The rate of progress in the field of artificial intelligence is one of the most hotly contested aspects of the ongoing boom in teaching computers and robots how to see the world, make sense of it, and eventually perform complex tasks both in the physical realm and the virtual one. And just how fast the industry is moving, and to what end, is typically measured not just by actual product advancements and research milestones, but also by the prognostications and voiced concerns of AI leaders, futurists, academics, economists, and policymakers. AI is going to change the world — but how and when are still open questions.
Finding from a group of experts were published last week inthe second annual AI Index, assembled by experts from Harvard, MIT, Stanford, the nonprofit OpenAI, and the Partnership on AI industry consortium, among others. The goal is to measure the field’s progress using hard data and to try and make sense of that progress as it relates to thorny subjects like workplace automation and the overarching quest for artificial general intelligence, or the type of intelligence that could let a machine perform any task a human could.
The first report, published last December, found that investment and work in AI was accelerated at an unprecedented rate and that, while progress in certain fields like limited game-playing and vision has been extraordinary, AI remains far behind in general intelligence tasks that would result in, say, total automation of more than a limited variety of jobs. Still, the report was lacking in what the authors call a “global perspective,” and this second edition set out to answer many of the same questions with new, more granular data and a more international scope.
“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 — or the type of cognition-related performance that lets a game-playing AI outsmart a human opponent — 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.
Read the source article in The Verge.