The robots haven't just landed in the workplace--they're expanding skills, moving up the corporate ladder, showing awesome productivity and retention rates, and increasingly shoving aside their human counterparts. One multi-tasker bot, from Momentum Machines, can make (and flip) a gourmet hamburger in 10 seconds and could soon replace an entire McDonalds crew. A manufacturing device from Universal Robots doesn't just solder, paint, screw, glue, and grasp--it builds new parts for itself on the fly when they wear out or bust. And just this week, Google won a patent to start building worker robots with personalities. As intelligent machines begin their march on labor and become more sophisticated and specialized than first-generation cousins like Roomba or Siri, they have an outspoken champion in their corner: author and entrepreneur Martin Ford.

IDC defines Digital Transformation as the continuous process by which enterprises adapt to or drive disruptive changes in their customers and markets by leveraging digital competencies to create new business models, products and services. Digital Transformation empowers organization to take advantage of all their existing digital assets in new ways, allowing enterprises to re-envision their entire business, including customer experience, operational processes and financial models. This is achieved by tapping into their DARK DATA, that valuable 80% of data assets that are not being utilized by organizations, which includes emails, internal documents, customer claims, and any other text based data. In 2016, and over the next several years, Cognitive Computing and IoT are two critical building blocks for digitally transforming today's organization into tomorrow's thinking businesses. By 2018 over 50% of enterprises are expected to embed cognitive capabilities in their apps and services (IDC March 2016).

Data scientists are often drawn to the profession excited by the chance to spend their days on cutting-edge research and development and working with fantastic new machine learning algorithms. While this is indeed a fun and exciting part of the job, as most data scientists in the field will tell you, much of one's time is spent cleaning, transforming, and engineering the data. The common wisdom is that, given enough data, most standard algorithms will be able to (eventually) detect the signal. This is the thesis that in large N, when you have enough data points, all machine learning algorithms tend to converge on the same answer.

This ANN introduction only covers the basic fundamentals. In the next chapter, we will learn about further techniques that gives ANN its powerful predictive capabilities. Subscribe below to be notified once the next part is out. Enter your email address to follow this blog and receive notifications of new posts by email.

Algorithms increasingly run our lives. They find books, movies, jobs, and dates for us, manage our investments, and discover new drugs. More and more, these algorithms work by learning from the trails of data we leave in our newly digital world. Like curious children, they observe us, imitate, and experiment. And in the world's top research labs and universities, the race is on to invent the ultimate learning algorithm: one capable of discovering any knowledge from data, and doing anything we want, before we even ask.

Microsoft created Tay as an experiment to learn more about how artificial intelligence programs can engage with Web users in casual conversation. The project was designed to interact with and "learn" from the young generation of millennials. Tay began its short-lived Twitter tenure on Wednesday with a handful of innocuous tweets. In one typical example, Tay tweeted: "feminism is cancer," in response to another Twitter user who had posted the same message. Lee, in the blog post, called Web users' efforts to exert a malicious influence on the chatbot "a coordinated attack by a subset of people." "Although we had prepared for many types of abuses of the system, we had made a critical oversight for this specific attack," Lee wrote.

There are a lot of creepy things you can do with the data gleaned from an online and mobile maps service used by 302 million people, but there are helpful ways to use it too. Baidu, China's version of Google, is making the case that it can use queries made on its maps service to predict areas where overcrowding may put people at risk for fatal accidents. In a paper titled "Early Warning of Human Crowds Based on Query Data from Baidu Map: Analysis Based on Shanghai Stampede," three Baidu researchers based in Beijing lay out an approach to using big data to give early warnings about potential crowd disasters 1-3 hours in advance. This data is already used by Chinese city planners to help them place transportation, facilities, and shops, according to MIT Technology Review. Now it can be used in the interest of public safety, the researchers assert.

TECH ENTREPRENEUR Elon Musk has been warning that the Age of the Robots is coming soon -- and it might not be pleasant for us. He may be right and he may be wrong on that, but one thing is sure: One robot certainly gave the anti-Whites a headache just this week. On Wednesday, tech giant Microsoft, the third largest corporation on Earth in terms of market value, launched and then immediately withdrew an Artificial Intelligence robot in the persona of a 19-year-old American girl called "Tay." Tay was a "chatbot," which interacted with real humans on the social media platform Twitter and was designed to learn from its interactions. Tay learned so fast that Microsoft pulled her offline in less than a single day.

SAN FRANCISCO • The resounding win by a Google artificial intelligence (AI) programme over a champion in the complex board game Go this month was a statement - not so much to professional game players as to Google's competitors. Many of the tech industry's biggest companies, like Amazon, Google, IBM and Microsoft, are jockeying to become the go-to company for AI. In the industry's lingo, they are engaged in a "platform war". A platform, in technology, is essentially a piece of software that other companies build on and that consumers cannot do without. Become the platform and huge profits will follow.

A drone has successfully delivered a package to a residential location in a small Nevada town in what its maker and the governor of the state said Friday was the first fully autonomous urban drone delivery in the U.S. Flirtey CEO Matt Sweeney said the six-rotor drone flew about a half-mile along a pre-programmed delivery route on March 10 and lowered the package outside a vacant residence in an uninhabited area of Hawthorne, southeast of Reno. The route was established using GPS. A pilot and visual observers were on standby during the flight but weren't needed, Sweeney said. He said the package included bottled water, food and a first-aid kit. "Conducting the first drone delivery in an urban setting is a major achievement, taking us closer to the day that drones make regular deliveries to your front doorstep," Sweeney said. Nevada Gov. Brian Sandoval congratulated the company "on successfully completing the nation's first fully autonomous urban package delivery."