With great power comes great responsibility--and artificial-intelligence technology is getting much more powerful. Companies in the vanguard of developing and deploying machine learning and AI are now starting to talk openly about ethical challenges raised by their increasingly smart creations. "We're here at an inflection point for AI," said Eric Horvitz, managing director of Microsoft Research, at MIT Technology Review's EmTech conference this week. "We have an ethical imperative to harness AI to protect and preserve over time." Horvitz spoke alongside researchers from IBM and Google pondering similar issues.

Machine learning couldn't be hotter. A type of artificial intelligence that enables computers to learn to perform tasks and make predictions without explicit programming, machine learning has caught fire among the hip tech set, but remains a somewhat futuristic concept for most enterprises. But thanks to technological advances and emerging frameworks, machine learning may soon hit the mainstream. Consulting firm Deloitte expects to see a big increase in the use and adoption of machine learning in the coming year. This is in large part because the technology is becoming much more pervasive.

America's manufacturing heyday is gone, and so are millions of jobs, lost to modernization. Despite what Treasury Secretary Steven Mnuchin might think, the National Bureau of Economic Research and Silicon Valley executives, among many others, know it's already happening. And a new report from PwC estimates that 38% of American jobs are at "high risk" of being replaced by technology within the next 15 years. But how soon automation will replace workers isn't the real problem. The real threat to American jobs will come if China does it first.

Bots are popping up everywhere from Facebook to home personal assistants. Advances in natural language processing, machine learning and other AI technology created the foundation for bots, but the field has a long way to go before it reaches its full potential. The Alexas and Cortanas of the world do an effective job at accomplishing requested tasks as long as people present them one at a time. A multi-threaded version of these digital personal assistants would allow them to remember multiple situations. This use case is closer to how people actually want to engage with the bots.

With great power comes great responsibility--and artificial-intelligence technology is getting much more powerful. Companies in the vanguard of developing and deploying machine learning and AI are now starting to talk openly about ethical challenges raised by their increasingly smart creations. "We're here at an inflection point for AI," said Eric Horvitz, managing director of Microsoft Research, at MIT Technology Review's EmTech conference this week. "We have an ethical imperative to harness AI to protect and preserve over time." Horvitz spoke alongside researchers from IBM and Google pondering similar issues.

Many people wish they could predict what will happen next in the world. Many predictions are assigned to the waste bin of time very quickly. With hindsight, unforeseen factors come into play that changed their'models'. It is because there were so many factors involved to predict. The ability of models to analyse and interpret means technology was not able to process, analyse and predict with a high degree of success.

Ring founder Jamie Siminoff tells Jefferson Graham how his video doorbell and companion products spook burglars and help curb crime, on #TalkingTech. The video doorbell, out since 2013, has expanded into a suite of products that also include new motion detection lights with companion camera (new), a standalone security camera and chimes to bring traditional audio to the doorbell. The added inventory helped push the company to sales that more than doubled in 2016. Ring founder and chief inventor Jamie Siminoff has positioned the company as a tech Batman, a product that can help keep the burglars away. The Ring doorbell connects to Wi-fi, and when it's rung, you get a notification on your phone that allows you to see who's out there, and say "Who's at the door?" from inside the house, at work, or even on vacation.

Facebook's deep-learning artificial intelligence systems have learned to recognize your friends in your photos, and Google's AI has learned to anticipate what you'll be searching for. But there's no need to feel left out, even if your company's computers haven't learned much lately. A growing number of tech giants and startups have begun offering machine learning as a cloud service. That means other companies and startups do not need to develop their own specialized hardware or software to apply deep learning--the high-powered version du jour of machine learning--to their specific business needs. "Deep-learning algorithms dominate other machine-learning methods when data sets are large," says Zachary Chase Lipton, a deep-learning researcher in the Artificial Intelligence Group at the University of California, San Diego, who has examined cloud AI services from companies such as Amazon and IBM.

Amazon is a company that has gone from being an innovative online book retailer, to one of the largest ecommerce retailers in the world, and is now the largest cloud computing provider and a major player in IoT.In addition to their core ecommerce website, Amazon has a line of internet connected ebook readers, personal tablets, a smartphone, a smart TV device, and now their latest, an intellig Their new product is the Echo. It's a small, relatively discreet IoT connected speaker that works in much the same way as Apple's Siri, Microsoft's Cortana, and Google's Now services. Are there enough compelling features with the Echo to make it a breakthrough device in IoT mass adoption? More importantly, are there risks with having an always on, always listening, IoT device in the home? Although IoT devices around the world have now exceeded 5 billion, there are still billions of consumers that haven't seen the value, or even recognized the potential of a more connected home.

America's manufacturing heyday is gone, and so are millions of jobs, lost to modernization. Despite what Treasury Secretary Steven Mnuchin might think, the National Bureau of Economic Research and Silicon Valley executives, among many others, know it's already happening. And a new report from PwC estimates that 38 percent of American jobs are at "high risk" of being replaced by technology within the next 15 years. But how soon automation will replace workers is not the real problem. The real threat to American jobs will come if China does it first.