Starship Technologies of Greenwich in London has built a robot that is starting trials delivering meals, groceries and parcels. Four firms in Britain and Germany are involved. But will the robots be able to navigate safely between business and customer?

At a competition in China to see who is better at recognizing faces, man or machine, Wang Yuheng, representing the humans, emerged victorious. Wang is famous in China for his photographic memory. He successfully identified a specific glass of water out of 520 seemingly identical ones in a Chinese reality TV show. He also reportedly helped police crack a case by extracting "hidden clues" from surveillance camera footage, thanks to his exceptional observational skills. But Wang's competitor, "Mark," is no less smart.

NEW YORK, July 6, 2016 /PRNewswire-USNewswire/ -- Thanks to his business acumen, poster boy looks, and relentless activism for freedom of the internet, Reddit's co-founder Alexis Ohanian has become one of the most high-profile residents of Brooklyn. A startup based in Armenia and San Francisco named 1AI Solutions has recently launched a working AI-based version of Alexis Ohanian named Avedis Ohanian. Additionally they used 3-D printing to replicate the body of Alexis Ohanian, infusing it with their proprietary Artificial Intelligence engine. "There's a lack of qualified IT professionals here in Armenia", said Dr. J.P. Hagopian, the CEO of 1AI Solutions. "We need to hire people, but we simply can't find enough good candidates. At some point our HR manager said that we should clone one of the high-performing Silicon Valley guys. She was kidding, but the idea stuck."

The makers of a new trend-forecasting platform claim they predicted the Rainbow Bagel before it was a thing. Santa Monica, California-based Tilofy is currently in a private, invitation-only beta of its new platform, which it says is the first automated trend forecaster. Unlike services that, say, spot current trends in social media, Tilofy utilizes machine learning, artificial intelligence and machine vision of imagery to forecast trends weeks or months before they become mainstream. "There's a bagel store in Brooklyn that was doing something interesting, tapping into the LGBT community" by creating a rainbow-colored bagel, CEO and founder Ali Khoshgozaran told me. He recalled that Tilofy predicted the future mainstream popularity of the Rainbow Bagel in November of last year. In February, The Wall Street Journal wrote an article about it, and now The Bagel Store is restructuring around its hit product.

Enterprises today are finding it exceedingly meaningful and resourceful in the massive amounts of data they generate and save every day. The required algorithms, applications and frameworks to bring greater predictive accuracy and value to enterprises' data sets are available; therefore, businesses need to make sure they have data sets of sufficient size and quality. It is due to the excessive need to do a better job in capturing and utilizing data. The rise of deep learning and neural networks has spread in everyday lives. It took about six years for neural nets to show impressive results, first in speech recognition, then computer vision, images, image detection and diagnostics, and more recently, in natural language processing.

Machine learning is a branch of artificial intelligence concerned with the design of data-driven programs which autonomously demonstrate intelligent behavior in a variety of domains. Machine learning systems are all around us. When you deposit a check, scan your fingerprint, or post a picture on social media, autonomous algorithms are deployed on the spot to sift through and make sense of your constant interactions with our technology. Machine learning silently underpins the fabric of our digital infrastructure, discriminating spam e-mail and banking fraud, making light-speed transactions in the global financial market, recommending music and films for customers to buy, deciding what search results are relevant to your queries, and countless more of the daily interactions with electronic media that we take for granted. Machine learning is the backbone that powers self-driving cars, content recommendation in social media, face identification in digital forensics, and countless other high-level tasks.

We're only at the beginning of the development of AI technology and the potential is enormous. AI has become integral to the inner workings of most industries and it's undeniable that it's evolving at an alarming rate. It's been adopted within the mechanics of everyday life and whilst simulating human intelligence is probably not all that far off – will AI ever harness true anthropomorphic traits like the capacity to be creative? Creativity is how we express our experiences. It relies on originality, imagination and the ability to make something not done before.

When Amazon first launched the Fire TV Stick in late 2014, it almost seemed too good to be true. The thumb-sized device promised more power than the latest Roku box and a better app selection than Apple TV at less than half the price of either. It was only a little pricier than Google's Chromecast dongle, yet it managed to include a proper remote control and on-screen interface. Despite some early launch bugs and quirks, it was a great way to make your TV smarter on the cheap. Cut to 2016, and the competition has gotten tougher.

In last month's blog I talked about keeping your team innovative. One of the key tenets of an innovative team is the concept of moonshots or "10x Thinking" or audacious goals. In a "moonshot economy," while a breakthrough can mean the start of a new industry leader, it can also mean the death of an industry stalwart. First, let's take a look at some previous moonshots and how they've impacted various industries and the world. The first is, of course, the great Space Race.

The science fiction TV series initially seemed like the savior for NBC. When it premiered in 2006, NBC was behind the other big networks and in need of a hit. The plot about normal people who develop super-powers caught on quickly but eventually lost pace. It solidified Hayden Panettiere's place in pop culture, and the series was a favorite among critics. It scored eight Emmy nominations in 2007, though it failed to bring home a single win. In its first season, "Heroes" scored a staggering 13.8 million viewers, but by season 3, viewership was down to 7.6 million viewers.