The potential of this kind of connectedness opens a new range of use cases that will propel societies into a much more intelligent world, where devices tuned to environments and context and fueled by mega-processing and artificial intelligence (AI) will anticipate needs, self-heal problems, and much more. This design is pushing the storage, control, and compute toward the edge of the cloud, closer to end devices. Moving some of the processing to edge devices is a fundamental part of the 5G vision of connecting trillions of devices. On-device AI processing will be integral in the 5G era for several key reasons: it will reduce latency, decrease bandwidth load, ensure data privacy, increase reliability, and provide a superior means of security. Much of today's AI compute takes place in the cloud.

Fueled by improvements in speech recognition, machine learning, better algorithms, cloud processing, and more powerful computing devices, the quality of machine translations is improving. Learning another language has never been a simple proposition. It can take months of study to absorb the basics and years to become fluent. Of course, there's the added headache that learning a language doesn't help if a person encounters one of the world's other 7,000 or so languages. "There has always been a need for human translators and interpreters," says Andrew Ochoa, CEO of translation technology firm Waverly Labs.

Almost thirty years ago, when the internet was launched onto an unsuspecting world, even inventor Tim Berners-Lee and colleagues at CERN could not have predicted the upheaval that would follow. It has been the greatest technology revolution since the industrial original. The combination of Cloud, IoT and AI is driving opportunity and threat in equal measure. Decisions made within organizations will have an impact for years to come. The way in which IoT-Edge links to the broader cloud backend, and the way in which AI integrates across the full processing chain, will be the key to unlocking material innovation and value. After many years of rationalization and stretched infrastructure investments, the IoT represents a tipping point for telcos, the cellular networks on whose backbones the new IoT offerings will be delivered.

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.