Facebook (NASDAQ:FB) disclosed that it now has over 11k chatbots on its FB Messenger platform and over 23k developers have signed up for the platform's bot engine. This is very impressive given that the chatbot function was only introduced several months ago and recent conversation with third-party developers in sports, life, ecommerce and local entertainment verticals suggests that the bots are driving engagements higher as users seek info via FB Messenger bots. This is certainly a positive for FB and a critical component of the overall FBM ecosystem. I have often argued that FBM's biggest potential lies in its ability to replicate the Wechat model to retain users and build an ecosystem featuring search, ecommerce, payment, advertising, gaming and social networking. Long-term implication could be a negative to Google (NASDAQ:GOOG) if additional developers are enrolled on the FBM chatbot network and the quality of results increase.

At WebRTC Argentina we covered a number of topics, including an introduction to WebRTC with coding demonstrations, demos of WebRTC use cases, and design/UX for WebRTC. We concluded the mini-conference with this talk, where we wanted to stretch people's minds a little bit about WebRTC. WebRTC is not simply about 1-1 video chats or business conferencing tools. WebRTC can be one part of larger technological change in our society, and in this talk we give updates on WebRTC in the short term as well as one vision for how WebRTC and Artificial Intelligence may intersect in the future. You can see the complete presentation below, and we've included the transcript below the video.

As we approach the celebration of the 4th of July, I thought it might be interesting to share a request for information made to the US Federal Register and a post on the Whitehouse blog. The US government is interested in what Artificial Intelligence might mean to the people of the United States, and how we could learn about it more. To find out, they are asking for comments by July 22, 2016. Ed Felton, Deputy U.S. Chief Technology Officer wrote the following blog post about what the government would like to learn: How to Prepare for the Future of Artificial Intelligence. Broadly, OSTP is interested in developing a view of AI across all sectors for the purpose of recommending directions for research and determining challenges and opportunities in this field.

They say the best investors know how an event in one corner of the market impacts a company in another. New mining laws in Colorado require thousands of workers to wear a certain type of hardhat,...

The current technological boom, and the increasing consumerism is doing that every day appear more machines that are playing an essential role in our lives and have already become a vital necessity in every activity that we, or actually they, carry out. Either at home, in the car, at work or anyplace, we will soon have a dependence of these machines. In this post I wanted to reflect the positive aspect of machines in our lives and I have considered that the machines will take the right decisions that will make be better people but without controlling us, but the risks to become too dependent on machines exist and we cannot forget.

Pathologists still do the bulk of their diagnosis of metastatic cancer cells in tissue and lymph nodes by hand, putting slides under a microscope and looking for signature irregularities they're trained to see. Recent advances in computer technology, however, particularly in artificial intelligence (AI), have begun to teach machines to do this kind of detection with growing rates of improvement. Now, a research team from Beth Israel Deaconess Medical Center (BIDMC) and Harvard Medical School have developed a form of AI that can interpret these pathology images with accuracy levels of 92.5 percent. Moreover, when the two are used in combination, the detection rate approaches 100 percent (approximately 99.5 percent). Their AI method is a form of deep learning, in which the system attempts to replicate the activity of the human neocortex through artificial neural networks.

Like many people, I start most mornings digging myself out of an inbox that often feels like more trouble than it's worth thanks to the seemingly infinite amount of newsletters I receive. And although these newsletters cross verticals as varied as marketing, technology, advertising and the agency world, lately each one has a headline that includes artificial intelligence. Not surprisingly, all of us are curious to know how this growing field of technology is going to infiltrate our professional and personal lives. Across every industry, people are afraid that AI is going to steal jobs. As a marketer I don't think we have any urgent concerns over job security.

When Jason West and Vince Zampella set up Respawn Entertainment in 2010, they had one ambition: to produce a new first-person shooter that would have as massive an impact on the genre as their previous creation: the Call of Duty series. It was a big ask, but when Titanfall arrived three years later, the game was certainly a brilliant attempt. The sci-fi shooter boasted an innovative mechanic allowing players to summon a giant robot into the arena, and an incredibly fluid, free-running movement style – all combined into a set of blisteringly loud and detailed map designs. But one thing many players said about Titanfall was that, beyond the raw speed and inarguable thrill of the highly vertical, highly acrobatic gameplay, there was little in the way of tactical depth. It's something the team says it wants to address. "We learned a lot from the community," says producer Drew McCoy.

In a major breakthrough for artificial intelligence, a computing system developed by Google researchers in Great Britain has beaten a top human player at the game of Go, the ancient Eastern contest of strategy and intuition that has bedeviled AI experts for decades. Machines have topped the best humans at most games held up as measures of human intellect, including chess, Scrabble, Othello, even Jeopardy!. But with Go--a 2,500-year-old game that's exponentially more complex than chess--human grandmasters have maintained an edge over even the most agile computing systems. Earlier this month, top AI experts outside of Google questioned whether a breakthrough could occur anytime soon, and as recently as last year, many believed another decade would pass before a machine could beat the top humans. But Google has done just that.

We hope you find it useful in your machine learning projects.