Machine learning is quickly becoming an indispensable tool for many large companies. Everyone has, for sure, heard about Google's AI algorithm beating the World Champion in Go, as well as technologies like RankBrain, but machine learning does not have to be a mystical subject relegated to the domain of math researchers. There are many approachable libraries and technologies that show promise of being very useful to any industry that has data to play with. Machine learning also has the ability to turn traditional website marketing and SEO on its head. Late last year, my colleagues and I (rather naively) began an experiment in which we threw several popular machine learning algorithms at the task of predicting ranking in Google. We ended up with an assembly that achieved 41 percent true positive and 41 percent true negative on our data set.

The amount of energy consumed by big data centers has always been a headache for tech companies. Keeping the servers cool as they crunch numbers is such a challenge that Facebook even built one of its facilities on the edge of the Arctic Circle. Well, Google has a different solution to this problem: putting its DeepMind artificial intelligence unit in charge and using AI to manage power usage in parts of its data centers. A 40 percent reduction in the amount of electricity needed for cooling, which Google describes as a "phenomenal step forward." After accounting for "electrical losses and other non-cooling inefficiencies," this 40 percent reduction translated into a 15 percent reduction in overall power saving, says Google.

New technology is arriving faster than ever and holds the promise of solving many of the world's most pressing challenges, such as food and water security, energy sustainability and personalized medicine. In the past year alone, 3D printing has been used for medical purposes; lighter, cheaper and flexible electronics made from organic materials have found practical applications; and drugs that use nanotechnology and can be delivered at the molecular level have been developed in medical labs. However, uninformed public opinion, outdated government and intergovernmental regulations, and inadequate existing funding models for research and development are the greatest challenges in effectively moving new technologies from the research lab to people's lives. At the same time, it has been observed that most of the global challenges of the 21st century are a direct consequence of the most important technological innovations of the 20st century. Understanding the implications of new technologies are crucial both for the timely use of new and powerful tools and for their safe integration in our everyday lives.

What will laws on self-driving cars look like? Think black boxes and'minimum attention' • The...

Are you familiar with self-driving cars? These things would not be possible without the help of Machine Learning--the study of pattern recognition and prediction within the field of computer science. This course is taught by Stanford-educated, Silicon Valley experts that have decades of direct experience under their belts. They will teach you, in the simplest way possible (and with major visual techniques), to put Machine Learning and Python into action. With these skills under your belt, your programming skills will take a whole new level of power.

Data science companies are increasingly looking at portfolios when making hiring decisions. One of the reasons for this is that a portfolio is the best way to judge someone's real-world skills. The good news for you is that a portfolio is entirely within your control. If you put some work in, you can make a great portfolio that companies are impressed by. The first step in making a high-quality portfolio is to know what skills to demonstrate.

After we Save and Activate our process, we are now ready to test it.

US department store Macy's have announced the pilot of "Macy's On Call," a mobile web tool that allows customers to interact with an AI-powered platform, via their mobile devices. "Macy's On Call" leverages IBM's Watson technology, via Satisfi, an intelligent engagement platform, to deliver a first-of-its-kind solution that will enhance the customer in-store shopping experience at 10 test locations nationwide. The mobile companion, accessed via a mobile browser, allows customers to input natural language questions regarding each participating store's unique product assortment, services and facilities and receive a customized response to the inquiry. There are a number of ways that customers may request information. For example, a customer could type, "Where are the ladies shoes?" or type a combination of brand and product inquiry such as "INC dress," and they will receive the relevant response and location of that product in the store.

Tech City News held a roundtable attended by a variety of AI experts, who discussed the potential of AI and the ethical challenges posed by the technology. Yessi Bello Perez, our reporter, has more. Just last year, Stephen Hawking – arguably one of the world's brightest minds – predicted artificially intelligent computers would overtake humans at some point over the next century. Although it may have seemed like an outlandish statement at the time, the truth is that since Hawking's appearance at the Zeitgeist conference in London, artificial intelligence has reached buzzword status among the highest echelons of the global tech scene. AI-focused investors have emerged, funding in the space is soaring, tech giants are acquiring AI startups – and pouring significant resources into researching the technology – and the community is avidly discussing the technology's potential and its ethical implications.

In the enterprise support field, there's a trend to have self-service bots replace human assistants. In fact, by 2020, Gartner estimates that customers will manage 85 percent of their brand relationships without talking to a human, and brands are answering this call for more self-service. However, there will occasionally be a point at which self-service tools alone will not satisfy. Sometimes circumstances call for a live, human interaction. Virtual assistant chatbots are usually the first point of contact.