Imagine you took a world-class business writer and asked him to rate the quality of several pieces of content in a blind test. Would he be able to tell which ones were created by humans and which ones were produced by automated writing? Well, that's exactly what Mark Schaefer addressed recently. To find out that… "two of the top three posts were written by a computer." Given that Mark is one of the most respected speakers and writers on marketing, with a successful blog, an impressive audience and numerous publications, I wouldn't blame you if it sounded so. But while his post focuses on what human content marketers can do to write better content and combat robots, I'd like to elaborate on how artificial intelligence (AI) can benefit human content marketers.

Leap Motion is transforming how we interact with technology using the original interface: the human hand. Over the last two years, we've shipped almost half a million motion-tracking controllers to developers and consumers around the world, opening up new possibilities for a platform beyond the screen – from music and gaming to the next generation of VR/AR interfaces. By bringing people and computing devices closer together, a career at Leap Motion offers the opportunity to help bring science fiction to life. Our software is rapidly evolving, and we're looking for a build engineer to help take it to the next level. This would involve managing our substantial continuous integration automation infrastructure, contributing to improving code coverage, and helping us automate as much of our build and testing pipeline as possible.

Microsoft has made Azure Machine Learning a much more compelling solution for data scientists today. The company issued an update for the service that brings support for multiple R and Python versions, easing workloads for developers. Azure Machine Learning gives users a cloud-based service to create analytic solutions with an easy to use UI. The platform has won praise and is powerful, bringing together Microsoft technology and analytic tools to make predictive analytic software easier to create. However, the service has also had limitations since arriving two years ago.

This is one of those sites you're going to want to try yourself. Take any black and white image, feed it to the algorithm, and watch as it spits out its best guess at a color version, which is often quite convincing. Using a deep learning algorithm developed by Richard Zhang, Phillip Isola, and Alexei Efros of UC Berkeley, the process was trained on one million images. Though it currently fools humans only 20% of the time, that's still a significantly higher rate than previous iterations and represents an exciting step forward, and further training should only increase that rate. Imagine a time when Photoshop can colorize a photo in one step, leaving the end-user to just tweak a few hues here and there.

Summer is welcoming us with great news! We are thrilled to announce Baidu Research as part of our AI Meetup series! We will start off with a Q&A with Andrew Ng, Chief Scientist at Baidu and one of the founding fathers of modern AI research. After that, we will follow with presentations from two researchers from Baidu's Silicon Valley AI Lab – Bryan Catanzaro and Eric Battenberg. Baidu Research brings together top researchers, scientists and engineers from around the world to work on fundamental AI research.

Artificial intelligence has been on humanity's radar for quite some time. But recent developments such as AlphaGo's triumph over Lee Sedol and Watson winning the quiz show Jeopardy have given us an even greater and discomfiting awareness of the vast strides that have been made in this field. On the other hand, Microsoft's famously bungled attempt to create an AI Twitter account, which started spouting racist and genocidal vitriol within a day, reminds us that an AI-orchestrated apocalypse is still far off. Indeed, the simple fact of the matter that all iPhone users realize is that Siri hasn't even quite mastered the nuances of human colloquialisms and syntax. This is precisely the point that the Winograd Schema Challenge seeks to prove.

Progressive is one of the largest auto insurers in the United States with over 13 million policies in force. Progressive is a pioneer in data analytics with more than 14 billion miles of driving data collected through its telematics offering, Snapshot. Hear from Pawan Divakarla, Data and Analytics Business Leader, on how H2O is helping build models and derive insights in just seconds using open source Machine Learning. Highlights from video: "Predictive analytics is making a very positive culture shift and I see it growing exponentially. It's fostering a lot more creativity…giving that empowerment to our data scientists is key for us. H2O is an enabler in how people are thinking about data."

Japan-based IT products and services provider Fujitsu has collaborated with Jorudan which is a public transport and route navigation website. Both will be adding a train delay time prediction function, using Artificial Intelligence (AI) machine learning technology, to Jorudan's "Norikae Annai," a service that provides public transportation route-planning information. With this collaboration, Fujitsu aims to deliver, predicted train delay times using AI technology for the Norikae Annai service and verify prediction effectiveness. This process is provided as the cloud service Fujitsu Intelligent Society Solution SPATIOWL, a service that studies previous railway operations data and data submitted by the users and with this, it forecasts the changing delay times built on fresh submitted data and operational information. These predictions are displayed in the route search results in Jorudan's Norikae Annai app, supporting users' route selection when trains are delayed.

Twelve months ago, in my one-bedroom apartment in NYC, my founding team at Wade & Wendy got together on a mission to make the recruiting process human again. The four of us had experienced the many pains of the recruiting process from all angles. Our CTO, Josh Brandoff, a highly-sought after engineer bombarded by pushy recruiters every time he joins a new social network. Our Head of Growth, Ian Jaffrey, a former chief of staff at American Express with a deep appreciation of the intimate mentorship it takes for career advancement. Our Head of Product Design, Adrian Von Der Osten, who was trained and educated in the field of architecture but found himself in the wonderful world of startups doing user experience design, a radical career jump many can only dream of.

When I woke up this morning, I asked my assistant a simple question: "Siri, is it going to rain today?" Siri understood my intent, pulled the local weather data via an API and answered me in less than two seconds: "There's no rain in the forecast for today." In the not-too-distant past, this kind of human-computer interaction would have blown away technologists and delighted consumers -- but in 2016, it's nothing special. Conversations with Siri are commonplace, just like they are with Microsoft's Cortana and Amazon's Alexa. Machine learning (ML) and narrow forms of artificial intelligence (AI) have officially reached the mainstream.