An unprecedented volume of data is currently being generated across the globe with no less than an estimated 2.5 quintillion (1018) bytes of data each day at our current pace. The variety of formats in which this data is being produced, and its structural complexity, are also on the rise. Collectively, these factors are driving demand among institutions for advanced analytics to generate actionable insights. At the most basic level, machine learning encompasses the use of computational algorithms more advanced than the analytics methods (data mining approaches, for example) traditionally employed to deliver insights into large datasets. Machine learning techniques are firmly rooted in the science of statistics and have valuable applications not least in financial services.

The United States Navy is developing robot submarine which will be controlled by Artificial Intelligence (AI) systems – with the ability to potentially kill without explicit human input. The project is named as'CLAWS' by the US Navy; however, very little information has been released about it. According to a report by New Scientist, the project is described as an'autonomous undersea weapon system' and carried out by the Office of Naval Research. Details of this killer-submersible were revealed as part of the 2020 budget documents which also disclosed its AI system name. Since this project is a'top secret', only a few details have been released including the fact that it will use sensors and algorithms to perform the complex missions on their own.

According to Gartner, "30 percent of data centers that fail to sufficiently prepare for AI will no longer be operationally or economically viable by 2020." With that milestone upon us, artificial intelligence (AI) is now -- or should be --part of a comprehensive and modern approach to data center maintenance and operations. When selling power and cooling, every operational efficiency that can be gained presents an opportunity for cost savings and infrastructure optimization. Balancing real-time need across an entire portfolio is challenging, particularly when also accounting for environment- and location-based variables. AI advances have reduced those challenges, allowing data center operators to more quickly and completely understand performance-based operations and adjust supply to true demand.

This special issue of Media-N gathers perspectives on artistic labor in an increasingly automated global economy, focusing on the impact of artificial intelligence and the role of Amazon.com, Inc. in reshaping how work is defined, valued, and performed. Our contributors are artists, curators, scholars, and critics interested in labor value, emerging forms of exploitation and alienation, as well as new possibilities for collective resistance, solidarity, and critique.

Rensselaer Polytechnic Institute is turning one of the most powerful supercomputers in the world against COVID-19. AiMOS, short for Artificial Intelligence Multiprocessing Optimized System, can perform eight quadrillion calculations per second and is uniquely capable of exploring new applications in artificial intelligence. RPI is offering the supercomputer to the research community--including government entities, academic universities, national labs, and private businesses--to support new coronavirus research. To combat the devastating effects of this pandemic, we must be able to fully grasp the complexities and interconnectedness of biological systems and epidemiological data, as researchers work to develop therapeutic interventions and address gaps in our knowledge. AiMOS is the most powerful supercomputer at a private university, the third-most energy-efficient supercomputer in the world, and the 24th most-powerful in the world overall.

It's already possible to take "snapshots" of the BIM as it evolves over time, using digital authoring software. When viewed as stand-alone files, these snapshots may not provide much information about workflow. However, when the files are compared automatically and continuously over time, they increase a project manager's understanding of the workflow involved, thus adding value. Kouhestani and Nik-Bakht saw an opportunity to improve BIM capability by automating an archiving and analyzing process. "We created an algorithm to make'event logs' that track changes in consecutive files," says Kouhestani. "Once we created the event logs, we used them as input for process mining."

The Centers for Disease Control and Prevention (CDC) has released a COVID-19 assessment bot, a chatbot that people can turn to for advice about whether they may be infected with coronavirus, officially called COVID-19. The tool is available on the CDC website, by clicking on the Coronavirus Self-Checker option. The bot asks questions like the location of the patient, their age and symptoms, their gender, and whether they have had recent contact with someone who has been confirmed to be sick. Then it suggests a course of action, whether it is to stay at home in isolation or to seek emergency care. The idea is to triage patients more efficiently into those who need immediate care and those who can safely stay at home and wait for the illness to run its course.

Machine learning companies have emerged as key players in enterprise IT over the few years. Why? Enterprise leaders have realized the value of having software that is capable of learning on its own without human intervention. Today, machine learning (ML) capabilities are baked into many different kinds of enterprise software. As machine learning has become ubiquitous, many organizations have begun building in-house data science teams. Many of these teams focus on analyzing business data to generate valuable insights, while others are incorporating machine learning capabilities into their company's products or using advanced algorithms to solve industry-specific problems. For these types of purposes, organizations often go looking for a general-purpose machine learning platform that can solve a wide variety of needs.

As artificial intelligence has become a growing force in business, today's top AI companies are leaders in this emerging technology. Often leveraging cloud computing, AI companies mix and match myriad technologies. Foremost among these is machine learning, but today's AI leading firms tech ranging from predictive analytics to business intelligence to data warehouse tools to deep learning. Entire industries are being reshaped by AI. RPA companies have completely shifted their platforms. AI in healthcare is changing patient care in numerous – and major – ways. AI companies are attracting massive investment from venture capitalist firms and giant firms like Microsoft and Google. Academic AI research is growing, as are AI job openings across a multitude of industries. All of this is documented in the AI Index, produced by Stanford University's Human-Centered AI Institute. Consulting giant Accenture believes AI has the potential to boost rates of profitability by an average of 38 percentage points and could lead to an economic boost of $14 trillion in additional gross value added (GVA) by 2035. In truth, artificial intelligence holds not just possibilities, but a plethora of risks. "It will have a huge economic impact but also change society, and it's hard to make strong predictions, but clearly job markets will be affected," said Yoshua Bengio, a professor at the University of Montreal, and head of the Montreal Institute for Learning Algorithms. To keep up with the AI market, we have updated our list of top AI companies playing a key role in shaping the future of AI. We feature artificial intelligence companies that are commercially successful as well as those that have invested significantly in artificial intelligence. AI companies in the years ahead are forecast to see exponential growth in deep learning, machine learning and natural language processing.

Now your iPhone or other Apple device can help you determine if you have symptoms associated with the coronavirus. You can simply ask Siri about symptoms of the coronavirus – "Siri, what are the symptoms of the coronavirus?" The assistant will ask you whether you certain symptoms such as fever, dry cough or trouble breathing and if you have been in contact with someone who might have contracted the virus. Even if Siri assesses that you are at lower risk, the assistant will offer some advice on hand washing and social distancing. Answers come from the U.S. Public Health Service and the Centers for Disease Control and Prevention.