Let's be honest, stupid humans are too smart sometimes for their own good and Skynet is going to happen, at least that's what Bill Gates, Stephen Hawking and Elon Musk think, but what do they know? In 2014, Stephen Hawking wrote: "Success in creating AI would be the biggest event in human history, – Unfortunately, it might also be the last, unless we learn how to avoid the risks. In the near term, world militaries are considering autonomous-weapon systems that can choose and eliminate targets." In a separate interview in the same year, he warned: "humans, limited by slow biological evolution, couldn't compete and would be superseded by A.I." In a Reddit Q&A Session in January 2015 Gates said: "I am in the camp that is concerned about super intelligence. First the machines will do a lot of jobs for us and not be super intelligent. That should be positive if we manage it well. A few decades after that though the intelligence is strong enough to be a concern. I agree with Elon Musk and some others on this and don't understand why some people are not concerned."

Oren Etzioni, CEO of the Allen Institute for Artificial Intelligence and an investor in Algorithmia, believes these algorithm can help transform deep learning from a "dark art" practiced only by the giants of the Internet into a technology used by "the 99 percent." Dennis R. Mortensen, the CEO and founder of the artificial intelligence startup x.ai, agrees--up to a point. He adds that these algorithms serve only some needs. As he points out, other companies are providing more complex tools for building deep learning systems, including Google, which recently open sourced a deep learning software engine called TensorFlow. He also points out that deep learning requires enormous amounts of data for training.

Modern radar and communications systems can subtly and quickly change their character, making them harder for U.S. aircraft and other platforms to jam or spoof. That reality is prompting DARPA to lead industry teams to apply artificial intelligence to electronic warfare. The difference between today's tech and that of the 1970s lies in the adoption of readily available digital processing. Such processing effectively allows operators to change aspects of the waveforms that radar and communications systems use. "The problem now is that if we continue to rely on that [old] approach, the radar waveforms we're expecting could be rapidly changed," Tilghman says.

While we'll continue to see businesses in and out of the retail space launch with AI at the core, this approach certainly won't make sense for all retailers. Instead, established retailers can apply AI to different business units. Recently, Macy's announced its customer service unit is testing a "mobile companion" tool using AI. The tool enables shoppers to get answers based on the store that they are physically shopping in rather than having to find a sales associate. While this is a great way to leverage AI to engage with current shoppers, what about using the technology to acquire new ones?

A Chicago company called Narrative Science was among the first to give computers the power of the pen -- or keyboard. It's created a software called Quill. And, like anyone with a creative streak, automated writing software likes to stretch its artistic muscles. The best part is, this virtual reality and machine learning revolution will spark the investing trend of the decade ahead.

This technology will affect the quality, pace and structure of daily living for everyone. Believe it or not, robotic personal assistants at home -- particularly for older people -- will be common by 2025. With startling effect, machines increasingly will do the thinking for us. Big data, a computer's ability to gather vast amounts of information in complex databases, will be stored in the limitless spheres of Cloud technology. And the deep learning capability of artificial intelligence software, able to learn from its own mistakes and experiences to improve functionality, will progressively eliminate the need for thousands of tasks now performed by humans.

A new release out of the company reports, "Dataiku, the maker of the all-in-one predictive analytics software platform Dataiku Data Science Studio (DSS), has today announced the release of Dataiku DSS 3.1, which now enables transformations in Apache Spark's Scala, adds additional external integrations, an improved UX interface, and includes 5 machine learning engines in its visual analysis section. Dataiku DSS 3.1 introduces new visual machine learning engines that allow users to create incredibly powerful predictive applications within a code-free interface. Users of all skill levels can now leverage HPE Vertica machine learning, H2O Sparkling Water, MLlib, Scikit-Learn, and XGBoost directly from within the visual analysis section of Dataiku DSS 3.1 to apply powerful machine learning algorithms to their data science projects without having to write a single line of code."

TensorFlow is an open source Python library for machine learning. It does mathematical computation using dataflow graphs. Data mining and machine learning are key methods used to gain information from databases in which hidden patterns are analysed from a huge repository of records. In classical methodology, there are a number of algorithms for clustering, association rule mining, visualisation and classification to get meaningful information for predictive analysis. Nowadays, a number of tools and technologies are available for the implementation of data mining and machine learning including WEKA, Tanagra, Orange, ELKI, KNIME, RapidMiner, R and many others which have Java, Python or C for back-end programming and customisation.

That's where artificial intelligence (AI) solutions like AppZen can really make a difference. AI improves compliance and cuts costs without losing any of a company's operational efficiency. By adopting "Natural Language Processing" (NLP) technology, AI understands and interprets the human language embedded in written text and can process reams of internal paper documents and electronic records - and scour enormous volumes of external data like laws and historical trends - in seconds. In a nutshell, a robotic auditor is capable of successfully detecting patterns and problems in everything from contracts to expense reports.

The most frequent criticism was summed up by a woman who wrote: "You do not understand the'staying power' that the two major parties have in elections. They are not going to let an outsider into their club. A man put it this way: "They can wait out the Tea Parties and the crazies. Mavericks can't get a major party nomination." No matter who wins in November, I contend that the moderates in both parties will rise again, if only because the extremists and the folks on the fringes are not very good at governing.) As I wrote in 2011, "this is one of those times when fewer and fewer Americans believe that good politicians exist.