Are you more clever than your fridge? There are two types of artificial intelligence, but not all artificial intelligence is created equal. There is narrow AI, which is painstakingly designed to compute just one thing, but it does it very well. And there is general AI that can adapt to solve different tasks by learning and changing. But who do general AIs learn from?

Zebra Medical Imaging is working with Intermountain to create a neural network that will study and compare x-rays with its own database. This means that, instead of handing your x-ray to a doctor, where human error could come into play, the image would instead be given to a computer equipped with deep learning to sift through a massive database of possible anomalies. The development of this technology also means that the AI can more efficiently interpret fresh x-rays and offer suggestions to radiographers, thus reducing the possibility of misdiagnosis. As deep learning technology evolves to become stronger and cheaper, the opportunities for artificial intelligence (AI) to continue assisting medical practitioners becomes more apparent. Eventually, the team behind this work is hoping that it can lend itself to better access to medical diagnostics, especially in countries where there is a shortage of medical experts.

Tesla CEO Elon Musk reckons humans will need to implant "neural laces" in their brains to keep up with AI advancement. While Musk's description of an injectable human-computer link may sound like science fiction, top tech executives repeatedly said artificial intelligence (AI) was on the verge of changing everyday life, during discussion at a conference by online publication Recode this week. It is no secret that tech companies are diving into AI analytics research, an industry that will grow to 70 billion by 2020 from just 8.2 billion in 2013, according to a Bank of America report citing IDC research. AI, which combs through large troves of raw data to predict outcomes and recognise patterns, is already used in Web search systems, marketing recommendation functions, and security and financial trading programs. The technology will spread to driverless cars and service robots in the future, the Bank of America report said.

What do you get when you cross self-driving artificial intelligence, 3-D printing, and public transportation? Local Motors, a manufacturer known for its focus on open-source vehicle designs, unveiled Olli on Thursday at its new facility in National Harbor, Md., a development just outside Washington D.C. To test Olli, Local Motors plans to offer free rides to the public around the development in what is believed to be the first public trial of a completely self-driving vehicle in the United States, reported The Washington Post. In February, the Netherlands launched a fleet of WEpod driverless buses, which can carry six passengers, on the campus of Wageningen University in a central Dutch agricultural town. Miami-Dade County has bought two Olli shuttles, and Las Vegas has bought one.

Last month Google revealed that it's making its own custom artificial intelligence processing chips. Now it turns out that you may already be using them. The chips are called TPUs, short for Tensor Processing Unit, named for Google's open source AI framework, TensorFlow. Today at the 2016 WIRED Business Conference in New York City, the head of Google's cloud business, Diane Greene, said that Google is already using TPUs in more than 100 projects. These include Android's voice recognition system, the "Smart Reply" feature of its Inbox app, and Google's new cross-application search service Springboard--in short, stuff you may already be using.

Local Motors officially introduced "Olli" -- a self-driving mini bus that incorporates IBM's Watson artificial intelligence (AI) platform to deal with customers. The IBM's AI service will not be used to operate the self-driving car, and will instead answer customer queries about the route and whether they have time to stop for coffee on the way. The self-driving electric vehicle will have the capacity to transport as many as 12 individuals at a time. Local Motors is known for creating the world's first 3D-printed car, and it has collaborated with IBM Corporation (NYSE:IBM) to introduce an equally innovative concept with its latest feature. The company unveiled Olli -- the brainchild of vehicle designer Edgar Sarmiento -- at the launch of its new facility in National Harbor, MD.

If that sounds familiar, it's because Google and Facebook have since also announced similar plans to integrate chatbots into their messaging apps. Facebook Messenger, for instance, already has bots that let you send flowers, get breaking news and go shopping without leaving the app. Wand Labs would boost Microsoft's ability to offer more in this space, given the former's experience with "third-party developer integration and conversational interfaces," according to Microsoft. Wand has shut down its messaging app, but screenshots on its website show its ability to pull up third-party services such as Yelp and YouTube from its keyboard. With the Wand application, you could even share access to apps such as Nest's smart thermostat app so the friends you're chatting with can change the temperature for themselves.

Image recognition, determining all the objects within a photo, is something Facebook's AI does with relative ease. The company's approach to machine learning is called deep learning, a popular route to AI also followed by Google and others. Deep learning employs algorithms to recognize patterns, learn from those patterns and complete sophisticated tasks. For Facebook, it could be tagging friends. For Google, it may be creating a program that plays the game Go well enough to beat human champions.

Companies like Clearpath, Fetch, and Locus Robotics are doing some amazing work in order fulfillment and other warehouse tasks by developing mobile platforms that can autonomously and intelligently ferry items between locations. We don't want to minimize how much of a challenge this is, but at the same time, it's only half of the order fulfillment problem (and not the most difficult half). The hard part is getting those robots to pick items from shelves, and apparently it's really hard: Amazon (whose warehouse robots are capable of tranporting items but not picking them) is holding its second Picking Challenge at RoboCup this year, and even with teams of researchers all collaborating on picking tasks with very expensive robots, results have been good but not inspiring. German startup Magazino is another company trying to solve both problems. It has begun deploying a mobile warehouse robot called Toru designed to not only transport items but also pick them (some of them, anyway) directly off of shelves. They haven't completely solved the problem of humans, but it's a step in the right direction.

Google is diving deeper into artificial intelligence, with the company opening a dedicated machine learning research center in its Zurich office, the search company announced on Thursday, June 16. The Google Research Europe center will focus on three areas: Machine intelligence, natural language processing, and understanding and machine perception. The research center aims to deliver machine learning that can be put into practical use, to improve the machine learning infrastructure, and to assist the research community overall. "Google's ongoing research in machine intelligence is what powers many of the products being used by hundreds of millions of people a day -- from Translate to Photo Search to Smart Reply for Inbox," Emmanuel Mogenet, head of Google Research Europe, wrote in the blog post announcing the center. Mogenet noted machine learning software engineers and researchers will be able to develop products and conduct research at the Zurich center, which also holds the largest Google engineering office outside of the US.