Old-school purists might argue that the pervasiveness of online chess has ruined the game's tactile appeal. Instead of pushing beautifully carved pieces across a painted board, most players nowadays drag and drop computer icons--a mouseclick is the only tangible element. But like something out of "Harry Potter," Square Off uses motors and magnets to glide an opponent's solid pieces over its rosewood surface, restoring an experience many players thought might be lost to technology. I bought two boards and shipped one to Danny. Paired to our smartphones via Bluetooth, the boards speak to one another over the internet.

The information age has generated far more data than humanity can ever hope to manually process, but with the help of artificial intelligence, that avalanche of data is now revealing itself to be far more useful than we ever thought possible. The omnipresent wireless signals that keep us connected can now be used like X-rays to see and track the movements of people, even when hidden behind walls. Though they're invisible to the human eye, radio waves still bounce off of human bodies as the wireless signals emanate out from broadcast antennas. How those radio signals bounce and scatter can be measured, and researchers at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) were able to train a neural network to extract the positions and movements of people as they interfere with radio frequency (RF) signals. Like babies, neural networks need to be trained on what to look for when analyzing the world.

Artificial intelligence has been taught to see people through walls, using nothing more than a radio signal 1,000 times weaker than Wi-Fi. Developed by a team of researchers at the Massachusetts Institute of Technology (MIT), the system can see the basic stick-person outline of human through a wall. It can do so with almost the same accuracy whether the wall is there or not. MIT's Computer Science & Artificial Intelligence Lab said: "The researchers use a neural network to analyze radio signals that bounce off people's bodies, and can then create a dynamic stick figure that walks, stops, sits, and moves its limbs as the person performs those actions." Called RF-Pose, the system works because radio frequencies pass through walls but reflect off humans, revealing their location in a similar way to how radar and lidar systems work.

There's no shortage of odes to the ability of athletes and high school sports teams to be the center and glue of a small town. But what if someone paid similar attention to the brainpower -- in this case the high school robotics competition and its ability to capture the hearts of that small town? In a profile in the Star Tribune in April, the Star Tribune's John Reinan said the kids are "Hoosiers with robots," a reference to the movie of an Indiana small town high school team that won a state championship. Greenbush has two of those, winning one in 2016, finishing second last year, and winning the second last month. The film will premiere at the Roso Theater in Roseau, Minn., in August.

Telltale Games has announced that it is bringing "Minecraft: Story Mode" to Netflix as an interactive show later this fall. The video game developer also revealed that it is developing an entirely new game that's based on the hit Netflix series "Stranger Things." "We're delighted by the response we're seeing to the idea of'Minecraft: Story Mode' coming to Netflix in the fall as an interactive adventure. Separately, we're thrilled to confirm that Telltale is developing a game based on'Stranger Things' that we'll publish to consoles and computers at a later date," Telltale Games said on its Twitter page. "Our partnership with Netflix is something we're incredibly proud of, and while we don't have anything more to share right now, we're excited to reveal details on these projects later in the year."

The report predicts the global humanoid robot market to grow with a CAGR of 51.7% over the period of 2018 - 2024 The report on global humanoid robot market provides qualitative and quantitative analysis for the period of 2016 to 2024 The report on humanoid robot market is a comprehensive study and presentation of drivers, restraints, opportunities, demand factors, market size, forecasts, and trends in the global humanoid robot market over the period of 2016 to 2024. Moreover, the report is collective presentation of primary and secondary research findings. Porter's five forces model in the report provides insights into the competitive rivalry, supplier and buyer positions in the market and opportunities for the new entrants in the global humanoid robot market over the period of 2016 - 2024. Further, the Growth Matrix given in the report brings an insight on the investment areas that existing or new market players can consider.

Amazon's DeepLens, a deep learning enabled video camera, is now generally available and hitting the market for $249. AWS DeepLens is designed to run models via TensorFlow and Caffe in less then 10 minute startup time for developers. The overall effort is to put more machine learning tool into the field and with developers. As for the hardware, DeepLens is a 4 megapixel camera with 1080P video, 2D microphone array, Intel Atom processor and 8GB of memory for models and code. The device runs Ubuntu 16.04, AWS Greengrass Core and optimized versions of MXNet and Intel clDNN libraries.

AI experts are worried the field is on the brink of a scenario similar to the dotcom bubble bursting. It's called an AI winter. And, if it happens, it could leave a lot of researchers, investors, and entrepreneurs out in the cold. Such a scenario could happen for a number reasons, and its effects could vary wildly depending on how poorly the investments in the space end up performing. But before we dive into all of that, it's important to understand that there's no official Bubble Czar out there determining when it's time to head for the lifeboats. The problem with bubbles is you can never tell when they're going to burst – or even if you're in one.

We present a method for estimating causal effects in time series data when fine-grained information about the outcome of interest is available. Specifically, we examine what we call the split-door setting, where the outcome variable can be split into two parts: one that is potentially affected by the cause being studied and another that is independent of it, with both parts sharing the same (unobserved) confounders. We show that under these conditions, the problem of identification reduces to that of testing for independence among observed variables, and present a method that uses this approach to automatically find subsets of the data that are causally identified. We demonstrate the method by estimating the causal impact of Amazon's recommender system on traffic to product pages, finding thousands of examples within the dataset that satisfy the split-door criterion. Unlike past studies based on natural experiments that were limited to a single product category, our method applies to a large and representative sample of products viewed on the site. In line with previous work, we find that the widely-used click-through rate (CTR) metric overestimates the causal impact of recommender systems; depending on the product category, we estimate that 50-80\% of the traffic attributed to recommender systems would have happened even without any recommendations. We conclude with guidelines for using the split-door criterion as well as a discussion of other contexts where the method can be applied.

Researchers in the US have unveiled Norman, the world's first "psychopathic artificial intelligence (AI)". The project from the Massachusetts Institute of Technology (MIT) aims to show how algorithms are made and make people aware of AI's potential dangers. Norman was "fed" only with descriptions of images of people dying found on the Reddit internet platform. Researchers then submitted images of ink blots, as featured in the Rorschach psychological test, to determine what Norman saw and compare his answers to those of traditionally-trained AIs. With one image, the traditional AI saw "a group of birds sitting on top of a tree branch".