Well, if I have a look at my personal life, there are some work categories where AI will be of great value to me--a maid, a driver, an on call doctor, even an assistant to help me filter through the information I have to churn through. When it comes down to it, I don't think AI can replace human communication, a combination of emotional and analytical perspective. We know when we're interacting with a machine, and as complex as we can make AI, will we ever truly feel it is more than talking to a toaster? Camilla Urdahl works for unified communications company Unified Inbox, and will speak to strangers at events about communications strategies, new business models, and how best to accelerate innovation.

The tech giant decided not to source its chips from other providers, instead building its own customised processors, dubbed Tensor Processing Units (TPUs), for its machine learning software. "We've been running TPUs inside our data centers for more than a year, and have found them to deliver an order of magnitude better-optimized performance per watt for machine learning," Google said in a blog post. Since AI has only recently found commercial use cases, companies that process AI functions are still solely using graphics processing units (GPUs) to do the job. "TPU is tailored to machine learning applications, allowing the chip to be more tolerant of reduced computational precision, which means it requires fewer transistors per operation," Google said.

Alexy Khabrov's talk at LX Scala caused the Scala community to raise their arms for a revolution. After his talk, Alexy discussed his thoughts on how to ease the transition for Python data scientists into the Scala community, what Scala can learn from Python as a programming language, and how machine learning will influence the future of the Scala community within the next five years.

Moving to the right, credit card fraud detection and spam filtering have higher levels of predictability, but current-day systems still generate significant numbers of false positives and false negatives. Consider two of the relatively higher predictability problems mentioned earlier--spam filtering and driverless cars. In contrast, above the frontier, we find that even the best current diabetes prediction systems still generate too many false positives and negatives, each with a cost that is too high to justify purely automated use. On the other hand, the availability of genomic and other personal data could improve prediction accuracy dramatically (long orange horizontal arrow) and create trustworthy robotic healthcare professionals in the future.

Google executives talk about the company's future in artificial intelligence. During his keynote talk, Pichai also showed a video of several robot arms that a research group at Google taught to pick up objects. "It's also conflated with the fact that people look at things like robots learning to pick things up and that's somehow inherently scary to people," Giannandrea said. In April, Facebook unveiled a new Applied Machine Learning group.

Based on artificial intelligence, Snips can memorize your contacts, calendar and location, conveniently storing them in one place. The app also guarantees to keep all of this personal data private, meaning no one will see it except for you. "We want Snips to be able to answer any question we might have, do anything we ask it to, and automate our connected devices." As more devices become connected, Snips may one day be able to pick up on how users utilize their tech and automate them for convenience.

But if you're looking for our most hated automated thing in the universe, that's easy. It's the Interactive Voice Response (IVR) system, better known as a phone tree. While bots may one day have the potential to replace customer support and e-commerce, human touch will remain essential to the experience for the foreseeable future. Leverage bots to handle the basics, but also create easy opportunities for customers to connect with a live human (or have one call back) if the interaction gets stalled.

As video content matures and proliferates and VR content creates new interactive environments and as the way we access software and apps changes and evolves, PVAs or personal virtual assistants will radically influence the interface with the internet and these new layers of content and virtual experience. Viv is just four years old, but by the time IoT and VR matures, she will be ready to make the smart home, smart city and billions of connected devices truly come to life. While we assume it will be one of the tech giants: Google, Facebook, Amazon, Apple or Microsoft; disruption doesn't usually come from an established player whose interests and investments are scattered. Just as VR represents a new platform of information, content, advertisement, marketing and social media, and digital experiences, VPAs like Viv could represent another springboard to the future.

As a leading technologist, Abinash has a vision that Indians can build great product companies provided the government and telecom operators figure out a way to offer free internet for students. AT: It pains me that we have technology focused on selling retail products to consumers. That said, India has the engineering skills to build technologies like machine learning and artificial intelligence. If the product is driven at large corporate then the founder must have great marketing skills.

Over the past several years, Riot Games, which produces the immensely popular League of Legends, has been experimenting with artificial intelligence (AI) and predictive analytics tools to find the online trolls and make their games more sportsmanlike. "We used to think that online gaming and toxic behavior went hand in hand," explains Jeffrey Lin, lead game designer of social systems at Riot Games. "First, put the tools in the hands of the community and second, build machine learning systems that leverage the scale of data--contributed from the community through reports--to combat the problem." To learn how Big Data, automation and artificial intelligence will shape the future, download the HPE white paper "Big Data in 2016."