Experiments at the Large Hadron Collider (LHC), the world's largest particle accelerator at the European particle physics lab CERN, produce about a million gigabytes of data every second. Even after reduction and compression, the data amassed in just one hour is similar to the data volume Facebook collects in an entire year – too much to store and analyze. Luckily, particle physicists don't have to deal with all of that data all by themselves. They partner with a form of artificial intelligence called machine learning that learns how to do complex analyses on its own. A group of researchers, including scientists at the Department of Energy's SLAC National Accelerator Laboratory and Fermi National Accelerator Laboratory, summarize current applications and future prospects of machine learning in particle physics in a paper published today in Nature.

Andrew Ng is a great fan of reading research papers as a long term investment in your own study (On Life, Creativity, And Failure about Andrew Ng). Anyone who has worked in our field (AI, Machine Learning) can attest to that. AI is a complex and a rapidly evolving field. It's a challenge to stay up to date with the latest technical details. Based on my experience, in this post, I discuss how you can stay up to date by learning from the community.

"NLP.js" is a general natural language utilities for nodejs. If you're looking to use NLP.js in your node application, you can install via NPM like so: You can see a great example of use at the folder \examples\console-bot. This example is able to train the bot and save the model to a file, so when the bot is started again, the model is loaded instead of trained again. There are several languages supported. The language support can be for the Stemmers or for Sentiment Analysis.

Coming-of-age technology, known as artificial intelligence, is blowing a heavy wind across the world, raising dust in various spheres and generating intellectual discourse among scholars about the fate of humanity. The assertion that "robots are taking over" is a bitter pill to swallow as it creates panic among employees. The 2017 McKinsey Global Institute Report reiterates this assertion, revealing that, by 2030, a good number of people will be forced to acquire new skills because their jobs will be performed by machines. Findings from WorkMarket's 2020 In(Sight) Report: What AI and Automation Really Mean for Work reveal that employers may not be bothered, on the contrary, if they are open to the prospects of artificial intelligence in the workplace. Seventy-eight percent of business leaders believe that 360 hours can be saved annually by the input of automation through artificial intelligence.

Test subjects paired with mean robots were faster and made fewer mistakes than those paired with friendly ones or with no robot. Researchers at the University of Clermont Auvergne in France say a mean robot could motivate human employees to improve their cognitive performance, compared to supervision by a friendly robot or no robot supervision. The team employed the Stroop task, a test in which words printed in different colors are displayed on a screen, with test subjects required to identify the color while ignoring the word. Into this task Clermont Auvergne's Nicolas Spatola and colleagues presented a humanoid robot perceived either as friendly or mean. Participants paired with mean robots were faster and made fewer errors than those paired with friendly ones or with no robot at all.

Tech industry insiders regularly herald AI as the solution to all of our problems, included those posed by health care. London-based DeepMind, owned by Google's parent company, Alphabet, focuses heavily on the specifics of using artificial intelligence in health care, and on Monday it released a study showing the progress it's made in using AI to diagnose eye conditions. Published in the science journal Nature Medicine, the study reports that DeepMind, in partnership with Moorfields Eye Hospital in London, has trained its algorithms to detect over 50 sight-threatening conditions to the same accuracy as expert clinicians. In a project that began two years ago, DeepMind trained its machine learning algorithms using thousands of historic and fully anonymized eye scans to identify diseases that could lead to sight loss. According to the study, the system can now do so with 94 percent accuracy, and the hope is that it could eventually be used to transform how eye exams are conducted around the world.

Focused and targeted agenda to fuel your AI plans – Gather with the brightest minds in insurance – from data and analytics C-level executives to core business leaders – and delve into the complexities of AI and machine learning. Don't get left behind in the race for next-generation analytics Exclusive Practical Case Studies Delivered by Insurance Leaders: From automation to customer-facing innovation, this is your opportunity to hear how insurers are deploying AI into core business areas, including underwriting and pricing, claims, and customer engagement, so you can walk away with the knowledge and tools you need to drive enterprise-wide AI Uniting pricing, marketing, analytics experts and more, with insurtech – Focusing on the core areas that are set to benefit most, plus representation from innovative start-ups, you'll get to rub shoulders with the people who are truly transforming our industry Guaranteed to deliver on learning and networking: The agenda was specifically designed to help you make the most of the 2-day summit. With 0ver 10 different interactive sessions and 8 hours of enhanced networking with Brella, can you afford to stay out of the AI revolution? Focused and targeted agenda to fuel your AI plans – Gather with the brightest minds in insurance – from data and analytics C-level executives to core business leaders – and delve into the complexities of AI and machine learning. Don't get left behind in the race for next-generation analytics Uniting pricing, marketing, analytics experts and more, with insurtech – Focusing on the core areas that are set to benefit most, plus representation from innovative start-ups, you'll get to rub shoulders with the people who are truly transforming our industry Guaranteed to deliver on learning and networking: The agenda was specifically designed to help you make the most of the 2-day summit.

Michaela Cordova, a research associate and lab manager at Oregon Health and Science University, begins by "de-metaling": removing rings, watches, gadgets and other sources of metal, double-checking her pockets for overlooked objects that could, in her words, "fly in." Then she enters the scanning room, raises and lowers the bed, and waves a head coil in the general direction of the viewing window and the iPad camera that's enabling this virtual lab tour (I'm watching from thousands of miles away in Massachusetts). Her voice is mildly distorted by the microphone embedded in the MRI scanner, which from my slightly blurry vantage point looks less like an industrial cannoli than a beast with a glowing blue mouth. I can't help but think that eerie description might resonate with her usual clientele. Original story reprinted with permission from Quanta Magazine, an editorially independent publication of the Simons Foundation whose mission is to enhance public understanding of science by covering research developments and trends in mathematics and the physical and life sciences.

In our prior The World's Most Disruptive Technology (That No One Is Talking About) post we portrayed the promise and peril of a potent new gene-altering technology. Since our CRISPR post, we've been tracking another technology development equally deserving of legal scrutiny, due to it's potential to "change everything" according to one prominent thinker who knows a thing about disruptive technology. However, unlike CRISPR's promise to fundamentally alter the basic structures of human life (i.e. Deep dive with me, if you dare, into the subzero world of quantum computers. How Cold Is Quantum Computing? Imagine a computer so powerful it could instantly crack any level of data encryption.

The US Department of Defense's recently established Joint Artificial Intelligence Center (JAIC) has finally debuted and will oversee the Pentagon's AI strategy. After a couple of years' worth of paperwork drills, Deputy Defense Secretary Patrick Shanahan released a document at the end of June establishing the JAIC, and stating it would take the next 30 days to figure out what its national mission objectives and personnel needs are. The specifics of how the center will carry out its duties going forward haven't been publicly released, but that's par for the course when dealing with military strategy. Let's just all keep our fingers crossed that whatever defense strategy the Pentagon eventually comes up with is comparable to those of other countries, such as China and Russia, who are all-in on AI at the state level. Because the White House, so far, has dealt with artificial intelligence (and STEM programs in general) by letting big tech do whatever it wants.