Maduro's critics say he is using the incident to stifle dissent and cement his power in the oil-rich nation amid the economic crisis that has brought with it hyperinflation and power cuts. He says his government is the victim of an "economic war" led by opposition activists with the help of Washington.

Enthought instructors have doctorates in scientific fields such as physics, engineering, computer science, and mathematics, and all have extensive experience through research and consulting in applying Python to solve complex problems across a range of industries, allowing them to bring their real world experience to the classroom every day. Enthought instructors possess professional, first-hand experience with the tools and technologies covered in our courses.

Of course, intelligent automation can't arrive at your business overnight. Transitioning from an entirely human workforce to one in which humans and robots work side-by-side must be a gradual process. However, the vast majority of companies find that the benefits of intelligent automation far outweigh the effort required to implement it within their organization, so start with a test run by implementing small automation projects, and then move to a company-wide deployment as you grow more comfortable.

Meltwater, the business intelligence platform is launching an AI-powered data science platform called Fairhair.ai. Meltwater is not the first business to dive into the AI vortex, but its involvement can prove to be a real game changer. As the company argues, more and more businesses are relying on AI to obtain useful business intelligence and better understand audiences and context. Originally developed to power Meltwater's media intelligence and social analytics products, Fairhair.ai Moreover, the tool offers integration opportunities, namely embedding the platform's capabilities into enterprise risk management toolkits.

The use of knowledge discovery on the Internet of Things (IoT) and its allied domains is undeniably one of the most indispensable ones, which results in optimized placement architectures, efficient routing protocols, device energy savings, and enhanced security measures for the implementation. The absence of knowledge discovery in IoT results in just an implementation of large‐scale sensor networks, which generates a huge amount of data, and which needs, an often under‐optimized, processing for actionable outputs. In this survey, we explore various domains of IoT for which knowledge discovery is inseparable from the application, and show how it benefits the overall implementation of the IoT architecture.

In the quest to become data-driven, companies are increasingly investing in Business Intelligence software to gain a competitive advantage. Yet the insights generated by those tools are mostly fueled by data from within a company's walls, instead of the real-time market signals found externally online – from consumer opinions to corporate filings. This outside data can unlock key indicators about an industry or competitor, but harnessing the volume and variety of global data is a time-intensive task. And although advances in artificial intelligence have made it easier to capture and analyze this data to create powerful insights, most commercial AI tools are one-size-fits-all models with limited capabilities. Keeping this in mind, Meltwater is opening up its AI platform, Fairhair.ai,

AI research group DeepMind created the new tech that is able to spot key signs of eye disease just as well as the world's top doctors. A link has been sent to your friend's email address. A link has been posted to your Facebook feed. AI research group DeepMind created the new tech that is able to spot key signs of eye disease just as well as the world's top doctors.

Sounds a bit unsettling, but this creepy, crawly robot could eventually save your life. A link has been sent to your friend's email address. A link has been posted to your Facebook feed. Sounds a bit unsettling, but this creepy, crawly robot could eventually save your life.

When engineers or designers want to test the aerodynamic properties of the newly designed shape of a car, airplane, or other object, they would normally model the flow of air around the object by having a computer solve a complex set of equations--a procedure that usually takes hours, or even an entire day. Nobuyuki Umetani from Autodesk research (now at the University of Tokyo) and Bernd Bickel from the Institute of Science and Technology Austria (IST Austria) have now significantly sped up this process, making streamlines and parameters available in real time. Their method, which is the first to use machine learning to model flow around continuously editable 3-D objects, will be presented at this year's prestigious SIGGRAPH conference in Vancouver, where IST Austria researchers are involved in a total of five presentations. Machine learning can make extremely time-consuming methods a lot faster. Before, the computation of the aerodynamic properties of cars usually took a day.

Have your machine learning (ML) services stalled out? Are stakeholders beginning to doubt their veracity? The application of machine learning is often mistaken to be an efficient, intelligent process. Data goes in and precise insights are quickly produced. The fact is, machine learning is still very much driven by humans.