use case.