There's an arms race among public cloud providers to provide businesses with the best machine learning capabilities. Enterprises are increasingly interested in creating intelligent applications, and companies like Amazon, Microsoft and Google are rushing to help meet their needs. Google fired its latest salvo on Tuesday, announcing a set of enhancements to its existing suite of cloud machine-learning capabilities. The first was a new Jobs API aimed at helping match job applicants with the right openings. In addition, the company is slashing the prices on its Cloud Vision API and launching an enhanced version of its translation API.

Microsoft said Tuesday that a forthcoming Azure cloud service will help developers build and deploy bots or chatbots easily. Bots, a hot, much-hyped topic of late, are pieces of software that work under the covers to let consumers perform tasks, such as ordering pizza, using their favorite chat or texting app. Microsoft's Azure Bot Service, now in preview, builds on the company's much touted Bot Framework, which aims to support all the popular chat and texting applications in the universe. "This is a full application, a managed platform that does all you need to host a bot," Microsoft executive vice president Scott Guthrie told Fortune. The service relies on Azure Functions, which like the Lambda service from Microsoft msft rival Amazon Web Services, lets developers quickly build in capabilities that are triggered by a user action or some sort of software trigger or event.

The U.S. State Department generates some two billion e-mails every year. A significant fraction of these contain sensitive or secret information and so have to be classified, a process that is time-consuming and costly. In 2015 alone, it spent $16 billion to protect classified information. But the reliability of this process of classification is unclear. Nobody knows whether the rules for classifying information are applied consistently and reliably.

REDWOOD CITY, CA - November 14, 2016-- Numerous proposals have been offered for how intelligent machines might learn sequences of patterns, which is believed to be an essential component of any intelligent system. Researchers at Numenta Inc. have published a new study, "Continuous Online Sequence Learning with an Unsupervised Neural Network Model," which compares their biologically-derived HTM sequence memory to traditional machine learning algorithms. The paper has been published in MIT Press Journal's Neural Computation 28, 2474-2504 (2016). You can read and download the paper here. Authored by Numenta researchers Yuwei Cui, Subutai Ahmad, and Jeff Hawkins, the new paper serves as a companion piece to Numenta's breakthrough research offered in "Why Neurons Have Thousands of Synapses, A Theory of Sequence Memory in Neocortex," which appeared in Frontiers in Neural Circuits, in March 2016.

Alphabet's Google announced the formation of an artificial intelligence group for Google Cloud, the tech company's latest gambit to increase its market share in the lucrative cloud computing business. Diane Greene, who leads Google's cloud business, announced the team at an event at the company's facilities in San Francisco. The group will be led by Fei-Fei Li, an artificial intelligence professor at Stanford University, and researcher Jia Li. "What really attracted these two people to come and be in Google Cloud is a chance to democratize machine learning and artificial intelligence," Greene said.

Harry Shum (left), Microsoft AI and research group executive vice president, and Sam Altman, co-chair of OpenAI, will be working together on artificial intelligence. Microsoft has formed a partnership with OpenAI, an Elon Musk-based company, to research artificial intelligence. The two companies will focusing on "making significant contributions to advance the field of AI" and will work on their "mutual goal of using AI to tackle some of the world's most challenging problems," Microsoft said Tuesday in a blog post. Microsoft add that it is "committed to democratizing AI and making it accessible to everyone." AI is one of the hottest trends in tech right now, fueled by powerful chips, fast networks and the massive trail of data we all leave behind us as we go about our digital days.

There are over 34,000 scholarly, peer-reviewed journals in existence today, collectively publishing some 2.5 million articles every year. It's estimated that a single researcher, depending on their discipline, will read about 270 of them in the same time frame. Scientists will never keep up. They're going to miss key insights. Fortunately, the Allen Institute for Artificial Intelligence (AI2) tossed them a life preserver.

The only possible culmination of AI research is packing it neatly inside a synthetic body and having sex with it. Or, at least that's what some researchers think. By 2050, sex with robots is predicted to become so commonplace that it'll overtake human on human intercourse. According to one expert, we'll all be okay with that because robot sex will be'mind blowing.' But will these robots replace the desire to have sex with, you know, other humans?

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Survival: "Our entire existence is based on having the best detection mechanism possible," says Valerie Bannert-Thurner at Nasdaq. Certain things make Valerie Bannert-Thurner raise an eyebrow when looking for signs of bad behavior on the Nasdaq exchange. "I like the example of excessive cheering because the guys just can't help themselves but cheer," said Bannert-Thurner, who is senior vice president and head of risk and surveillance at Nasdaq. Another worrisome indicator is seemingly too-good-to-be-true trading profits. "If people are excessively profitable given how they trade and in comparison to everybody else trading the same instruments with similar styles, then we ask, is this luck or something else?" Bannert-Thurner said.