…findings from a group of experts were published in an ongoing effort to help answer those questions. The experts include members of Harvard, MIT, Stanford, the nonprofit OpenAI, and the Partnership on AI industry consortium, among others, and they were put together as part of the second annual AI Index.
“There is no AI story without global perspective. The 2017 report was heavily skewed towards North American activities. This reflected a limited number of global partnerships, not an intrinsic bias,” reads the 2018 report’s introduction. “This year, we begin to close the global gap. We recognize that there is a long journey ahead — one that involves collaboration and outside participation — to make this report truly comprehensive.”
In that spirit of global analysis, the second AI Index report finds that commercial and research work in AI, as well as funding, is exploding pretty much everywhere on the planet. There’s an especially high concentration in Europe and Asia, with China, Japan, and South Korea leading Eastern countries in AI research paper publication, university enrollment, and patent applications. In fact, Europe is the largest publisher of AI papers, with 28 percent of all AI-related publications last year. China is close behind with 25 percent, while North America is responsible for 17 percent.
When it comes to the type of AI activity, the report finds that machine learning and so-called probabilistic reasoning is far and away the leading research category by a number of published papers.
Not far behind, however, is work on computer vision, which is the foundational sub-discipline of AI that’s helping to develop self-driving cars and power augmented reality and object recognition, and neural networks, which, like machine learning, are instrumental in training those algorithms to improve over time. Less important, at least in the current moment, are areas like natural language processing, which is what lets your smart speaker understand what you’re saying and respond in kind, and general planning and decision making, which is what will be required of robots when automated machines are inevitably more integral facets of daily life.
China is heavily focused on agricultural science, engineering, and technology, while Europe and North America are focused more on the humanities and medical and health sciences, though Europe is generally more well-rounded in its approach to research.
As far as performance goes, AI continues to skyrocket, especially in fields like computer vision. By measuring benchmark performance for the widely used image training database ImageNet, the report finds that the time it takes to spin up a model that can classify pictures at state-of-the-art accuracy fell “from around on hour to around 4 minutes” in just 18 months. That equates to a roughly 16x jump in training speed. Other areas like object segmentation, which is what lets software differentiate between an image’s background and its subject, has increased in precision by 72 percent in just three years.
AI will only continue to get more sophisticated, but there are a number of hurdles, both technological and with regard to bias and safety, before such software could be reliably used without error in hospitals, education systems, airports, and police departments.
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