In the previous recipe "Engage Machine Learning for detecting anomalous behaviors of things", we saw how one can integrate IBM Watson IoT, Apache Spark service, Predictive Analysis service and Real-Time Insights to take timely action before an (unacceptable) event occurs. And in this recipe, we will make use of the data (historical data) produced by the previous recipe to discover the hidden patterns, temperature trend over the days, month and year using Apache Spark SQL, Pandas DataFrame and Jupyter Notebook. Apache Spark SQL is a Spark module for structured data processing. Unlike the basic Spark RDD API, the interfaces provided by Spark SQL provide Spark with more information about the structure of both the data and the computation being performed. Internally, Spark SQL uses this extra information to perform extra optimizations.

This controversial question is argued by many who hold very strong opinions.

Google has built its own computer chip. And this won't be the last. The Internet's most powerful company sent a few shock waves through the tech world yesterday when it revealed that a new custom-designed chip helps run what is surely the future of its vast online empire: artificial intelligence. In building its own chip, Google has taken yet another step along a path that has already remade the tech industry in enormous ways. Over the past decade, the company has designed all sorts of new hardware for the massive data centers that underpin its myriad online services, including computer servers, networking gear, and more. As it created services of unprecedented scope and size, it needed a more efficient breed of hardware to run these services.

Magenta will use TensorFlow, the machine-learning engine that Google built and opened up to the public at the end of 2015, to determine whether AI systems can be trained to create original pieces of music, art, or video. Much in the same way that Google opened up TensorFlow, Eck said Magenta will make available its tools to the public. Roberts also showed off a simple digital synthesizer program he'd been working on, where an AI could listen to notes that he played, and play back a more complete melody from those notes: The goal of the project, Eck suggested, could well be to create a system that could give a listener "musical chills" with entirely new pieces of music, on a regular basis, as they sit listening to computer-generated music from the comfort of their couch at home. Eck said the inspiration for Magenta had come from other Google Brain projects, like Google DeepDream, where AI systems were trained on image databases to "fill in the gaps" in pictures, trying to find structures in images that weren't necessarily present in the images themselves.

Magenta will use TensorFlow, the machine-learning engine that Google built and opened up to the public at the end of 2015, to determine whether AI systems can be trained to create original pieces of music, art, or video. Much in the same way that Google opened up TensorFlow, Eck said Magenta will make available its tools to the public. Roberts also showed off a simple digital synthesizer program he'd been working on, where an AI could listen to notes that he played, and play back a more complete melody from those notes: The goal of the project, Eck suggested, could well be to create a system that could give a listener "musical chills" with entirely new pieces of music, on a regular basis, as they sit listening to computer-generated music from the comfort of their couch at home. Eck said the inspiration for Magenta had come from other Google Brain projects, like Google DeepDream, where AI systems were trained on image databases to "fill in the gaps" in pictures, trying to find structures in images that weren't necessarily present in the images themselves.

Google wants to put the art back in artificial intelligence. During the last session at Moogfest, a four-day music and technology festival, in Durham, North Carolina, Douglas Eck, a researcher on Google Brain, the company's artificial-intelligence research project, outlined a new group that's going to focus on figuring out if computers can truly create. The group, called Magenta, will launch more publicly at the start of June, but attendees at Moogfest were given a taste of what it's going to be working on. Magenta will use TensorFlow, the machine-learning engine that Google built and opened up to the public at the end of 2015, to determine whether AI systems can be trained to create original pieces of music, art, or video. This is no simple task, given that even the most advanced artificially intelligent systems have enough trouble copying the styles of existing artists and musicians, let alone coming up with entirely new ideas themselves.

Volkswagen, acknowledging the growing automotive importance of machine learning, has acquired a stake in the German Research Center for Artificial Intelligence (DFKI). "Artificial intelligence (AI) is a key technology for autonomous driving and therefore an investment in our future," VW Group CEO Matthias Mueller said in a press statement. "We want to forge ahead with AI research in the automotive industry and beyond." VW also hopes its involvement in DFKI, one of the world's biggest AI research institutes, will help it with the digitalization of plants and a range of corporate processes. Many carmakers have been expanding their AI activities as an industry-wide effort to build autonomous vehicles is stretching current computer capacity to its limits.

Computer users have long relied on Nvidia Corp.'s technology to paint virtual worlds on the screen as they gunned down videogame enemies. Now some researchers are betting it can also help save lives--of real people. Massachusetts General Hospital recently established a center in Boston that plans to use Nvidia chips to help an artificial-intelligence system spot anomalies on CT scans and other medical images, jobs now carried out by human radiologists. The project, drawing on a database of 10 billion existing images, is...

Machine Learning today tends to be "open-loop" – collect tons of data offline, process them in batches and generate insights for eventual action. There is an emerging category of ML business use cases that are called "In-Stream Analytics (ISA)". Here, the data is processed as soon as it arrives and insights are generated quickly. However, action may be taken offline and the effects of the actions are not immediately incorporated back into the learning process. If we did, it is an example of a "closed-loop" system – we will call this approach "Adaptive Machine Learning" or AML.

Douglas Eck, a researcher at Google, talks about Magenta during at panel at Moogfest. If Google's artificial intelligence can paint its dreams, why not make other kinds of art? On June 1, Google is set to launch Magenta, a research project to explore using artificial intelligence to create art, and make that process easier for TensorFlow users. The group has about six researchers now, and will invite other academics to help try to solve the problem of creative machines. The project exists within Google Brain group.