Determining the value of some of that old gear taking up space in your closet or garage might become a lot easier if you have a Google Home. In an onstage demo at Google Cloud Next, eBay chief product officer RJ Pittman showed how the online auctioneer might tie into Google's digital assistant. He started in by asking the bot if eBay could find the value of his Canon digital camera. You can ask me what something is worth," the bot introduced itself. The chatbot asked a couple of follow-up questions, including the model of the camera (it was an EOS 5D), if it was new, and its overall condition.

The concept of machine learning has been around for decades, primarily in academia. Along the way it has taken various forms and adopted various terminologies, including pattern recognition, artificial intelligence, knowledge management, computational statistics, etc. Regardless of terminology, machine learning enables computers to learn on their own without being explicitly programmed for specific tasks. Through the use of algorithms, computers are able to read sample input data, build models and make predictions and decisions based on new data. This concept is particularly powerful when the set of input data is highly variable and static programming instructions cannot handle such scenarios. In recent years, the proliferation of digital information through social media, the Internet of Things (IoT) and e-commerce, combined with accessibility to economical compute power, has enabled machine learning to move into the mainstream.

As I think back about our research this last year, and all we have learned, I leave you with one simple message. All the changes we discuss are no longer "interesting" or "informative" – they have become real, and essential mandates for the future. We decided to call them "rules" because we believe they are now clear, and we want you to understand them so you can experience greater levels of productivity, performance, and employee excitement in your company. As always we look forward to explaining the Global Human Capital Trends to you in person this year, and hope to hear your comments and feedback as we all learn how to build the thriving organizations of the future.

We envision that algorithm such as ours could improve the efficiency and consistency of pathologists,

Artificial Intelligence is among the hottest topics in the financial markets today, seeming to promise untold benefits to the major banks that are embracing it, and destruction to traditional asset managers and other victims who get left behind. The truth may be a little different. Indeed, Opimas does foresee myriad benefits coming to financial players in the future from the robots and machines that think and learn and analyse mountains of unorganized data, enabling firms to anticipate and better serve customers' needs. We estimate a 28% improvement in financial institutions' cost-to-income ratio by 2025 as they automate routine processes currently performed by employees. In 2017, we expect financial firms to spend more than US$1.5 billion on AI-related technologies and, by 2021, US$2.8 billion, representing an increase of 75%.

Technology must be controlled in order to safeguard the future of humanity, Stephen Hawking has warned. The physicist, who has spoken out about the dangers of artificial intelligence in the past, says a'world government' could be our only hope. He says our'logic and reason' could be the only way to defeat the growing threat of nuclear or biological war. We are living through the most dangerous time in the history of the human race, according to Professor Stephen Hawking. 'Since civilisation began, aggression has been useful inasmuch as it has definite survival advantages,' he told The Times. 'It is hard-wired into our genes by Darwinian evolution. 'Now, however, technology has advanced at such a pace that this aggression may destroy us all by nuclear or biological war.

Facebook on Wednesday rolled out some staggering statistics related to its social networks. Each day, users watch 100 million hours of video, 400 million people use Messenger, and more than 95 million photos and videos are posted on Instagram. That puts a heavy load on Facebook's servers in data centers, which help orchestrate all these services to ensure timely responses. In addition, Facebook's servers use machine learning technologies to improve services, with one visible example being image recognition. The story is similar for Microsoft, which is continually looking to balance the load on its servers. For example, Microsoft's data centers apply machine learning for natural language services like Cortana.

People are just now getting comfortable with the idea that data from many electronic gadgets they use flies up to the cloud. But going forward, much of that data will stick closer to Earth, processed in hardware that lives at the so-called edge--for example, inside security cameras or drones. That's why Nvidia, the processor company whose graphics processing units (GPUs) are powering much of the boom in deep learning, is now focused on the edge. Deepu Talla, vice president and general manager of the company's Tegra business unit, says bringing AI technology to the edge will make a new class of intelligent machines possible. "These devices will enable intelligent video analytics that keep our cities smarter and safer, new kinds of robots that optimize manufacturing, and new collaboration that makes long-distance work more efficient," he said in a statement.

What if your friend the robot could tell what you're thinking, without you saying a word? Researchers at MIT's Computer Science and Artificial Intelligence Lab and Boston University have created a system where humans can guide robots with their brainwaves. This may sound like a theory out of a sci-fi novel, but the goal of seamless human-robot interaction is the next major frontier for robotic research. For now, the MIT system can only handle simple binary activities such as correcting a robot as it sorts objects into two boxes, but CSAIL Director Daniela Rus sees a future where one day we could control robots in more natural ways, rather than having to program them for specific tasks -- like allowing a supervisor on a factory floor to control a robot without ever pushing a button. "Imagine you look at the robots, and at some point one robot is not doing the job correctly," Rus explained.

The Amazon Echo, a voice-controlled virtual assistant, is seen at its product launch for Britain and Germany in London, in 2016. After several months of pushback, Amazon has agreed to release user data from an Amazon Echo device involved in a high-profile Arkansas murder trial. The device, a popular, hands-free artificial intelligence assistant named "Alexa" that responds to human directives, contains audio recordings that prosecutors say could could provide information in the murder of Victor Collins, 47, who was found dead in his hot tub on Nov. 22, 2015, in Bentonville, Arkansas. James Bates, 31, was charged with first-degree murder and tampering with evidence in the case. Benton County Prosecuting Attorney Nathan Smith wrote in an email that prosecutors were "pleased" with Amazon's decision.