In binary classification problems such as predicting probability of churn or probability of default, it makes sense to have a time-series dataset (multiple observations for each account, with each observation representing a unique point-in-time). I imagine this dataset structure violates standard logistic regression, but could more advanced regression forms (such as generalized linear mixed models) or tree-based algorithms handle this type of dataset structure?

Online learning may refer to the ones with batch size to be 1, but here I mean online reinforcement learning is the RL where the agent is updated at every timestep. Naively speaking, the concept of online reinforcement learning sounds very much like how human learns, and it's very effective for tasks like stochastic games. Since it performs an update at each timestep, the agent may be more robust under the circumstances such that the current state is relatively unfamiliar. As it was updated in the past ten or so timesteps which are close to the current timesteps, the agent is more adapted to the unfamiliar current states. Also, the weights of the agent may be considered to be conditioned on the past events in the same episode, which may alleviate the issue of LSTM and memory network, that is, they still has the limit on the extent to which they can remember the distant past events in the same episode.

Carnegie Mellon University will lead a $27.5 million Semiconductor Research Corporation (SRC) initiative to build more intelligence into computer networks. Researchers from six U.S. universities will collaborate in the CONIX Research Center headquartered at Carnegie Mellon. For the next five years, CONIX will create the architecture for networked computing that lies between edge devices and the cloud. The challenge is to build this substrate so that future applications that are crucial to IoT can be hosted with performance, security, robustness, and privacy guarantees. "The extent to which IoT will disrupt our future will depend on how well we build scalable and secure networks that connect us to a very large number of systems that can orchestrate our lives and communities. CONIX will develop novel architectures for large-scale, distributed computing systems that have immense implications for social interaction, smart buildings and infrastructure, and highly connected communities, commerce and defense," said James H. Garrett Jr., dean of Carnegie Mellon College of Engineering.

A comedic adventure flick about being teleported into a video game outplayed a political drama over the four-day MLK weekend as "Jumanji: Welcome to the Jungle" landed at the top of the domestic box office. The Sony movie outpaced "The Post," about the Washington Post's 1971 decision to publish the Pentagon Papers. In its fourth week of release, "Jumanji: Welcome to the Jungle" added an estimated $35.4 million, for a cumulative $291.6 million, according to numbers from measurement firm comScore. It's on track to become one of Sony's top five domestic releases of all time. "The film shows the strong drawing power of Dwayne Johnson and Kevin Hart in this reboot of the original'Jumanji' that opened way back in December of 1995," said comScore senior media analyst Paul Dergarabedian.

AI Robot, Sophia, became the first robot citizen. But was there more to the story and, although impressive and featuring genuine AI, do the animatronic features of Sophia suggest the goal here is the appearance of humanity – rather than an extension of it? This caused widespread uproar amongst human rights groups and on social media, and it was picked up by many of the big media outlets, but it turns out that the whole affair was mainly a PR stunt. The eye-grabbing headlines were a well strategised ploy to promote a tech summit in Saudi Arabia, but some experts say this sort of approach to robot rights is actively damaging, both to public understanding of technology and to civil society itself. So what about Sophia's amazing conversational abilities that led to the robot having an argument with Elon Musk?

Danish toymaker Lego is teaming up with Chinese internet giant Tencent to jointly develop online games and potentially a social network aimed at Chinese children. Privately-owned Lego has seen a slowdown in sales growth in recent years, but the Chinese market has been a bright spot with sales growing 25-30 per cent in 2016. It is competing with Barbie maker Mattel and Hasbro, the firm behind My Little Pony, for a slice of the $31bn (£22bn) toys and games market in China. Lego said on Monday the partnership with Tencent, China's biggest social network and gaming company, aimed to create a safe online environment covering content, platforms, and experiences tailored for Chinese children. "What we are looking for now with Tencent is just to find more creative ways... (of) reaching children, and creating bespoke content with Tencent, in this case, video games," Jacob Kragh, head of Lego in China, told Reuters on Monday at joint event with Tencent in Beijing. The partnership includes developing a Lego video zone for children on the Tencent video platform, as well as developing and operating Lego branded licensed games, the toymaker said.

Hi, I am new to machine learning. I have an input data with huge amount of features around 20200. I want to check which features survived after each layer. Are there any way to check this on tensorflow?

Fujitsu Ltd. said Monday that it will provide the Shinano Mainichi Shimbun, a regional Japanese newspaper, with a system that automatically summarizes articles using artificial intelligence. Using the system developed by the electronics maker, summarizing jobs will be finished in an instant, versus 3 to 5 minutes per article if done by hand, according to Fujitsu. The newspaper's publisher, based in Nagano, will use the system in its news distribution services for cable TV starting in April. The Shinano Mainichi Shimbun currently delivers some 60 summarized reports each day that are a maximum of 150 characters long for CATV viewers in the prefecture. In developing the system, Fujitsu applied machine learning to about 2,500 sets of past newspaper articles and their summaries so the system could become capable of picking out important sentences within an article.

Artificial intelligence (AI) is suddenly everywhere. From phones and TVs to air conditioners and even a toilet, the flashy new products at the year's CES (Consumer Electronics Show) in Las Vegas - the world's largest tech show - are showing the 180,000 attendees that if a device doesn't have AI inside, it's not worth having. At least, that's what they're being led to believe. Have you ever decided to buy a smartphone because it had AI inside? Probably not, but next time you buy a handset it's likely to be a major factor. Huawei kicked it off a few months ago with its Mate 10, claiming the phone's NPU (neural processing unit) would enable smart photography and machine translation.

Noise and misinformation, especially on climate, has long been a problem on social media. To counter this, Australian not-for-profit the Climate Council has created a Facebook Messenger chatbot to inform people about climate science. Launched on its Facebook page last week, it's an effort to connect with younger people who are interested in issues like climate change, but aren't the most engaged with the organisation -- largely due to broader information overload. "Young people are saturated on social media because they're the most active on it, we know that they care and that they've got the thirst for information," Nelli Huié, digital manager at the Climate Council, explained. "But because they've got the highest use of social media, they've got the most voices clamouring to reach them through the News Feed. It can be a real challenge for us to cut through that noise."