As artificial intelligence software has grown in prominence in recent months, one fear has flowed beneath the surface of many discussions: What will the technology's effect be on jobs? In some cases, AI applications are being designed to automate specific jobs, like that of customer service agents. More broadly, some commentators have suggested the technology could become general enough to perform most tasks currently being performed by workers, whether blue collar or white collar. But Matt Gould, founder and chief strategy officer at Arria NLG, a software company that uses a flavor of AI to produce business reports in natural language, says we have nothing to fear from the coming artificially intelligent future. In this interview, he explains why workers stand to gain far more than they may lose as more and more enterprises adopt AI applications.

In Singapore, the Fullerton Health Group has increased its quality of care and reduced costs with the help of machine learning and a partnership with Microsoft. Real-time medical data helps Fullerton's health care providers give the best course of action for patients. And operational analytics and machine learning power a program that helps patients and providers manage chronic diseases. Watch the video to learn more and go to the Microsoft Enterprise blog.

Before we discuss it in the context of marketing automation, let us define ALAMO – it is the All-important Leading-edge Analytics-based MIPS mOdel. The acronym MIPS refers to the four-step process in marketing automation: Measurement – Inference – Prediction – Steering. In a previous article "The K.I.S.S. Principle in Marketing Analytics – Keep It Simple and Smart", we listed some of the major benefits of marketing automation to businesses who use it. It has its ups and its downs (which are all good): the ups include increased revenues, leads, conversions, sales, and accuracy of multi-channel attributions; and downs include reduced marketing overhead. Those are outcomes that any CMO would love.

When a sleepy Marc Dubois walked into the cockpit of his own aeroplane, he was confronted with a scene of confusion. The plane was shaking so violently that it was hard to read the instruments. An alarm was alternating between a chirruping trill and an automated voice: "STALL STALL STALL." His junior co-pilots were at the controls. In a calm tone, Captain Dubois asked: "What's happening?" Co-pilot David Robert's answer was less calm. "We completely lost control of the aeroplane, and we don't understand anything! The crew were, in fact, in control of the aeroplane. One simple course of action could have ended the crisis they were facing, and they had not tried it. But David Robert was right on one count: he didn't understand what was happening. As William Langewiesche, a writer and professional pilot, described in an article for Vanity Fair in October 2014, Air France Flight 447 had begun straightforwardly enough – an on-time take-off from Rio de Janeiro at 7.29pm on 31 May 2009, bound ...

Satalia is an optimisation company founded in 2007 by Dr Daniel Hulme. We solve hard problems using data science, optimisation and artificial intelligence, and were named a 2016 Gartner Cool Vendor. Our purpose is to enable everyone to do the work they love. By sharing the journey that we're on to understand ourselves and realise our purpose, we hope to inspire others in the AI sphere to be proactive in considering their relationship with society. Satalia was birthed during a period of relative calm for the Artificial Intelligence (AI) ecosystem.

If you've seen one Atari game you've seen them all, or at least once you've seen enough of them anyway. When we (humans) learn, we don't start from scratch with every new task or experience, instead we're able to build on what we already know. And not just for one new task, but the accumulated knowledge across a whole series of experiences is applied to each new task. Nor do we suddenly forget everything we knew before – just because you learn to drive (for example), that doesn't mean you suddenly become worse at playing chess. But neural networks don't work like we do.

The tech giant's AI software is named after Albert Einstein. Last week, Salesforce CEO Marc Benioff touted a vision of the future in which everything and everyone will be connected and driven by machine learning and data. Benioff was launching his company's foray into artificial intelligence last week in front of 170,000 people at its annual Dreamforce conference in San Francisco. While the future-looking technology has been in the works for years and was built by hundreds of data scientists, Salesforce's AI tool actually takes a branding lesson from the past--specifically, from Albert Einstein. Salesforce unveiled Einstein in September and at Dreamforce explained how it works.

We've been hearing all artificial intelligence, all the time from the Customer Relationship Management (CRM) industry over the last several weeks. Microsoft is the latest to trumpet its AI capabilities for sales people with the general availability of Dynamics 365 coming on November 1st. Microsoft announced last summer that it was going to be combining its ERP and CRM into a unified solution, and this is the culmination of that announcement. Like many large organizations, Microsoft tends to deliver the news in waves -- it's coming, it's in beta, it's here. While the news smacks of "look at me too," Microsoft points out it has been working on AI long before its biggest competitors like Salesforce and Oracle, which recently announced their own AI capabilities at their respective customer customer conferences, Dreamforce and Oracle Open World. Microsoft has built in a couple of intelligence features into the release designed specifically for sales and service personnel.

AI today is a buzzword in technology that has everyone sitting up to pay attention. With every other billboard in the Bay area talking about AI and machine learning, it appears like the time of Jarvis from Iron Man, Samantha from'Her' and even the creepy'HAL' from 2001 – a space odyssey is fast approaching. This idea always presents itself with a bit of fear. Are machines going to take over? Are we going to lose our jobs?

They didn't know it, but the early humans who created the first stone axes and hammers started the incredibly fast-paced technological cycle we're living in today. Their primitive tools were used to create other, better tools, which were used to make even better tools. This cycle progressed relatively slowly for thousands of years -- leaving humans time to acclimate to the effect technology had on our daily lives. Today, technology changes so fast we can barely see what's 6–12 months ahead. Already, autonomous cars are driving on the road, money automatically moves between accounts as needed, homes autonomously control their climate while we're away.