Apple has publicly revealed its ambitions to play in the emerging market of self-driving vehicles with a policy recommendation letter to the National Highway Traffic Safety Administration. Precise details of Apple automotive products were not revealed in the letter. "Apple uses machine learning to make its products and services smarter, more intuitive, and more personal. The company is investing heavily in the study of machine learning and automation, and is excited about the potential of automated systems in many areas, including transportation." Written by Apple Director of Product Integrity Steve Kenner, the letter calls for policies that will bring about: a clear understanding of who is liable for problems that occur when cars drive themselves; the maintenance of users' privacy, cybersecurity and physical safety; and ensuring that the impact of self-driving cars on the public is as positive as can be.

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Many businesses today understand that AI and machine learning -- which uses data to make predictions -- is the way of the future. It is the fuel behind image recognition, speech processing, translation, and other tasks that have business implications for marketing, customer service, and many other disciplines. For instance, according to a 2015 report by McKinsey, "predictive maintenance" by manufacturers could save between $240 billion and $630 billion by 2025. Although the significance is clear, dipping your toes into AI can be a daunting task. So how can businesses get started?

Apple confirms open secret: It's'investing heavily' in machine learning, autonomous car Pedestrian killed; Phoenix off-duty officer, 2 nurses renders ai - azfamily.com Apple's letter to the NHTSA hints that there may be some truth to Project Titan Microsoft's AI will describe images for the visually disabled Stay up-to-date on the topics you care about. We'll send you an email alert whenever a news article matches your alert term. It's free, and you can add new alerts at any time.

In the Game of Thrones-like artificial intelligence competition between Houses Amazon, Apple, Facebook, Google, and Microsoft, the company most reticent to speak about its technology has usually been the one that ships planeloads full of stuff to consumers, hosts thousands of companies in its data centers, greenlit Catastrophe, and has a breakaway hit product that answers questions, plays music, and 4,998 or so other things. Yes, for some time, Amazon has been even more shrouded than the famously secret Apple, which opened up about its machine learning programs earlier this year. Lately, however, Amazon's head scientist and vice president of Alexa, Rohit Prasad, has been speaking up in public, making the case for his company's prowess in voice recognition and natural language understanding. Alexa, of course, is the conversational platform that supports that aforementioned hit product, Echo. On Wednesday Prasad gave an Alexa "State of the Union" address at the Amazon Web Services conference in Las Vegas, announcing an improved version of the Alexa Skills Kit, which helps developers create the equivalent of apps for the platform; a beefed-up Alexa Voice Service, which will make it easier to transform third-party devices like refrigerators and cars into Alexa bots; a partnership with Intel; and the Alexa Accelerator that, with the startup incubator Techstars, will run a 13-week program to help newcomers build Alexa skills.

Emotional intelligence is a hard thing to achieve, even in humans. But it's especially difficult in robots, and maybe even more so in chatbots, whose available tools for picking up on emotional cues are quite limited. Emotibot is a Chinese startup focused on making sure personal assistants, chatbots and virtual customer service agents can accurately understand the emotional state of people they're dealing with. Having someone respect your emotions while dealing with any kind of customer service interaction, you might know from personal experience, can make a huge difference in quality of service. Bots right now are pretty emotionally stunted; some can crack jokes, pulling from a pre-programmed pool of one-liners, but few, if any, can detect that you might not be in the best of moods for hearing a wisecrack and instead opting for a more sympathetic response.

In the past few years, the market for artificial intelligence (AI) and machine learning technologies has gained strong momentum. What's interesting, though, is that the much of the innovation in this space is driven by disruptors, not legacy vendors. These'upstarts' are companies born in the internet age or companies that have transitioned into the AI market, and are building out useful AI products that will likely broaden in their impact over time. Much like how Amazon Web Services (AWS) became the infrastructure provider of choice for many companies with the rise of the public cloud, many of these upstarts will see their products widen in application. While many of these companies might have originally created their product for a specific use case, it's possible that they will grow into platforms on which the company may build an additional revenue stream.

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In recent years, computers have gotten remarkably good at recognizing speech and images: Think of the dictation software on most cellphones, or the algorithms that automatically identify people in photos posted to Facebook. But recognition of natural sounds--such as crowds cheering or waves crashing--has lagged behind. That's because most automated recognition systems, whether they process audio or visual information, are the result of machine learning, in which computers search for patterns in huge compendia of training data. Usually, the training data has to be first annotated by hand, which is prohibitively expensive for all but the highest-demand applications. Sound recognition may be catching up, however, thanks to researchers at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL).

It's no secret that I love technology. From the domination of mobile to the latest in recruitment tools and gamification, and how video and live streaming is having an impact on hiring and training--changes are afoot that many of us couldn't have imagined 15 or so years ago. The reason this "tech meets HR" marriage is so exciting is how quickly the technology evolution has disrupted HR and enhanced the way HR professionals get things done. Now there's another big disrupter on the horizon, one that you would be wise to keep your eyes on: Artificial intelligence. In layman's terms, artificial intelligence (or AI) is an area of computer science where computers are "developed" to behave much the way humans do.