Ambarish is the founder and CEO of Blippar, an augmented reality and image recognition platform. Leading venture capitalists, scientists and CEOs all have the same prediction for artificial intelligence: machines will take jobs away from both blue- and white-collar workers, "eat the world" and, ultimately, overthrow humanity. These histrionics have driven a widely accepted negative narrative about this technology's potential impact on the future of humanity. Bringing artificial intelligence into the mainstream world should be met with hope and empathy, not fear. The concerns of these experts -- wealthy men with unparalleled access to utilities, healthcare, public safety, education and job opportunities -- are the concerns of privilege.

The development of digital health technology causes many concerns regarding bioethics. Here are 10 examples why people should not be afraid of, but rather embrace the advancements of such technologies. The fear from the unknown is as old as mankind itself, thus the fear from technological development has the same age as advancement itself. When the telephone was introduced to Sweden in the late 1800s, people were afraid that the contents of the lines would spill out in some way if there was a break and many elderly persons refused to touch a telephone for fear of electrical shock. The fear is even scarier when it comes to one's health. Shortly after Wilhelm Conrad Röntgen introduced his discovery about the X-Ray, people got scared that it might read their thoughts, and they were afraid that such omnipotent gaze will see through their body and soul. Merchants even offered X-Ray proof underwear.

For more than a decade, Silicon Valley's technology investors and entrepreneurs obsessed over social media and mobile apps that helped people do things like find new friends, fetch a ride home or crowdsource a review of a product or a movie. Now Silicon Valley has found its next shiny new thing. And it does not have a "Like" button. The new era in Silicon Valley centers on artificial intelligence and robots, a transformation that many believe will have a payoff on the scale of the personal computing industry or the commercial internet, two previous generations that spread computing globally. Computers have begun to speak, listen and see, as well as sprout legs, wings and wheels to move unfettered in the world.

Google just paid for part of its acquisition of DeepMind in a surprising way. The internet giant is using technology from the DeepMind artificial intelligence subsidiary for big savings on the power consumed by its data centers, according to DeepMind Co-Founder Demis Hassabis. In recent months, the Alphabet Inc. unit put a DeepMind AI system in control of parts of its data centers to reduce power consumption by manipulating computer servers and related equipment like cooling systems. It uses a similar technique to DeepMind software that taught itself to play Atari video games, Hassabis said in an interview at a recent AI conference in New York. The system cut power usage in the data centers by several percentage points, "which is a huge saving in terms of cost but, also, great for the environment," he said.

For more than 10 years, Silicon Valley's technology investors and entrepreneurs obsessed over social media and mobile apps that helped people do things like find new friends, fetch a ride home or crowdsource a review of a product or a movie. Now it's found its next shiny new thing. And it does not have a "Like" button. The new era in Silicon Valley centres on artificial intelligence and robots, a transformation many believe will have a payoff on the scale of the personal computing industry or the commercial internet. Computers have begun to speak, listen and see, as well as sprout legs, wings and wheels to move unfettered in the world.

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.