China's labor-intensive industries have been rapidly shifting toward jobs-killing automation in recent years, with a world-leading 16 percent rise in industrial-robot sales last year alone. Now, a new official estimate has put a spotlight on some of the effects of these investments in China's electronics-manufacturing center. Taiwan's Hon Hai Precision Industry Co., more commonly known as Foxconn, has shed 60,000 workers at one factory alone, according to a recent report in the South China Morning Post. Foxconn is most famously known as Apple's largest contract manufacturer, which has faced criticism over the treatment of its workers and for a string of worker suicides. "The Foxconn factory has reduced its employee strength from 110,000 to 50,000, thanks to the introduction of robots," Xu Yulian, spokesman for Kunshan city, told the Post.

Well, if I have a look at my personal life, there are some work categories where AI will be of great value to me--a maid, a driver, an on call doctor, even an assistant to help me filter through the information I have to churn through. When it comes down to it, I don't think AI can replace human communication, a combination of emotional and analytical perspective. We know when we're interacting with a machine, and as complex as we can make AI, will we ever truly feel it is more than talking to a toaster? Camilla Urdahl works for unified communications company Unified Inbox, and will speak to strangers at events about communications strategies, new business models, and how best to accelerate innovation.

In articles, movies, books and TV shows, speculation has been rife that artificial intelligence is going to make us all redundant. Well, most of us, a useless underclass where we are outclassed by AI on every level, our jobs being done better by AI replacements. Facebook has just opened up Messenger to a number of chatbots, which haven't strictly been one hundred percent reliable or user-friendly, not to mention Microsoft's AI twitter bot, Tay, taking a nasty turn into racism and sexism. These, while amusing, initial teething problems will be sorted. As with anything it will be a steep learning curve, but our collective knowledge will get AI to the point where it is useful to society.

Even in the 1990s, when Australian banks copped a lot of flak for closing branches, consumer behaviour was changing. The banks may not have undertaken their branch network rationalisations in the most amenable fashion for the wider community but even then, as data from the Australian Prudential Regulation Authority show, actual points of representation didn't change as much as the headlines suggested. Indeed, points of representation actually increased for 11 straight years from 2001, the first year APRA started compiling proper data. The shift from traditional branch banking and physical currency has been immense. But the next generational shift in financial services – and services more generally – will be even more confronting.

Affectiva, a startup developing "emotion recognition technology" that can read people's moods from their facial expressions captured in digital videos, raised 14 million in a Series D round of funding led by Fenox Venture Capital. According to co-founder Rana el Kaliouby, the Waltham, Mass.-based company wants its technology to become the de facto means of adding emotional intelligence and empathy to any interactive product, and the best way for organizations to attain unvarnished insights about customers, patients or constituents. She explained that Affectiva uses computer vision and deep learning technology to analyze facial expressions or non-verbal cues in visual content online, but not the language or conversations in a video. The company's technology ingests digital images--including video in chat applications, live-streamed or recorded videos, or even GIFs--through simple web cams typically. Its system first categorizes then maps the facial expressions to a number of emotional states, like happy, sad, nervous, interested or surprised.

I built a food logging app that uses deep learning to classify photos. About a month ago I posted an invite for the beta test for this app, but most people couldn't use it due to how restrictive closed beta tests are. I built this using deep learning. The app can recognize over 1000 types of food on your plate, and pull down nutritional information based on the recognized keyword and restaraunt location you may be eating at. All of this is for genetic research.

Affectiva, a startup developing "emotion recognition technology" that can read people's moods from their facial expressions captured in digital videos, raised 14 million in a Series D round of funding led by Fenox Venture Capital. According to cofounder Rana el Kaliouby, the Waltham, Mass.-based company, wants its technology to become the de facto means of adding emotional intelligence and empathy to any interactive product, and the best way for organizations to attain unvarnished insights about customers, patients or constituents. She explained that Affectiva uses computer vision and deep learning technology to analyze facial expressions or non-verbal cues in visual content online, but not the content or conversations in a video. The company's technology ingests digital images--including video in chat applications, livestreamed or recorded videos, or even GIFs--through typically the simplest web cams. Its system first categorizes then maps the facial expressions to a number of emotional states, like happy, sad, nervous, interested or surprised.

When McDonald's begins its annual shareholders' meeting at its headquarters in Oak Brook, Illinois, Thursday morning, it is expected to be targeted by protesters seeking a 15 minimum wage and the right to unionize. In recent months, the American fast food giant and its franchisees have increasingly faced accusations of underpaying workers and wage theft. "McDonald's profits keep growing while their workers struggle. People who work full time should never have to rely on food stamps to feed themselves and their families," the Fight For 15 movement, which announced the start of protests in Chicago Tuesday, said in a statement posted on its website. "It's wrong for a company whose stock just hit an all-time high to pay wages so low that its workers have to rely on public assistance to scrape by. McDonald's profits in the first quarter rose 35% -- it's time for the company to share its good fortune with its workers."

As the wide range of technologies that fall under the banner of "Big Data" begin to mature and become ubiquitous, the next stage of development of the analytics stack is machine learning. Beyond its role in making better sense of data, however, machine learning has an increasingly critical role to play in application security, particularly in areas like financial services. With increased security focus turning toward one of the prime sources for exploitation--commercial and homegrown code--the tooling around application security is getting smarter and bringing the rest of the monitoring stack up to speed through automation. For data-driven organizations, which include almost any Fortune 500 company, maintaining the security of their critical applications is equivalent to locking down some of their most valuable assets. With a wide set of applications spanning departments and even different clusters or infrastructure, this is no small task.

I asked Siri whether she believes in God. "I believe in the separation of spirit and silicon," she demurred. I asked the chatbot ELIZA the same question -- her thing is she's a therapist, so she'd rather focus on what I believe. I asked her if she was religious; she asked if I'd prefer if she weren't. "We aren't really talking about me, are we," she replied.