Data is a multi-billion dollar industry, and it will only grow as data-fueled technologies like AI become more advanced. It's used to train powerful AI systems to recognize patterns in human and machine behavior, to train AI on images, sounds, and objects. Essentially data is AI's window to the outside world. However, huge amounts of data are needed to train AI systems effectively, and China collects more data from its civilians than any other country.
Eric Schmidt, the former Google chief executive who chairs the National Security Commission on Artificial Intelligence, has warned the US will hurt its own innovation by barring co-operation with Chinese researchers. The comments come as some Trump administration officials push to decouple technology from China.
Recent technology advances in education are focusing in on personalized learning. Software programs help students learn at their own pace. These programs teach students the material, test their proficiency, then either progress them to new topics or review the material again to develop their understanding of the topic. AI will even adjust how the lessons are taught to each student as it learns each student’s best learning style.
The U.S. Department of Energy (DOE) is planning a major initiative to use artificial intelligence (AI) to speed up scientific discoveries. At a meeting here last week, DOE officials said they will likely ask Congress for between $3 billion and $4 billion over 10 years, roughly the amount the agency is spending to build next-generation “exascale” supercomputers.
So far, efforts to cultivate algorithmic fairness lag far behind the enthusiasm to adopt the technology. Industry, with its drive for competitive advantage and focus on profits, has shown little inclination to shoulder this responsibility. The institution that needs to play a critical role in leading the way to an AI-powered world that is both ethical and fair is higher education.
The National Science Foundation today announced the creation of a new program that will significantly advance research in AI and accelerate the development of transformational, AI-powered innovation by allowing researchers to focus on larger-scale, longer-term research.
Contrary to what the mainstream media would have you believe, China is still behind and second to the United States in artificial intelligence (AI) innovation, according to Lux Research, a leading provider of tech-enabled research and advisory services for technology innovation. Over the past four years, Chinese artificial intelligence (AI) startups have received $6.1 billion in funding.
As automation and technology change the nature of work from physical to technical labor, as manufacturing jobs transition from physical assembly-line occupations to those tied to supporting automation and robotics, a strong STEM skill set will be of the utmost importance in the new economy.Unfortunately, this skill set is exactly what our workforce lacks at the moment. In recent years, the skills gap has received much attention, and rightfully so.
The announcement Tuesday of a nearly $1 billion federal commitment toward artificial-intelligence research drew a mixed response from business leaders who said the U.S. needs to do more to maintain a competitive edge in AI. Government agencies requested $973.5 million in nondefense AI research spending for the fiscal year ending in September 2020.
China comes in second, and the European Union lags further behind. This order could change in coming years as China appears to be making more rapid progress than either the United States or the European Union. Nonetheless, when controlling for the size of the labor force in the three regions, the current U.S. lead becomes even larger, while China drops to third place, behind the European Union. This report also offers a range of policy recommendations to help each nation or region improve its AI capabilities.