Machine learning is the next big thing, says Google with its acquisition of AI site Kaggle. It doesn't take artificial intelligence to know Google thinks machine learning will be central to your future. After all, the Silicon Valley powerhouse has been busy creating self-teaching tech that can translate languages, vamp with you on piano, and politely crush you at the ancient Chinese game of Go. "Over time, the computer itself -- whatever its form factor -- will be an intelligent assistant helping you through your day," Google CEO Sundar Pichai wrote in his first-ever letter to shareholders, last year. "We will move from mobile first to an AI first world." Now Google has taken another step toward that future.

She speaks with Bloomberg's Caroline Hyde on "Bloomberg Technology."

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.