Note: Videos may auto start with sound so be prepared. How The Monster at the End of This Book (a Grover story I enjoyed with my kids) helped teach an author about the power of literature and its influence on the reader. I received a slightly different lesson from reading it in terms of perception, but both are there in this short, but powerful, children's early reader. Kareem Abdul-Jabbar may be best known as a sports persona, but what he's doing to bring STEM education to inner city students is impressive as shown in this interview about his Skyhook Foundation. Enjoy a wander through the history of a medieval street preserved until modern day in York, England.

Muse is creating an advanced AI to search the world's video. We are looking for engineers who want to be at the forefront of search and discovery to make searching video as intuitive as recalling a memory in your mind. We are working across the frontiers of storage & distributed file systems, machine learning infrastructure, high performance computing and intuitive user interfaces across (web, mobile, voice and beyond). You will join the machine learning team in sunny Lisbon with a focus on implementing and productionizing the latest machine learning algorithms to analyze video and interpret the knowledge inside video across speech, people, objects, actions and locations. We are agnostic to the algorithms, but care deeply about the computational efficiency of these algorithms in the analysis of a video file.

Britain's map maker is demonstrating that machine learning isn't all hot air – but has discovered just how much donkey work is involved. The Ordnance Survey set up an ML experiment to identify roofs from its remote sensing data (satellite and aerial imagery), and found the trial reached 87 per cent accuracy within a week, from a standing start. That's still less accurate than humans (at 95 per cent), but that's not the point – it could process thousands in the time it takes a human to do one. "Your mission, should you choose to accept it, is to classify this roof..." [Source: Ordnance Survey] "It does have the potential to revolutionise our operations," an OS spokesman enthused. The week-long prototype isn't ready for deployment because it isn't yet accurate enough, but it promises to accelerate visual data analysis.

Whether financial institutions are looking for improved customer service, risk management, fraud prevention, investment prediction or cybersecurity, the scopes of machine learning and artificial intelligence are limitless. In the modern era of the digital economy, technological advancements are no longer a luxury for the organizations, but a necessity to outsmart their competitors and business growth. With the technological advancements in the recent times, the impact of Machine Learning (ML) and Artificial Intelligence (AI) are very critical than ever before. Previously, we discussed the scopes of big data and data science in banking and financial services. In this article will explain in detail about ML and AI, and their scopes in banking and financial services. Apparently, in order to be successful and making an impact, the banks and financial institutions need to make machine learning and artificial intelligence an expansion of their big data and data analytics approach.

The Optimizing Government Project brings together scholars and researchers to discuss the use of machine learning by government. In recent years, the private sector has succeeded in finding many ways to leverage machine learning--a type of artificial intelligence that enables computers to "learn and adapt through experience." Well-known private sector applications of machine learning include Google's self-driving car project, online recommendations personalized for customers on websites like Amazon and Netflix, and fraud detection by credit card companies. But as the private sector embraces machine learning in new ways, the application of machine learning by government agencies has only started to take root. The use of artificial intelligence by government, though, raises important questions for a democratic society--about fairness, equality, transparency, and accountability.

"Why incur the expense of generating and collecting all of this IoT data if you're not going to monetize it?" Organizations are racing to embrace the Internet of Things (IoT) as the pundits create "visions of sugar-plums dancing in their heads." McKinsey Global Institute released their study "The Internet of Things: Mapping the Value beyond the Hype" in June 2015 that highlighted the staggering financial value that IoT could create! The folks at Wikibon provided a perspective on the sources of "IoT monetization" in their recent research titled "Harvesting Value at the Edge" written by the always delightful and provocative Neil Raden. IoT, though a useful application of available technology, and well-defined at the hardware and network levels, the heart of IoT, that part that yields the real value, is edge analytics.

Volvo is adjusting the timeline on its ambitious Drive Me autonomous program until it can find the right sensors. "The development in sensor performance and processor capabilities is going so much faster than we expected in 2013," program director Marcus Rothoff recently told Automotive News Europe. "Because advancements are being made at such a rapid pace, we want to make this decision as late as possible." In addition to the sensors that enable Level 4 autonomy (the car can drive itself, but a steering wheel and pedals are still present), the Swedish automaker is having issues with the wiring. Rothoff said that laying copper has been "a really huge" challenge that was unanticipated at the project's outset in 2013.

By thinking of atoms as letters and molecules as words an Artificial Intelligence (AI) from IBM is now using the same neural network techniques that other AI's use to translate between different languages to predict the outcomes of organic chemical reactions, and the breakthrough could help speed up the development of new drugs. Scientists have been trying to teach computers about chemistry for decades in the hope that one day they'll be able to help them discover and predict the outcomes of chemical reactions but organic chemicals can be extraordinarily complex, and past simulations of their behaviours have been at best time consuming and inaccurate. Now though the team at IBM, and their new AI have tried a different technique to solve this thorny problem. "Instead of translating English into German or Chinese, we had the same artificial intelligence technology look at hundreds of thousands or millions of chemical reactions and got it learn the basic structure of the'language' of organic chemistry, and then we had it try to predict the outcomes of possible organic chemical reactions," said the study's co-author Teodoro Laino from IBM Research's lab in Zurich. "We want to help chemists design new synthesis routes for organic compounds," he added.

A combined physical and digital games chart is finally coming to the UK. GfK's charts are considered the gold standard because of its relationship with the ERA, which counts GAME, Amazon and the nation's top supermarkets among its members. Now, the ERA has announced that its exclusivity deal with GfK will end in January 2019. Around the same time, it will start working with the Interactive Software Federation of Europe (ISFE) and data services provider B2Boost on charts that include both physical and digital sales. It's not clear, however, just how many of the major console and marketplace providers are on board -- a reflective multi-platform chart, for instance, would require representation from Nintendo (eShop), Sony (PSN), Microsoft (Xbox Store) and Valve (Steam).

A computer with an automatic facial recognition system shows German Interior Minister Thomas de Maiziere, center right, as he visits the Suedkreuz train station in Berlin, Friday, Dec. 15, 2017. At the train station, German authorities test automatic facial recognition technologies.