U.S. Senators Rob Portman (R-OH), Martin Heinrich (D-NM), and Brian Schatz (D-HI) today proposed the Artificial Intelligence Initiative Act, legislation to pump $2.2 billion into federal research and development and create a national AI strategy. The $2.2 billion would be doled out over the course of the next 5 years to federal agencies like the Department of Energy, Department of Commerce's National Institute of Standards and Technology (NIST), and others. The legislation would establish a National AI Coordination Office to lead federal AI efforts, require the National Science Foundation (NSF) to study the effects of AI on society and education, and allocate $40 million a year to NIST to create AI evaluation standards. The bill would also include $20 million a year from 2020-2024 to fund the creation of 5 multidisciplinary AI research centers, with one focused solely on K-12 education. Plans to open national AI centers in the bill closely resembles plans from the 20-year AI research program proposed by the Computing Consortium.
NASA's next trip to the moon will entail 37 separate launches over a decade and culminate in the construction of a moon base by 2028, according to leaked documents that detail the agency's'Artemis' plan. Information on the nascent mission come from documents obtained by Ars Technica, and, for the first time, show a detailed glimpse of America's first human-led mission to the moon since 1972. In a graphic, NASA breaks down a year-by-year guide of the construction of the'Gateway' a space station and waypoint on the way to the moon, human test flights, and a lunar landing slated for 2024. Russia and the United States are cooperating on a NASA-led project to build the first lunar space station, codenamed the Lunar Gateway. The agreement, signed in September 2017, is part of a long-term project to send humans to Mars.
The IEEE International Conference on Robotics and Automation (ICRA) is being held this week in Montreal, Canada. It's one of the top venues for roboticists and attracts over 4000 conference goers. Andra, Audrow, Lauren, and Lilly are on the ground so expect lots of great podcasts, videos with best-paper nominees, and coverage in the weeks and months ahead. For a taste of who is presenting, here is the schedule of keynotes. It also looks like you can navigate the program, read abstracts, and watch spotlight presentations by following these instructions.
This article is also available in Japanese and Simplified Chinese. Lionbridge AI has assembled a wealth of resources for machine learning and natural language processing activities. In our previous articles, we explained why datasets are such an integral part of machine learning and natural language processing. Without training datasets, machine-learning algorithms would have no way of learning how to do text mining, text classification, or categorize products. This article is the ultimate list of open datasets for machine learning.
Measles, once thought to have been eliminated in the U.S., is popping up in isolated outbreaks as a result of skipped well-child visits and parents' fears that the measles-mumps-rubella (MMR) vaccine is linked to autism. Though some 350 measles cases occurred in 15 states in the first three months of 2019, more than half were in Brooklyn, N.Y., and nearby Rockland County, N.Y., where large religious communities have adopted anti-vaccine positions. Rockland County responded by pulling 6,000 unvaccinated children out of schools and barring them from public places. The county's actions were effective; in just a few months, 17,500 doses of MMR were administered to area children. Yet, wouldn't it have been better to contain the outbreak before it got started?
The condition is the leading cause of cancer-related death in the U.S., and early detection is crucial for both stopping the spread of tumors and improving patient outcomes. As an alternative to chest X-rays, healthcare professionals have recently been using computed tomography (CT) scans to screen for lung cancer. In fact, some scientists argue that CT scans are superior to X-rays for lung cancer detection, and research has shown that low-dose CT (LDCT) in particular has reduced lung cancer deaths by 20%. These errors typically delay the diagnosis of lung cancer until the disease has reached an advanced stage when it becomes too difficult to treat. New research may safeguard against these errors.
In this issue of Communications, as evidenced by the cover and lead article, we celebrate the latest recipients of the ACM A.M. Turing Award. Yoshua Bengio, Yann LeCun, and Geoffrey Hinton carried out pioneering work in deep learning that has touched all our lives. As Turing Laureates, they now join the eminent group of technology visionaries recognized with the world's highest distinction in computing. The Turing Award is one of a suite of professional honors ACM bestows annually to recognize technical achievements that have made significant contributions to our field. This month, I will have the pleasure of joining the awardees, ACM Fellows, and other luminaries in San Francisco for the ACM Awards Banquet.
Columbia University is learning how to build and train self-aware neural networks, systems that can adapt and improve by using internal simulations and knowledge of their own structures. The University of California, Irvine, is studying the dual memory architecture of the hippocampus and cortex to replay relevant memories in the background, allowing the systems to become more adaptable and predictive while retaining previous learning. Tufts University is examining an intercellular regeneration mechanism observed in lower animals such as salamanders to create flexible robots capable of adapting to changes in their environment by altering their structures and functions on the fly. SRI International is developing methods to use environmental signals and their relevant context to represent goals in a fluid way rather than as discrete tasks, enabling AI agents to adapt their behavior on the go.