There’s less than two weeks left to apply for the 2020-2021 cohort of AAAS Leshner Leadership Fellows! This program convenes mid-career scientists who demonstrate leadership in their research careers and in promoting meaningful dialogue between science and society. Each year, 15 Leshner Fellows from disciplines at the nexus of important science-society issues convene for a week of public engagement and science communication training and public engagement plan development in Washington, DC, then continue their activities while at their home institutions during the fellowship year. The 2020-2021 cohort will be comprised of active researchers in the field of artificial intelligence, new and emerging technologies that seek to replicate, mimic or augment human […]

In Tuesday’s opening lecture at the Heidelberg Laureate Forum (HLF), Joseph Sifakis, 2007 Turing Award winner, discussed whether we can trust autonomous systems and considered the interplay between the trustworthiness of the system – the system’s ability to behave as expected despite mishaps – and the criticality of the task – the severity of the impact an error will have on the fulfillment of a task. Sifakis defined autonomy as the combination of five complementary functions – perception, reflection, goal management, planning, and self-awareness/adaption. The better a given system can manage these functions the higher the level of autonomy we say that it has, from 0 (no automation) to 5 (full automation, no […]

Yesterday morning at the Heidelberg Laureate Forum (HLF) laureates Yoshua Bengio (2018 Turing Award), Edvard Moser (2014 Nobel Prize in Physiology or Medicine), and Leslie G. Valiant (1986 Nevanlinna Prize and 2010 Turing Award) each presented a lecture related to artificial intelligence or the modeling of the brain. Yoshua Bengio’s lecture on “Deep Learning for AI” provided a retrospective of some of the key principles behind the recent successes of deep learning. Dr. Bengio’s work has mostly been in neural networks, which are inspired by the computation found in the human brain. One of the key insights in the field came with the representation of words as vectors of numbers. This allowed relationships between words to be learned […]

Recently, the Computing Community Consortium (CCC) released the completed Artificial Intelligence (AI) Roadmap, titled A 20-Year Community Roadmap for AI Research in the US! An HTML version is available here. Slides summarizing the roadmap are now available here. We encourage you to use these when sharing the community vision. This roadmap is the result of a year long effort by the CCC and over 100 members of the research community, led by Yolanda Gil (University of Southern California and President of AAAI) and Bart Selman (Cornell University and President Elect of AAAI). Comments on a draft report of this roadmap were solicited in the Spring of 2019 and incorporated in the final report. If you would like […]

The Computing Community Consortium (CCC) is sponsoring a Blue Sky Ideas Track at the Association for the Advancement of Artificial Intelligence Meeting (AAAI-20) in February 2020 in New York through their Senior Member Presentation Track (SMPT). Summary: SMPT provides an opportunity for established researchers in the AI community to give a broad talk on a well-developed body of research, an important new research area, or a promising new topic. These presentations should provide a big picture view, in contrast to regular papers, which may focus on a specific contribution. There are two subtracks for submissions of talk proposals for the AAAI 2020 Senior Members Track (SMPT): the summary talk – broad talks on a well-developed body of research […]

The following blog was written by Computing Community Consortium (CCC) Chair Mark D. Hill from the University of Wisconsin Madison.  This week Cerebras announced a bold design to accelerate deep neural networks with silicon that is not cut into chips. AI and Moore’s Law: Artificial Intelligence (AI) is much in the news for what it can do to today and the promise of what it can do tomorrow (CCC/AAAI 20-Year AI Roadmap). Over half a century, AI innovation has been abetted by a million-fold progress in computer system cost-performance and parallelism. For decades, computer benefits came transparently via repeated doubling of processor performance (popularly called “Moore’s Law”). For the last decade, however, AI–especially for the great successes of […]