Amid concerns that robots will replace human workers at an increasingly rapid pace thanks to artificial intelligence, Microsoft's new initiative aims to fund start-ups that build AI that has a positive impact on society. To qualify, the companies must be "designed to assist humanity; be transparent; maximize efficiency without destroying human dignity; provide intelligent privacy and accountability for the unexpected; and be guarded against biases," Microsoft said in a statement. The investment expands Microsoft's start-up investing, which had previously focused on cloud companies. It comes at a time when rivals like Google, Apple and Amazon have accelerated their efforts in artificial intelligence. Of course, not all aspects of artificial intelligence have been well received by tech leaders, many of whom signed an open letter calling for AI systems that are "robust and beneficial [to society]."

Netflix employs an algorithm that helps its users discover movie options, and now it's about to help discover new planetary systems. Researchers at the University of Toronto Scarborough have developed a new approach to identifying stable planetary systems based on the machine learning artificial intelligence Netflix uses. "Machine learning offers a powerful way to tackle a problem in astrophysics, and that's predicting whether planetary systems are stable," Dan Tamayo, lead author of the research and a postdoctoral fellow in the Center for Planetary Science at the University of Toronto Scarborough, said in a press release. Machine learning is a type of artificial intelligence that allows computers to learn new functions without being programmed. This is how Netflix can make scarily accurate predictions of what you're interested in watching without you telling it.

There is quite a lot of confusion about the differences between machine learning, cognitive computing and artificial intelligence. Is there an easy distinction? Josefin Rosén (JR): I think the easiest way of thinking about it is that machine learning is basically a subfield of artificial intelligence. Then you can think of cognitive computing as artificial intelligence plus elements of natural language processing. So cognitive computing understands input like text, voice and video, and it can reason and create outputs that can be used and consumed by humans, not just computers.

Artificial Intelligence is becoming a game for the big dogs. To succeed in genuine artificial intelligence efforts, beyond trivial prediction, you need three things. AI is emerging, so you need to be able to recruit and attract a sufficient core of people and create the culture that allows them to explore. You also need mechanisms to exploit their progress commercially. The second is training environments, which include training data but also systems which let you train and test your systems.

'Tis the season for the public relations exercise known as "here's what we think (or hope) will happen in the tech sector next year," flooding my inbox with predictions for 2017. No one knows what will happen tomorrow, let alone over the next 12 months, but the exercise yields interesting insights into what's hot (and what's not) in technology today. Artificial intelligence (and machine/deep learning) is the hottest trend, eclipsing, but building on, the accumulated hype for the previous "new big thing," big data. The new catalyst for the data explosion is the Internet of Things, bringing with it new cybersecurity vulnerabilities. The rapid fluctuations in the relative temperature of these trends also create new dislocations and opportunities in the tech job market.

Artificial intelligence is learning to take on an increasing number of sophisticated tasks. Google Deepmind's AI is now able to imitate human speech, and just this past August IBM's Watson successfully diagnosed a rare case of leukemia. Rather than viewing these advances as threats to job security, we can look at them as opportunities for AI to fill in critical gaps in existing service providers, such as mental healthcare professionals. In the US alone, nearly eight percent of the population suffers from depression (that's about one in every 13 American adults), and yet about 45 percent of this population does not seek professional care due to the costs. There are many barriers to getting quality mental healthcare, from searching for a provider who's within your insurance network to screening multiple potential therapists in order to find someone you feel comfortable speaking with.

Digital (and in our case search and content) data holds the keys to marketing success. It contains the critical patterns on consumer intent and behavior, preferences, and content/topics that brands need to provide customers with that critically personal, one-to-one experience that people today want to see. The problem, however, is that the human brain is only capable of processing 1m gigabytes of memory. In other words, the amount of information available far exceeds the processing ability of humans. The term'Big data'- although often overused and misunderstood – is the science that drives the art of content marketing creation and engagement.

Microsoft Corp.'s venture arm started an artificial intelligence-focused fund, kicking it off with an investment in a startup by a luminary in the field. Element AI, a Montreal-based research lab started by Yoshua Bengio and others, will get an undisclosed amount from Microsoft Ventures, Redmond, Washington-based Microsoft said in a statement Monday. The size of the fund, which will back AI companies, wasn't disclosed. "The kinds of companies in this fund will help people and machines work together to increase access to education, teach new skills and create jobs, enhance the capabilities of existing workforces and improve the treatment of diseases, to name just a few examples," Nagraj Kashyap, who heads Microsoft Ventures, wrote in a blog post. Element AI helps develop and release technologies in partnerships with large companies and research institutions.

Microsoft Ventures today announced two steps that point to how the tech giant's VC arm wants to get involved in artificial intelligence in a big way. First, it's now going to pursue investments in AI startups through a special fund dedicated to AI startups that focus on "inclusive growth and positive impact on society." Second, it is the first announced backer for Element AI, a new incubator out of Montreal co-founded by "the godfather of machine learning" Yoshua Bengio, which is dedicated to the space. As with its news in May first announcing Microsoft Ventures and its initial focus on cloud-based startups, the VC firm is not specifying just how much money it intends to invest in artificial intelligence, or in Element AI specifically. Element AI is not the only AI investment that Microsoft Ventures is making public today: it's also part of a $15 million round for Tact, a CRM startup.

By far the fastest expanding frontier of data science is AI and specifically the rapid advances in Deep Learning. Advances in Deep Learning have been dependent on artificial neural nets and especially Convolutional Neural Nets (CNNs). In fact our use of the word "deep" in Deep Learning refers to the fact that CNNs have large numbers of hidden layers. Microsoft recently won the annual ImageNet competition with a CNN comprised of 152 layers. Compare that with the 2, 3, or 4 hidden layers that are still typical when we use ordinary back-prop NNs for traditional predictive analytic problems. First, CNNs have come close to achieving 100% efficiency for image, speech, and text recognition.