Sessions include: 1) Setting the Scene: The Machine Intelligence Landscape in Renewables; 2) Predicting Energy Consumption Using Machine Learning; 3) Deep Learning for Multiple Weather Prediction Models; and 4) Discussion: What Are The Next Steps?

I just got back from SXSW where I was on a panel entitled "Can AI Systems Really'Think?'"

Seymour Papert with LEGO Mindstorms robotics kits, which were named in recognition of Papert's seminal book, Mindstorms: Children, Computers, and Powerful Ideas. Seymour Papert with LEGO Mindstorms robotics kits, which were named in recognition of Papert's seminal book, Mindstorms: Children, Computers, and Powerful Ideas. The field of educational technology is mourning a visionary whose work was considered 50 years ahead of its time. Seymour Papert, who died July 31 at age 88, was a mathematician and computer scientist who spent decades at MIT. "Seymour was one of the very first people to recognize that new computer technologies could be used by kids to create things in new ways and express themselves," Mitchel Resnick, a professor of learning research at MIT and a longtime colleague and friend, told NPR Ed. "It's amazing that Seymour was thinking these ideas in the 1960s," Resnick adds, "when computers cost hundreds of thousands of dollars, but he foresaw the day that every child would have access to a computer." The great theme of Papert's work and life was the nature of intelligence, or what he called thinking about thinking.

When we talk about artificial intelligence, many imagine a world of science fiction where robots dominate. In reality, artificial intelligence is already improving current technologies such as online shopping, surveillance systems and many others. In the area of cyber security, artificial intelligence is being used via machine learning techniques. Indeed, the machine learning algorithms allow computers to learn and make predictions based on available known data. This technique is especially effective for daily process of millions of malware.

Ronnie Vuine runs a Berlin-based startup that harnesses artificial intelligence for industrial uses – but that doesn't mean he's all business, all the time. His company Micropsi Industries also programmed an A.I. game piece known as D1 "for fun, and because we want to show what's possible," he told Handelsblatt. D1's A.I. "brain" looks a bit like a fire hydrant spraying out countless tiny streams of water. The figure uses trial and error to track down food, Mr. Vuine explained, and each stream represents a different experience.

Scientists have developed a new software that can analyse the handwriting of any individual and accurately replicate it, an advance that may spark the comeback of the handwritten word in a world dominated by the QWERTY keyboard. Researchers at University College London (UCL) created'My Text in Your Handwriting', a programme which examines a sample of a person's handwriting and generates new text saying whatever the user wishes, as if the author had handwritten it themselves. "Our software has lots of valuable applications," said Tom Haines, from UCL. "Stroke victims, for example, may be able to formulate letters without the concern of illegibility, or someone sending flowers as a gift could include a handwritten note without even going into the florist," Haines said. "It could also be used in comic books where a piece of handwritten text can be translated into different languages without losing the author's original style," he said. The machine learning algorithm is built around glyphs – a specific instance of a character.

WEF names robotics as one of the areas of technology that could revolutionise finance in the next few decades. Biometrics, cloud computing, cognitive computing, blockchain technology, machine learning, quantum computing, and robotics are set to transform financial services over the next few decades, according to the World Economic Forum (WEF). WEF made the prediction in its "Future of Financial Infrastructure" report looking at blockchain technology, which was published on Friday. The influential non-profit rates the transformative potential of these new technologies alongside past innovations such as the personal computer, the internet, and smartphones. WEF's report focuses on blockchain technology -- referred to as distributed ledger technology in the above graphic -- so it does not actually give any concrete examples of how technologies other than blockchain might be applied to finance.

The robots are coming, and they're getting smaller, smarter and cheaper. While today, businesses may own just a single drone, one day, large parts of whole industries could be overseen by a new generation of robots. But, how will groups of these robots perform useful tasks like collecting crop data or organizing around a common goal? That's one role for the blockchain proposed in a new white paper from MIT Media Lab research affiliate Eduardo Castello Ferrer. The eight-year robotics veteran believes that by using the blockchain to distribute information, whole armies of robots could solve problems and accomplish tasks more efficiently. The idea is that in robotic swarms, each robot follows basic rules, drawing inspiration from creatures like ants and fish that often clump together.

Below is a compilation of APIs that have benefited from Machine Learning in one way or another, we truly are living in the future so strap into your rocketship and prepare for blastoff. To check out all this information, click here.

Chipmaker Intel today announced that it has acquired Nervana, a startup that has been developing artificial intelligence software and hardware. Terms of the deal weren't disclosed, but a source familiar with the matter told VentureBeat Intel paid more than 350 million. "Nervana's Engine and silicon expertise will advance Intel's AI portfolio and enhance the deep learning performance and TCO of our Intel Xeon and Intel Xeon Phi processors," Diane Bryant, executive vice president and general manager of Intel's Data Center Group, said in a blog post. While Intel has a running business in high-performance computing (HPC), it has taken a back seat to Nvidia, another HPC supplier, when it comes to creating chips for deep learning, a trendy type of artificial intelligence that involves training artificial neural networks on lots of data and then getting them to make inferences on new data. Google has deployed competing chips named tensor processing units (TPUs) that can handle Google's TensorFlow open source deep learning framework.