"The important thing is to understand what causes an engaged employee to become disengaged, and to focus action on reducing the rate this happens." Andrew Marritt (pictured right) is the founder of OrganizationView, a prominent people analytics firm based in Switzerland. He is also the creator of Workometry, a tool for capturing and understanding employee feedback. This technology uses machine learning techniques to gather and make sense of large volumes of employees' comments in real-time. In fact, the tool uses computational linguistics, a computer technique that identifies what employees talk about and makes sense of thousands of texts in different languages. Indeed, it has all the benefits that you would expect from a modern tool, such as the responsive design for the mobile age.

New parallel processing platforms in the growing big data ecosystem are enabling organizations to bring greater compute power to bear on analytical problems. And machine learning applications are likely to be among the leading uses for systems based on big data technologies such as Hadoop and Spark. They want to build complex machine learning models and run the models repeatedly to fine-tune the algorithms and improve the results -- and they want to do that work as quickly as possible so they can handle a greater number of analytical problems, according to presentations and discussions at the Strata Hadoop World 2015 conference held recently in San Jose, Calif. In this Talking Data podcast, SearchDataManagement's Jack Vaughan, who covered the conference, tells colleague Ed Burns that people are coming to machine-learning applications from a couple different points of view. One group includes data analysts and programmers at e-commerce websites who want to serve up recommendations to visitors. Another includes enterprise statisticians who have been immersed in the technology for years but haven't had the processing power needed to move beyond relatively simple models.

AI is one of those technologies whose promise is resurrected periodically, but only slowly advances into the real world. I remember the dog-and-pony AI shows at IBM, MIT, Carnie-Melon, Thinking Machines, and the like in the mid-1980s, as well as the technohippie proponents like Jaron Lanier who often graced the covers of the era's gee-whiz magazine like "Omni." AI is an area where much of the science is well established, but the implementation is still quite immature. It's not that the emperor has no clothes -- rather, the emperor is only now wearing underwear. There's a lot more dressing to be done.

Amazon has three big pillars: the retail marketplace, Amazon Prime, and Amazon Web Services. But there certainly would be room for a fourth pillar. It's possible that Amazon Studios, which is producing original video content for Prime Video, could be that fourth pillar, but it's also possible that the Alexa voice assistant, which is packaged inside of the Echo speaker, could end up being the fourth pillar, Amazon founder and CEO Jeff Bezos told Recode's Walt Mossberg today at Recode's Code Conference in Rancho Palos Verdes, California. Google revealed its own Echo competitor earlier this month, and Apple is also working on an answer to the Echo. But Bezos does not seem to be worried about that.

Cogito's technology uses real-time feedback to better facilitate and streamline calls MIT technology offshoot Cogito has developed a potential solution to the cumbersome customer service call center process, via a voice-analytics software that can provide real-time feedback to make the conversations more effective. The software, cultivated through years of behavioral research, relies on the voice patterns of consumers and agents to determine its recommendations. Cogito has a history of using similar technology to track mental health, and has also partnered with the U.S. Department of Veterans Affairs to monitor post-traumatic stress disorder (PTSD) in returning soldiers. By venturing into the call center space, the company aims to "make millions of call center workers happier and more productive."

A student in Ashok Goel's class last semester had a question: How long could the computer programs, or "agents," they were building take to solve problems? Since it was an online course, the student posted the question to the group discussion board. One teaching assistant replied, pointing to a portion of the assignment that set a 15 minute limit. The student clarified that their agent was running a little slow, and could take a bit longer. "It's fine if your agent takes a few minutes to run," she wrote.

While Musk's description of an injectable human-computer link may sound like science fiction, top tech executives repeatedly said that artificial intelligence (AI) was on the verge of changing everyday life, during discussion at a conference by online publication Recode this week. It is no secret that tech companies are diving into AI analytics research, an industry that will grow to 70 billion by 2020 from just 8.2 billion in 2013, according to a Bank of America report citing IDC research. AI, which combs through large troves of raw data to predict outcomes and recognize patterns, is already used in web search systems, marketing recommendation functions and security and financial trading programs. The technology will spread to driverless cars and service robots in the future, the Bank of America report said. Sundar Pichai, chief executive of Alphabet Inc's Google, said he sees a "huge opportunity" in AI.

IBM is busy reshaping itself for the future, moving out of commodity hardware and chip manufacturing and further into higher end, value-added services. At the heart of the new strategy is the artificial intelligence machine Watson, around which IBM now intends to build a business in cognitive computing. The vision of the 105-year-old company is that Watson works in tandem with users, doing the heavy-lifting analytics, but ceding the judgement to humans. In particular, it wants to help make sense of the data now pouring out of the Internet of Things (IoT). As part of the remodelling, the IBM is making some large investments in Europe, in areas including cloud computing, artificial intelligence and data analytics.

HONG KONG--Chinese search-engine giant Baidu Inc. Senior Vice President Wang Jing said Friday that the company plans to mass produce a driverless car in five years--so that babies born today won't need a driver's license. Baidu, which is China's largest search-company with 80% market share, is already testing its model on public roads in Beijing and in Wuhu, in China's southeastern Anhui province, and in a closed testing area in Shanghai. Speaking at The Wall Street Journal's Converge technology conference, Mr. Wang said...

HONG KONG--The biggest challenges for Chinese companies making the next generation of wearables, self-driving cars and drones is having experts in cross disciplines, GGV Capital Managing Partner Jenny Lee said Friday. Speaking at the Converge technology conference hosted by The Wall Street Journal and f.ounders in Hong Kong, Ms. Lee said Chinese companies benefit from having government support and funding, and a huge market of...