The blending of home-based diagnostic platforms with medical care at home is arriving. The Tricorder XPRIZE competition is well underway, with several teams set to compete in the final stages. Leading contenders include CloudDx and Scanadu, a company started at our first Exponential Medicine program, have successfully leveraged crowdfunding to enable their clinical trials. Gale by 19Labs is a next generation "first aid kit meets home health center" (see the below video for a demo) exemplifying how integration of home diagnostics paired with menu-driven (and potentially AI-driven) assistance and optional telemedicine connectivity can provide increased access to home-based diagnosis, triage and management of minor bumps and scrapes and also more complex medical conditions. Interactive and engaging, from coaching on diet and nutrition to reminding you to take your medications or offering psychological support and follow up -- the chatbots are on their way.

Over the past few years, Siri's functionality and reliability has improved by leaps and bounds. Not only is Siri's feature-set more expansive than ever, but it operates much more quickly and does a much better job at understanding and processing language. To this point, Medium last week published a fascinating and detailed profile on how Apple's advancements in the field of AI and machine learning have helped take Siri's performance to the next level. In fact, Siri Senior Director Alex Acero boasted that advancements in Siri's underlying technology has cut down the error rate "by a factor of two in all the languages" and "more than a factor of two in many cases." DON'T MISS: Apple's iPhone 8 will feature the radical redesign we've been waiting for "That's mostly due to deep learning and the way we have optimized it," Acero added, " not just the algorithm itself but in the context of the whole end-to-end product."

Interest in bots and artificial intelligence is on the rise. VC funds are looking at the space for new investments. Likewise, players such as Facebook, Amazon, Google, and Microsoft are hoping to find new revenue streams here. And at the same time, an increasing number of entrepreneurs are trying to make it big with Bots. MobileBeat 2016 was all about bots and artificial intelligence and this blog will give you the lowdown on the latest and greatest in this exciting field.

Over the past few years, Siri's functionality and reliability has improved by leaps and bounds. Not only is Siri's feature-set more expansive than ever, but it operates much more quickly and does a much better job at understanding and processing language. To this point, Medium last week published a fascinating and detailed profile on how Apple's advancements in the field of AI and machine learning have helped take Siri's performance to the next level. In fact, Siri Senior Director Alex Acero boasted that advancements in Siri's underlying technology has cut down the error rate "by a factor of two in all the languages" and "more than a factor of two in many cases." DON'T MISS: Apple's iPhone 8 will feature the radical redesign we've been waiting for "That's mostly due to deep learning and the way we have optimized it," Acero added, " not just the algorithm itself but in the context of the whole end-to-end product."

One of the first computers required punch cards. Yes, you would take a piece of paper with tiny holes and use it to interact with the device. Now we have computers the size of soda cans that sit in your house and control your lights, provide weather updates, solve math equations and tell jokes, all by simply speaking to them… and some of them have better jokes than my actual friends. In many ways, we all should have seen this coming -- we can thank our Hollywood friends for that. We had C-3PO and R2-D2 running around the galaxy with Luke trying to help him save the universe from his dad.

Apple TV users were left with the third generation unit for far too long. As many waited for years to see what Apple would do next, the wait seemed obnoxiously long. In a deep dive on Apple's AI efforts, Backchannel notes that Siri is the reason the current Apple TV took so long to arrive: Apple now says that without those advances in Siri, it's unlikely it would have produced the current iteration of the Apple TV, distinguished by sophisticated voice control. While the earlier versions of Siri forced you to speak in a constrained manner, the supercharged-by-deep-learning version can not only deliver specific choices from a vast catalog of movies and songs, but also handle concepts: Show me a good thriller with Tom Hanks. Siri's recent advancements, like the Apple TV, were years in the making.

Apple wants you to know it's been working on AI for years now -- you just didn't know it. In a new feature by Stephen Levy in Backchannel, some of the company's top execs and machine learning experts hammer home this message, pointing out all the ways in which AI is used in Apple's products today. But, they also point out that artificial intelligence isn't the "final frontier" for tech products "despite what other companies say." Apple has cause to push this message. The perception of the iPhone-maker in the wider AI community is that it's been behind the game, despite having launched Siri, its virtual assistant, back in 2011.

In his biting, much-cheered defense of the work of local newspapers on his show "Last Week Tonight," the red-hot HBO satirist John Oliver had much fun at the expense of the role of "artificial intelligence" in modern journalism. Oliver's highly entertaining piece -- which quickly garnered well in excess of 4 million views -- contrasted the current enthusiasm of some publishing executives, including the ones who currently pay my salary, for various automated manifestations of reporting, editing and news distribution with what you might call the old-fashioned, sentimental view of the profession: the notepad-wielding reporter at the quotidian school board meeting, fighting corrupt politicians and delivering the truth to your stoop. There is a lot to unpack in Oliver's 19-minute segment and various levels of irony at work. For starters, there's this: In decrying the tendency of panicked newspapers to veer toward populist click-bait, Oliver cleverly created, well, his own populist click-bait. Oliver humbly and openly acknowledged how much his show depends on newspapers for its material -- thank you very much on behalf of my hard-working colleagues.

From Google's advertisements to Amazon's product suggestions, recommendation engines are everywhere. As users of smart internet services, we've become so accustomed to seeing things we like. This blog post is an overview of how we built a product recommendation engine for Hubba. I'll start with an explanation of different types of recommenders and how we went about the selection process. Then I'll cover our AWS solution before diving into some implementation details. Content-based recommenders use discrete properties of an item, such as its tags.

Despite the ongoing efforts of banks to attract millennials, they are still failing to make an impression. According to Gallup, only 23% of millennials are actively engaged with their bank, making millennials the least engaged generation. Considering that fully engaged customers bring considerable benefits and higher revenues – this is a big problem. If banks expect millennials to "simply grow up," they may be facing a tough road ahead. Financial institutions – banks and others – that find a way to communicate with millennials on their terms and give them the financial tools they want are more likely to end up the winners. When millennials feel supported and are able to choose the way in which they interact with a bank, they are more likely to strengthen their relationships and make smarter financial decisions.