Tucked away in western Wisconsin, not terribly far from Minneapolis, sits a factory full of babies. This factory produces each baby in just 15 minutes, and sells them for $649 apiece. Many of them are given to teenagers, in a bid to keep them from having babies of their own. These'bot babies teach would-be parents and medical types how to care for a newborn, and let teenagers experience being awakened in the wee hours by a wailing infant so perhaps they'll think twice about pregnancy. Realityworks calls them RealCare babies and started producing them in 1994, when the dolls went by the name Baby Think It Over.

According to Mark Cuban, "The world's first trillionaires are going to come from somebody who masters AI." And as we continue to encounter stories and predictions about AI, we're seeing how it will fundamentally change a variety of industries on an almost day-to-day basis. The challenge, however, lies in effectively explaining what this type of technology can do to improve job functions. The lack of articulating the concept of AI (in this case) is typical of any hype cycle; but, the truth is that implementing systems to make dynamic and complex decisions as a way to displace humans is way off from mainstream adoption. As we move further into 2017, we will start to see the hype die down and broader adoption of AI-based solutions within organizations -- particularly in data analysis and deriving insight from that data.

Let's think about all of the new technologies that have hit the market in the past year or so. We've all heard about the iPhone 7, Google's driverless cars, Snapchat Glasses, and even Elon Musk's'city on Mars'. The evolution of big data and advanced analytic solutions have made it possible for marketers to build a clearer picture of their target audiences than ever before; and in this hotbed of advancement lies artificial intelligence (AI) marketing. Armed with big data insights, digital marketers can greatly boost their campaigns' performance and ROI, all of which can be achieved with essentially no extra effort on the marketer's part. But, what exactly is artificial intelligence marketing?

Market pull for better factory automation and the ever-increasing relevance of software in every domain are triggering a rethink in how we develop software for robotics. Techniques such as Model Driven Engineering (MDE), proven effective in businesses like automotive and aerospace, can be used to this end. Practices such as collaborative development through Open-Source Software (OSS) can also be used. Two projects funded by the European Horizon 2020 research and innovation programme are exploring these opportunities, in a common foundational effort for an EU Digital Industrial Platform for Robotics. RobMoSys, coordinated by the French Alternative Energies and Atomic Energy Commission, envisions a composition-oriented approach to system-of-system integration which is independent of the current code-centric robotic platforms, yet can build on top of them.

He enrolled in the NYC Data Science Academy 17-week remote bootcamp program, taking place from January to April 2017. This post is based on his third class project focusing on web scraping in Python. The original article can be found here. Clean technology continues to undergo significant advancements spanning technology, sustainability, financial, and policy issues. Given the field's large scope, there is no shortage of news outlets covering the action.

We are trying to improve the efficiency in power networks. The under-utilisation is even worse for renewables! Consumers end up footing the bill for this chronic inefficacy. Because we think we can't control demand, so we have to over-supply in case of spikes… The gateway contains hard-coded information on the assets it controls, sensors that help it tell when the asset has stored energy and constraints (such as peak tariff avoidance), enabling it to dispatch them when grid frequency is too low or too high. The aggregation means that each asset need not be a proportional control to grid frequency, but remains free to perform operational duties 94% of the time – our service is invisible to the end customer (except for the monthly checks).

Disruptive technology has had a profound impact on academic institutions. STEM subjects have benefitted hugely from new tech, but technological disruption has also changed the way that social studies and economics is taught. As well as working alongside companies, universities (as well as colleges and schools) train students to navigate the changing world. For example, Ohio State University and Carnegie Mellon University have both opened classes in smart city technology. Academia is a key resource for tech firms, providing hubs of innovation with the knowledge and talent to complete successful projects.

Geologists have long been able to work out the approximate risk of an earthquake. Their approach is to work out when the fault moved in the past and use any periodicity to predict the future. The most famous example involves the Parkfield segment of the San Andreas Fault in California, one of the most carefully studied faults on the planet. Earthquakes occurred here in 1857, 1881, 1901, 1922, 1934, and 1966, suggesting a pattern in which quakes occur every 22 years give or take a few years. Geologists therefore predicted that a quake would occur between 1988 and 1993, but they had to wait until 2004 for their temblor.

Robots are probably the first thing you think of when asked to imagine AI applied to industrials and manufacturing. Indeed many innovative companies like Rodney Brooks' Rethink Robotics have developed friendly-looking robot factory workers who hustle alongside their human colleagues. Industrial robots have historically been designed to perform specific niche tasks, but modern-day robots can be taught new tasks and make real-time decisions. As sexy and shiny as robots are, the bulk of the value of AI in industrials lies in transforming data from sensors and routine hardware into intelligent predictions for better and faster decision-making. By 2020, Cisco predicts the number will surpass 50 billion.

In late February, the UN-Secretary General held a press conference, highlighting the risk of starvation in East Africa and the necessity to raise funds to address the emergency situations in Somalia and South Sudan. Drought has been back in these countries and their neighbours since 2016, leading to a huge current food crisis. While governments are trying to handle the situation, how could technology innovations help prevent starvation and improve agriculture management in the future? We met with Laurent Rivière, a French 30 years-old entrepreneur, who shared with us his view on the subject with a combination of engineer pragmatism and changemaker idealism . Founder and CEO at Sunbirds for two years, he explained to us how his "bird of the sun," his solar drone, is addressing the agriculture challenges of the 21st century.