Self-driving cars are a focus for a lot of tech companies, but in Europe, a group of companies are working to bring self-driving technology to an unexpected area: the ocean. Two companies in Norway are working on an autonomous shipping boat that wouldn't need a human crew. Firms Yara International ASA and Kongsberg Gruppen are developing the Yara Birkeland and want to begin test runs with the boat starting in 2018, according to the Wall Street Journal. According to Kongsberg Gruppen, the ship will have a storage capacity of 100 to 150 twenty-foot equivalent units and will feature batteries as a major power source. The ship will use Lidar, cameras, radars and other physical sensors to power its autonomous functions.

Regarding Fear and Artificial Intelligence (AI), one question often comes up:'Will we be killed by a Terminator Doppelganger?' I don't know if this will happen eventually, but I do know that we already have robots fighting our wars. This century is therefore, the first time in human history that we engage in Unmanned Warfare. What is the current status of this'Unmanned Warfare'? What do people think about drone strikes and will terminators be the next step?

DoNotPay, an AI-based chatbot app created to help fight parking tickets in the UK, now addresses roughly 1,000 consumer concerns and is available throughout the United States as well as across the pond. The app's creator, Stanford University student Joshua Browder, announced the expansion last week. Powered by IBM Watson, DoNotPay has about 1,000 bots capable of tackling a variety of legal and service issues, ranging from fighting one's landlord to appealing against unreasonable warranties, to getting a refund when a company doesn't fulfill its promise. The app lets users use a feature similar to instant messaging to get help. When opened, the app presents a blue screen that asks what it can help the user with, and offers a search field in which the user can type a response.

In the near future, the camera will be able to recognize images and communicate that data with other Si500s. For example, if a cop were seeking a missing child, the body cam could learn the infant's likeness from an image. That info would then be automatically distributed to other officers wearing the device, allowing them to take part in the search. Neurala claims that its AI will even be able to pick out a person of interest in crowded public spaces. Of course, using AI-integrated surveillance systems does pose concerns over public privacy and the potential misuse of the tech.

Earlier this year, it was reported that an artificial intelligence (AI) robot called Libratus won $1.5m worth of chips from four of the world's top poker players in a three-week challenge. Whilst this might be seen as a crushing defeat for mankind, it is a huge leap for AI. Machine learning isn't a brand new concept and when we look specifically at the financial services (FS) sector, its noticeable that it has always been one of the lead drivers of new technology trends with data analytics, mobile banking and new payment methods. However, with the next wave of technology disruption set to come from AI, how can banks and FS providers ensure they exploit the benefits? Despite the FS market being generally seen as leaders when implementing new technology, some are still struggling with legacy tech such as cloud platforms and applications.

WARNING - GRAPHIC CONTENT: You may find some of these images distressing. When James Andrews' friend invited him over to the beach earlier this month to try out his drone, it appeared to be any regular Saturday. It was James' first experience with the small unmanned aircraft but it ended in disaster, nearly blinding him and leaving him with serious injuries. "It all happened so quickly. I didn't realise what it could actually do," James, 43, told the BBC.

Most machine learning is literally prejudice--telling a machine, "based on what you've seen in the past, predict the future." But what do we do when it's also correct? Many of the most popular examples of "artificial intelligence" today are actually about classification. For example, we can show a computer past pictures of dogs, and have it predict whether a new picture is a dog (or a pastry.) We can also use those predictions to do things like mimic an art style, or try and anticipate what word will come next in a sentence, or suggest people with whom you might want to connect.

The "deep artificial composer", or "DAC" for short, generates brand-new melodies that imitate traditional folk music of Irish or Klezmer origin. It does so without plagiarizing already existing ones, since melodies it writes are as original as those produced by a human composer. The results were presented in April at this year's edition of the Evostar conference. The DAC actually produces musical scores of melodies, symbolic music written using notation, and does not generate audio files. The deep artificial composer can produce complete melodies, with a beginning and an end, that are completely novel and that share features that we relate to style," says Swiss Federal Institute of Technology in Lausanne (EPFL) scientists Florian Colombo who developed the artificial intelligence under the guidance of Wulfram Gerstner, director of the Computational Neuroscience Laboratory. "To my knowledge, this is the first time that an artificial neural network model has produced entire and convincing melodies.

The next time you come across a picture of a ravishing dish on Instagram or WeChat that whets your appetite but you can't exactly make out what it is made of, don't wrack your brain trying to guess the recipe. An AI system unwrapped earlier this week helps those with culinary curiosity find the right ingredients of an unknown dish and offers step-by-step instructions how to make it just by analyzing a photo they upload online. Researchers from the Polytechnic University of Catalonia, Massachusetts Institute of Technology (MIT) and Qatar Computing Research Institute have developed a deep-learning algorithm that can whip out a recipe just by "looking" at a photo of the dish. They fed the neural network one million recipes, along with one million photos of their final outcome, from popular websites like Allrecipes.com and Food.com to create a huge database they dubbed, Recipe1M, accessible through a web portal they called Pic2Recipe. With a single click of a button, the website allows users to upload a photo of the mystery dish and then the system, using machine learning, goes through the massive mounds of data to analyze it. It then predicts a list of possible ingredients along with their relevant recipes, then ranks them based on how certain the AI is they match the image.

If Beijing has its way, the future of artificial intelligence will be made in China. The country laid out a development plan on Thursday to become the world leader in A.I. by 2030, aiming to surpass its rivals technologically and build a domestic industry worth almost $150 billion. Released by the State Council, the policy is a statement of intent from the top rungs of China's government: The world's second-largest economy will be investing heavily to ensure its companies, government and military leap to the front of the pack in a technology many think will one day form the basis of computing. The plan comes with China preparing a multibillion-dollar national investment initiative to support "moonshot" projects, start-ups and academic research in A.I., according to two professors who consulted with the government about the effort. The United States, meanwhile, has cut back on science funding.