In 2012, Google made a breakthrough: It trained its AI to recognize cats in YouTube videos. Google’s neural network, software which uses statistics to approximate how the brain learns, taught itself to detect the shapes of cats and humans with more than 70% accuracy. It was a 70% improvement over any other machine learning at the time.
Make no mistake, we are living in the future. We can store millions of files into a piece of hardware the size of our pinky nail. We can converse face-to-face while thousands of miles away from each other. We have cars that can drive themselves. We have personal computers and entertainment systems built into tiny phones that fit into our pockets. We have amazing robots that can run, swim, fly, and speak.
Source: A.I. Writes a Screenplay, Screenwriters Breathe a Sigh of Relief | HuffPost
Are you thinking of Chappie, Terminator, and Lucy? Sentient, self-aware robots are closer to becoming a reality than you think. Developing computer systems that equal or exceed human intelligence is the crux of artificial intelligence. Artificial Intelligence (AI) is the study of computer science focusing on developing software or machines that exhibit human intelligence. A simple enough definition, right?
Source: Artificial Intelligence 101: How to Get Started | HackerEarth Blog
The platform war over machine learning tools is heating up. Use our features comparison chart to see how four top vendors stack up and help you decide which is right for your enterprise.
Source: Machine learning platforms comparison: Amazon, Azure, Google, IBM
Three main players of business cloud services have an array of products covering all you can possibly need for your online operations. But there are differences not only in pricing but also in how they name and group their services, so let’s compare one next to another and find out what they offer.
Source: A Side-by-Side Comparison of AWS, Google Cloud and Azure — SitePoint
As Earth-observing satellites become more plentiful and climate models more powerful, researchers who study global warming are facing a deluge of data. Some are now turning to the latest trend in artificial intelligence (AI) to help trawl through all the information, in the hope of discovering new climate patterns and improving forecasts.
Source: How Machine Learning Could Help to Improve Climate Forecasts – Scientific American
Fears about the impact of technology on jobs have resurfaced periodically ever since. The latest bout of anxiety concerns the arrival of artificial intelligence (AI). Once again, however, technology is creating demand for work. To take one example, more and more people are supplying digital services online via what is sometimes dubbed the “human cloud”. Counter-intuitively, many are doing so in response to AI.
Source: Artificial intelligence will create new kinds of work
The cloud is getting smarter by the minute. In fact, it will soon know more about the photos you’ve uploaded than you do. Cloud storage company Box announced today that it is adding computer-vision technology from Google to its platform. Users will be able to search through photos, images, and other documents using their visual components, instead of by file name or tag. “As more and more data goes into the cloud, we’re seeing they need more powerful ways to organize and understand their content,” says CEO.
AI may be key in preventing contaminated drugs, according to the Director of Xavier Health Marla Phillips. “It can recognize connections from data that might seem irrelevant to a human and identify that it is producing a signal that could lead to a flawed product. Humans would otherwise let it go undetected.”
Source: Using Artificial Intelligence To Keep Drugs Safe | WOSU Radio
Doctors are often deluged by signals from charts, test results, and other metrics to keep track of. It can be difficult to integrate and monitor all of these data for multiple patients while making real-time treatment decisions, especially when data is documented inconsistently across hospitals.In a new pair of papers, researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) explore ways for computers to help doctors make better medical decisions.
Source: Using machine learning to improve patient care | MIT News
