SAN FRANCISCO -- The cloud may be the future, but the specter of the PC lingers. Microsoft is the latest tech giant to learn that first-hand. Microsoft on Thursday posted substantial drops in revenue and earnings as it continues to navigate from its legacy PC business into emerging technologies -- a day after chip maker Intel announced a 11% workforce reduction. The computing giant reported a 5% decline in fiscal third-quarter revenue to 20.5 billion. Earnings of 3.8 billion, or 47 cents per share, fell from 5 billion, or 61 cents a share, in the same quarter a year ago.

During Build 2016 this year, Microsoft pitched a world of connected devices and sensors all speaking through cloud-backed machine learning models to developers. Microsoft is betting on a future that involves developers utilizing sensors that link to a vast pool of intelligent data to return immediate real-world benefits. Practicing what the company preaches, Microsoft's Solution Architect and Technical Manager of Microsoft Research, Kenji Takeda talks about how Cortana Intelligence suite is being used to secure safe drinking water for thousands of villages in rural Africa and Asia. A team consisting of Dr. Robert Hope of the REACH initiative, and machine learning experts David Clifton, an associate professor, and graduate student Farah Colchester have come together to try and secure safe and healthy water sources for 5 million poor people in Asia and Africa. The REACH program utilizes a series of mobile sensors connected to cloud computing to monitor water wells to secure a safe supply of water in more rural areas.

In Part 1, we said that Machine Learning is using generic algorithms to tell you something interesting about your data without writing any code specific to the problem you are solving. This time, we are going to see one of these generic algorithms do something really cool -- create video game levels that look like they were made by humans. We'll build a neural network, feed it existing Super Mario levels and watch new ones pop out! Just like Part 1, this guide is for anyone who is curious about machine learning but has no idea where to start. The goal is be accessible to anyone -- which means that there's a lot of generalizations and we skip lots of details.

In an art contest where robots are the artists, the future of art and artificially-intelligent computational creativity is on display. Fourteen teams from seven countries contributed 71 entries to the first RobotArt Competition. Started by artist and mechanical engineer Andrew Conru, the event aims to highlight the technical side of art creation and promote AI, image processing, and robotics. There are two different categories for robot artists: Fully automated and manually generated. Automated artwork means the entire process is done by a robot, running autonomously without input from the human creators.

See if your favorite'Game of Thrones' character will survive or die with this machine learning algorithm. You don't have to be a diehard Game of Thrones fan to know that characters are killed off left and right in the HBO series. What real fans don't know is the fate of their favorite characters in season 6, especially since war is coming. If you can't bear to wait one more second wondering what happened to Jon Snow out in the cold, you can check out this site that uses a machine learning algorithm to reveal which GoT characters will probably kick the bucket next. The algorithm was developed as part of a project called "A Song of Ice and Data" by students in a JavaScript Course at the Technical University of Munich.

IMAGE: Researchers collect information for the design of PAWS in a protected area for a trial patrol. A century ago, more than 60,000 tigers roamed the wild. Today, the worldwide estimate has dwindled to around 3,200. Poaching is one of the main drivers of this precipitous drop. Whether killed for skins, medicine or trophy hunting, humans have pushed tigers to near-extinction.

When we think of automation in the workplace, the first jobs that come to mind of being most at threat are low paying, low-skilled jobs. While this is definitely true, advances in technology are starting to threaten high paying, higher skilled jobs. Due to the advancements in robotics, artificial intelligence and machine learning, there seem to be very few jobs, if any, that will be completely immune to, if not replacement, then some sort of alteration. This market snapshot looks at how the progression of machine learning could impact on jobs we thought immune to automation. We look at the impact of automation on the middle class and what support would need to be available to people losing their jobs.

My wife can spend up to eight hours a day typing reports in Microsoft Word 2010 and due to RSI issues, is thinking about investing in some speech recognition software. There seems to be a huge diversity in the price of these, and we need to know how much we should spend and how reliable they are.

A program designed by MIT to battle hackers is example of effective artificial intelligence and human collaboration. South Korean professional Go player Lee Sedol puts the first stone against Google's artificial intelligence program, AlphaGo.

Last week, the New York Times reported the first successful "limb reanimation" in a person with quadriplegia. Ian Burkhart, 24, had broken his neck as a teen in a diving accident. His spine was damaged at the fifth cervical vertebra, leaving him paralyzed from the shoulders down. Using nerve bypass technology that transmits his thoughts directly to his hand muscles, he has regained control over his right hand and fingers. This is the first time a brain-computer interface has been used to help an individual move his own hands.