Investors poured a record high $1.05B into artificial intelligence startups in Q2'16, and AI is already affecting more areas of our lives than many people realize. Even retail and e-commerce companies are increasingly integrating the technology. Recently there's been a rush of AI announcements and acquisitions by major retailers: Just this week, Etsy acquired Blackbird to enhance its search functionality through AI, followed the very next day by Amazon acquiring Angel.ai And earlier this month, e-commerce unicorn Houzz (see our full unicorn tracker here) announced a deep learning initiative to help users find and buy products by clicking on images. Using CB Insights data, we dove into the wide array of AI startups focused on retailers and e-commerce businesses, including AI-powered personal shopping apps, natural language processing and image recognition tools for shopping websites, predictive inventory allocation tools, and more.

In this way it identifies buildings, vehicles, persons, trees and pavements among other things and reliably finds traffic lights as well as smaller dangerous obstructions on the road. Based on this, the autonomous vehicle analyses the traffic situation, predicts the behaviour of other road users and decides on its own behaviour. 'In daylight many systems for image and pattern recognition, on the market are reliable', says Dr Uwe Franke, responsible for image recognition/signal processing and sensor fusion in the Mercedes-Benz development department. 'Meanwhile, our system even offers top level results at night and that is a major development. The next step is about recognising and interpreting people's gestures and facial expressions.'

Using a combination of artificial intelligence (AI) and brain scanning technology, a team of researchers has developed a novel method that can help remove specific fears from the brain. The new technique that could read and identify a fear memory can pave way of treating patients with conditions such as post-traumatic stress disorder (PTSD) and phobias, the study said. Neuroscientists, from the University of Tokyo, developed'Decoded Neurofeedback' -- which used brain scanning to monitor activity in the brain, and identify complex patterns of activity that resembled a specific fear memory. In the study, the team included 17 healthy volunteers in whom a fear memory was created by administering a brief electric shock when they saw a certain computer image. Using brain scanner, the researchers monitored the volunteers' mental activity and were able to spot signs of that specific fear memory. Using AI algorithms, they also developed a fast and accurate method of reading the fear.

Machine learning has become an invaluable tool in the fight against fraud. It combines computational statistics, artificial intelligence, signal processing, optimisation, and other methods to identify patterns. Machine learning has been a significant breakthrough in helping companies move from reactive to predictive by highlighting suspicious attributes or relationships that may be invisible to the naked eye but indicate a larger pattern of fraud. The great value of machine learning is the sheer volume of data that computers can analyse that humans cannot, thanks to a variety of pattern recognition algorithms. With this you can add exponentially more data to your analysis -- but selecting the right data and approach to model the problems is critical. A solid solution also requires specialised expertise to apply rigorous methodology in data analysis and develop the fraud models to ensure consistent quality.

One of the basic features of artificial intelligence (AI) is the ability to recognize images and process them. Companies like Microsoft and Google have debuted tools to show how accurate their image recognition platforms are. Now it seems that Amazon wants in as well as they have announced Amazon Rekognition. This is an image recognition service that is part of a suite of deep-learning services that Amazon has recently announced for developers. For the most part it does what most image recognition services do, which is to identify human faces, identify emotions, and label objects just by looking at it.

Amazon today announced three new artificial intelligence-related toolkits for developers building apps on Amazon Web Services. At the company's AWS re:invent conference in Las Vegas, Amazon showed how developers can use three new services -- Amazon Lex, Amazon Polly, Amazon Rekognition -- to build artificial intelligence features into apps for platforms like Slack, Facebook Messenger, ZenDesk, and others. The idea is to let developers utilize the machine learning algorithms and technology that Amazon has already created for its own processes and services like Alexa. Instead of developing their own AI software, AWS customers can simply use an API call or the AWS Management Console to incorporate AI features into their own apps. AWS CEO Andy Jassy noted that Amazon has been building AI and machine learning technology for 20 years and said that there are now thousands of people "dedicated to AI in our business."

Under, behind and inside many of the apps we use every day, a revolution is underway. It's a revolution that started decades ago but today is empowering companies to deliver better, smarter services with greater ease and on broader scales than ever before. At Singularity University's inaugural Global Summit, Neil Jacobstein, chair of Artificial Intelligence and Robotics, provided a primer showing how artificial intelligence literally transforms everything it touches. First of all, it's critical to define the scope of artificial intelligence (AI), which can be categorized into four areas: techniques in pattern recognition, software agency (that is, software that acts like real users), an exponential technology that is accelerating other exponential technologies, and a vision of a future superhuman intelligence (that fortunately hasn't happened yet). Anyone who has seen a science fiction film is likely familiar with this last area, but it's the other three areas where AI is making huge strides at a revolutionary pace.

Researchers at the University of Cambridge have discovered a way to remove specific fears from the brain using a combination of artificial intelligence and brain scanning technology. Fear related disorders effect around 19 million US adults, or 8.7 percent of the adult population. Current treatments are limited to expensive and'unpleasant' forms such as aversion therapy, where individuals confront their fear by being exposed to it in the hope they will learn that the thing they fear isn't harmful after all. Now a team of neuroscientists from University of Cambridge, Japan and the USA, has found a way of unconsciously removing a fear memory from the brain. Using AI, the team developed a method to read and identify fear memory using'Decoded Neurofeedback'.

As part of Google's slew of artificial intelligence announcements today, the company is releasing a number of AI web experiments powered by its cloud services that anyone can go and play with. One -- called Quick, Draw! -- gives you a prompt to draw an image of a written word or phrase in under 20 seconds with your mouse cursor in such a way that a neural network can identify it. Quick, Draw! is a great way to familiarize yourself with how neural networks work to identify objects and text in photos, which is one of the most common forms of AI-guided software techniques we see daily on platform's like Facebook and Google Photos. As you start to craft the doodle, Quick, Draw!'s software automaton will start yelling out words and phrases it thinks you're trying to illustrate. As you get closer to the finished product, the voice starts to become a good indication of how your drawing could be misinterpreted as something else. If you're on point, however, the neural network will hone in on the object and guess correctly.