Today on In Case You Missed It: Robots have finally gotten around the'needing human assistance' thing when it comes to sewing clothing. The Sewbo is one such option, which can stitch together clothing as long as the garment is first dipped in a stiffening solution that makes it feel like cardboard. Meanwhile MIT's Computer Science and Artificial Intelligence Lab created a computer program made to simplify the process of 3D-printing with different materials in the same object. News about the Foundry is here. The video we can't stop watching from Russia is here.

President Barack Obama envisions AI as the next Apollo program--an 80 billion effort shepherded by the US government. In his interview with WIRED Editor-in-Chief Scott Dadich and MIT Media Lab director Joi Ito, President Obama said that the government should facilitate a range of research in artificial intelligence. "The way I've been thinking about the regulatory structure as AI emerges is that, early in a technology, a thousand flowers should bloom," he says. "The government should add a relatively light touch, investing heavily in research and making sure there's a conversation between basic research and applied research." That means the government should help provide a path for getting AI into the real world.

Here I put together a number of new data science techniques to solve a real life problem: identifying good articles to write and publish (or to harvest and re-post) on a website, and re-tweet them with the optimum frequency, given a specific audience. The focus is on scoring articles based on selected features (keywords in subject line, author, channel and many more), feature selection, data generation and harvesting to solve the problem, automatically categorizing and tagging articles using indexation algorithms, and predicting the lifetime value and total page views of an article. We also discuss bucketisation, and use both hidden decision trees and jackknife regression for scoring articles. The methodology applies to many contexts, not just digital publishing. It applies to situations in which a lot of unstructured text data needs to be processed (categorized and scored using natural language processing methods).

Since 1956, when computer science researchers gathered in the small town of Hanover, N.H. at Dartmouth College to talk about the field's nascent investigations into artificial intelligence, both government and industry in the U.S. have grappled with how to structure a systematic approach to research and development in the newly important field. From the government's perspective, this is increasingly important. With both federal research institutions and private companies pursuing artificial intelligence breakthroughs at breakneck speed, the federal government is frankly having a bit of an existential crisis about its role in research efforts and the priorities it has for what AI research should look like. To wit, in 2015 government spending on unclassified research and development in AI-related technologies was around 1.1 billion, according to one of the twin reports released today. But in the last five years alone, mergers and acquisitions among private companies vying for dominance in the AI market have far outstripped that figure, according to data from CB Insights.

Over the past four years, readers have doubtlessly noticed quantum leaps in the quality of a wide range of everyday technologies. Most obviously, the speech-recognition functions on our smartphones work much better than they used to. When we use a voice command to call our spouses, we reach them now. We aren't connected to Amtrak or an angry ex. In fact, we are increasingly interacting with our computers by just talking to them, whether it's Amazon's Alexa, Apple's Siri, Microsoft's Cortana, or the many voice-responsive features of Google.

Recent news about Google, Microsoft, Facebook and other tech giants teaming up to advance the capabilities of AI only confirms that the next generation of technology is going to be focused on machine learning. With artificial intelligence being at the core of all the new and upcoming programs and technologies, you can only stay relevant if you start learning about it now. Stay ahead of the pack with The Complete Machine Learning Bundle, which is now available for a special price of 25 only. The offer is valid for 24 hours, so grab the deal from WCCFtech Deals while it lasts.

Vox tech writer Timothy B. Lee used to be one of the most ardent techno-optimists. But he's had a bit of a conversion, of late, and is now on the side of those who think tech progress is slowing. Maybe it was the economist Robert Gordon who convinced him, or maybe years of observing the tech world changed his mind. In any case, Lee now broadly suggests that the inventions of tomorrow won't be as world-changing as those of yesteryear. There are a number of industries -- with health care and education being the most important -- where there's an inherent limit on how much value information technology can add.

Oracle, like so many other enterprise IT specialists, is talking up plans to integrate machine learning into its software. What the Redwood City giant hopes will set it apart from competitors is the way it plans to use those features. Where rivals have been touting AI and machine learning as a way to overhaul and redefine platforms, Oracle hopes that its Adaptive Intelligence features will instead complement its other cloud compute offerings. Introduced last month at the annual OpenWorld conference in San Francisco, Adaptive Intelligence will look to tie machine learning into Oracle's cloud to make features more personalized and better suited for individual companies. Part of Oracle's approach is based on the availability of data it has to feed into the machine learning system.

Start developing applications with advanced AI and computer vision today using NVIDIA's deep learning tools, including TensorRT and DIGITS. Webinar access will be emailed to you. Sign up anyway to get the recording! A renowned GPGPU developer and systems architect, Dustin Franklin works to deploy CUDA-accelerated embedded applications and solve challenging sensor processing problems on Jetson, NVIDIA's low-power, high-performance embedded platform. Dustin and his team utilize the parallel compute horsepower of NVIDIA GPUs for real-time computer vision, autonomous navigation, and other toolsets, to enable new product categories and industries.

Leading UK MPs are calling on the government to set up a commission on artificial intelligence (AI) to examine the potential problems the technology could create for future generations. A report into the issue by the House of Commons science and technology committee, which was chaired by MP Dr Tania Mathias warned that the government is failing to prepare for how AI will "fundamentally" change people's lives. The research concluded that there is no strategy for developing the new skills workers will need to succeed as AI becomes more popular, and cautioned that more must be done to tackle the ethical and social problems posed by the advent of robots. "Concerns about machines'taking jobs' and eliminating the need for human labour have persisted for centuries. Nevertheless it is conceivable that we will see AI technology creating new jobs over the coming decades while at the same time displacing others," said Mathias. Dr Cotton-Barratt from the Future of Humanity Institute, who is quoted in the report, said that the UK is "well-positioned" to respond to this challenge.