IBM Japan has teamed up with Subaru to investigate how its Watson Supercomputer could help improve the automaker's EyeSight driver assist technology. As well as developing a data analytics system, the two companies are keen to integrate cloud and artificial intelligence technologies, which bodes well for the ongoing development of autonomous, networked cars. The benefits of networked autonomous vehicles were recently demonstrated by the European Truck Platooning Challenge, where teams of autonomous trucks made their way from their respective factories to Rotterdam. As well as demonstrating the fact autonomous vehicles can effectively make long trips without causing the end of the world (shocking, we know), the trucks were able to maintain a gap of just 15 m (49 ft) and react to sudden braking manoeuvres in just 0.1 seconds thanks to a WiFi connection keeping them all linked. Daimler has also invested in Car-to-X technology, which features in its latest E-Class.

Walking across the floor of SEW-Eurodrive's factory in Baden-Württemberg is like moving through a time warp. On one side, the light is dim and workers stand at long assembly lines repeating the same task over and over. On the other, a fleet of low-lying robotic trucks scoot around the shop floor, restocking restyled workstations. In these small cells, a single employee helped by a robotic workbench assembles a virtually complete drive system that will be used to power the production of everything from cars to cola. Elsewhere, a robotic arm called Carmen helps workers load machines or pick components out of bins.

There's huge progress in AI, or at least huge interest in AI--a bigger interest than there's ever been in my lifetime. I've been interested in AI since I was a little kid trying to program computers to play chess, and do natural language databases, and things like that, though not very well. I've watched the field and there have been ups and downs. There were a couple of AI winters where people stopped paying attention to AI altogether. People who were doing AI stopped saying that they were in the field of AI. They say, "Yes, I do artificial intelligence," where two years ago they would have said, "I do statistics." Even though there's a lot of hype about AI and a lot of money being invested in AI, I feel like the field is headed in the wrong direction. There's been a local maximum where there's a lot of low-hanging fruit right now in a particular direction, which is mainly deep learning and big data. People are very excited about the big data and what it's giving them right now, but I'm not sure it's taking us closer to the deeper questions in artificial intelligence, like how we understand language or how we reason about the world. The big data paradigm is great in certain scenarios. One of the most impressive advances is in speech recognition. You can now dictate into your phone and it will transcribe most of what you say right most of the time. That doesn't mean it understands what you're saying. Each new update of Siri adds a new feature. First, you could ask about movie times, then sports, and so forth. The natural language understanding is coming along slowly. You wouldn't be able to dictate this conversation into Siri and expect it to come out with anything whatsoever. But you could get most of the words right, and that's a big improvement. It turns out that it works best with a lot of brute force data available. When you're doing speech recognition on white males, who are native language speakers, in a quiet room, it works pretty well.

Acquiring Expertmaker is part of eBay's structured data push to better organize products on its marketplace. EBay Inc. took another step this week to better organize its product data and make items easier to find when the online marketplace acquired a Swedish company focused on artificial intelligence, machine learning and big data analytics. EBay bought Malmo, Sweden-based Expertmaker, which has worked with eBay since 2010 and also has offices in San Francisco. When the transaction is final, Expertmaker employees will become part of eBay's structured data product and technology team, with founder and CEO Lars Hard joining as director, data science, according to eBay. The online marketplace continues to press its initiative to have sellers define their products using structured data, which means characterizing items in a standard way.

Merging beliefs requires the plausibility of the sources of the information to be merged. They are typically assumed equally reliable in lack of hints indicating otherwise; yet, a recent line of research spun from the idea of deriving this information from the revision process itself. In particular, the history of previous revisions and previous merging examples provide information for performing subsequent mergings. Yet, no examples or previous revisions may be available. In spite of the apparent lack of information, something can still be inferred by a try-and-check approach: a relative reliability ordering is assumed, the merging process is performed based on it, and the result is compared with the original information. The outcome of this check may be incoherent with the initial assumption, like when a completely reliable source is rejected some of the information it provided. In such cases, the reliability ordering assumed in the first place can be excluded from consideration. The first theorem of this article proves that such a scenario is indeed possible. Other results are obtained under various definition of reliability and merging.

Biological systems are often modelled at different levels of abstraction depending on the particular aims/resources of a study. Such different models often provide qualitatively concordant predictions over specific parametrisations, but it is generally unclear whether model predictions are quantitatively in agreement, and whether such agreement holds for different parametrisations. Here we present a generally applicable statistical machine learning methodology to automatically reconcile the predictions of different models across abstraction levels. Our approach is based on defining a correction map, a random function which modifies the output of a model in order to match the statistics of the output of a different model of the same system. We use two biological examples to give a proof-of-principle demonstration of the methodology, and discuss its advantages and potential further applications.

The winner for our second data science competition is Tom De Smedt, biostatistician completing a Ph.D program at University of Leuven, Belgium. His special interests are in spatial statistics, environmental epidemiology, novel regression techniques and data visualization. The competition consisted of simulating data and testing the Jackknife regression technique recently developed in our laboratory, on correlated features or variables. The technique provides an approximation to standard regression, but is far more robust and deemed suitable for automated or black-box data science. The easiest version consists of pretending that variables are uncorrelated, to very quickly obtain robust regression coefficients that are easy to interpret.

While many video games are pushing their stories toward the future, the classic franchise Battlefield is stepping back to revisit the past. Publisher Electronic Arts announced Battlefield 1, the latest chapter in the military action series that will take players to the battlefields of World War I. It launches October 21 for PC, PlayStation 4 and Xbox One. The game will take place across multiple locations around the world, including France, the Italian Alps and the deserts of Arabia. Battlefield 1's story kicks off right around the start of World War I, as players "witness the birth of modern warfare."

The e-commerce giant has been working with Expertmaker since 2010 to organise and crunch massive data sets. It will join eBay's structured data product and technology team. Financial terms of the deal were not disclosed. Amit Menipaz, vice president and general manager of structured data at eBay, said Expertmaker's expertise woulid help the auction site build a "best-in-class product catalogue". On its website, Expertmaker says that its "genetics-inspired multi-AI approach extracts hidden value in your data, turning chaotic and unstructured data into actionable knowledge to predict outcomes and optimize your business", which is handy considering eBay has more than 900 million listings scattered throughout its online catalogue.

Trash can be sticky, stinky, and sharp. The entrepreneurs at Jodone want to turn this mundane task into a human-robot collaborative game to improve efficiency and accuracy. For Jodone's new pilot project at the Pope/Douglas waste-to-energy facility in Alexandria, Minnesota, human operators will use its software to monitor waste as it travels along a conveyor belt. Using a touch screen, workers will swipe any recyclables they spot and then select the appropriate category: paper, plastic, tin, etc. Those instructions will be sent wirelessly to robotic arms that will grab the recyclables and drop them in the correct bin.