Google’s AI scientists showed that you can get better image recognition results by feeding …

Google CEO Sundar Pichai delivers the keynote address at the Google I/O 2017 Conference at Shoreline Amphitheater on May 17, 2017 in Mountain View, California. Justin Sullivan/Getty Images A recent artificial intelligence (AI) experiment Google conducted in partnership with Carnegie Mellon University (CMU) showed that it’s possible to get far better image recognition results simply by feeding algorithms a lot more data, according to a Wired report. Google released a new paper last week outlining the principles behind the experiment. Machine learning algorithms learn to better perform a particular task by munching through enormous quantities of data, but so far the amount of data the major AI experiments have been conducted with has remain mostly unchanged. Image recognition software usually works with a collection of about 1 million pictures, and AI scientists questioned whether merely tweaking the machine learning algorithms could return better, more accurate results. “While both GPUs and model capacity have continued to grow, datasets to train these models have remained stagnant. Even a 101-layer ResNet with significantly more capacity and depth is still trained with 1M images from ImageNet circa 2011,” reads the paper. “Why is that? Have we once again belittled the importance of data in…


Link to Full Article: Google’s AI scientists showed that you can get better image recognition results by feeding …

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