Leading augmented reality (AR) technology company Blippar has confirmed its commitment to putting power in the hands of creators with the launch of its WebAR SDK technology. The toolkit will empower AR creators to build their own immersive WebAR experiences from the ground up using HTML and Java coding. WebAR SDK users will have access to full 24/7 support from the Blippar team to help hone their creative campaigns, and, during its beta phase, the platform will be entirely free to use, create, and publish from – with its immersive WebAR experiences able to be accessed and shared across platforms including browsers, Facebook, TikTok, WeChat, and WhatsApp – a further step in ensuring access to AR creativity is available to everyone. Blippar's WebAR SDK includes its most advanced implementation of simultaneous location and mapping (SLAM) to date, boasting 99% accuracy on tracking when locked, with less than a 1% margin of error in angular accuracy. SLAM is a set of computer vision technologies that allow AR developers and creatives to build much more interactive, immersive, and realistic AR experiences by using the device camera to create a mesh of the user's surroundings that includes floors, walls, ceilings, and other objects.

Europe is'the' place when it comes to areas like Data Science, Artificial Intelligence or even Deeptech Scaleups. About the AI, it has grown rapidly over the past few years and we've seen the impact on our everyday lives, from facial recognition to the recommendations we're served up. Looks like Artificial Intelligence (AI) is the most influential technology trends for 2019. However, if you look in-depth, you'll find all the intricacies that make Artificial Intelligence possible including machine learning and other deep learning techniques. Being the buzzword at present, Machine learning is the application of AI based around the concept – provide data to machines and let them learn by themselves.

Just a few weeks ago, I read that the three top British AI companies to watch are Alphabet subsidiary DeepMind, cyber security firm DarkTrace and Blippar. Not sure why Blippar was on the list, it was after-all an augmented reality company. But what we can now say is that Blippar is in trouble -- it may not have gone to meet its maker, but it has met its administrators. I can see an argument that follows on from this which suggests that the future of AI is worrisome. After-all, there are clear parallels with boo.com.

You will soon be able to instantly identify people using a futuristic facial recognition app on your smartphone. The app scans faces and brings up a profile with information about the person including links to their social media profiles. The augmented reality technology, from London-based firm Blippar, can recognise over 400,000 public figures and has a more than 99 per cent accuracy rate. It can even tell apart identical twins such as American actresses the Olsen twins, British Olympic runners the Brownlee Brothers and Irish pop duo Jedward. Blippar's augmented reality technology (pictured) can recognise over 400,000 public figures and has a more than 99 per cent accuracy rate.

Computers are getting better at recognising faces and shapes and making connections between images, heralding a new age of visual search that could transform the way we interact with the world around us. Have you ever searched Google maps for a destination, asked it for directions, then walked off in completely the wrong direction? I have, plenty of times - and I'm way down the street before the arrow on my phone jolts into the right position telling me I'm getting colder, not hotter. Of course, being a man, I have to walk on a few more metres before finally admitting my mistake and effecting the 180-degree "swivel of shame". And this always seems to happen when I'm late for a meeting, which is quite often.

Mechanically, the human visual system is not unique. We surpassed our own abilities long ago with inventions that catapulted us into areas of the light spectrum that most living creatures can't reach. The photo lens, essentially a glass eye, is pretty well perfected. But human perception is another matter. The 15 centimeters that lay behind the eye – the brain – is a massive net of neurons that process focused light into image, and image into meaning.

There are few sights more dispiriting than a long queue at ticket offices or machines when you're rushing to catch a train. However, technology is now offering an ingenious solution. A facial recognition system is being developed that uses two invisible, near-infrared lights flashing at high speed to help a single camera capture a 3-D image of a face in astonishing detail. It will register the smallest details, down to tiny blemishes and wrinkles, and can recognise individuals even if they are wearing glasses or moving quickly along a platform. The image can then be checked against a customer database.

Do you think you know cars? Well, Blippar's new machine learning technology is ready to take you on, as the augmented reality/visual search company is today announcing automotive recognition tech. In other words, Blippar's AI can identify the make, model and year of any U.S. car made in 2000 or after, as long as the car is traveling slower than 15mph. Blippar originally launched as an AR platform for brands and publishers. Using a little tag (a Blipp), brands could identify content like a label of a ketchup bottle or an ad in a magazine that users could scan with their phones to reveal extra augmented reality content.

Over 1,000 attendees, 50 speakers and 30 exhibitors; this is a brief summary of what I was lucky enough to take part in during the first AI Europe 2016 conference held in London on the 5 and 6 December. The attendee list boasted the biggest names from the world of artificial intelligence such as Microsoft, Dell, Uber, Samsung and Nvidia, as well as several innovative start-ups, the likes of Blippar and DreamQuark whose innovations are based on machine or deep learning models. Even if we can say with a degree of certainty that further advances in artificial intelligence are yet to come, leading players are in agreement that most AI techniques and technologies are now well-advanced. Therefore, their major preoccupation today is more about the quality of the data sets being used to train and validate their machine and deep learning models. Whether it's Dell or Uber, Microsoft or Blippar, they all have one thing in common: they all agree on the fact that as of now, the quality of the data used in AI for machine learning is of the utmost importance.

"OK, this one is pretty cool," said 6-foot-tall Omar Tayeb as he held his left hand in front of himself and snapped it with his iPhone. He left it there as an app detected each of his fingernails and proceeded to paint each one. On the phone's screen, Tayeb's nails turned a dazzling shade of Maybelline purple. "So the app was able to detect where my nails were, paint them in one of Maybelline's nail polish colors, then adjust to the room's lighting so it looks natural," Tayeb said. And it is impressive, given that as little as five years ago the smartest smartphones would have struggled to recognize the most basic of images, let alone identify individual fingernails and accurately color them.