University of California-San Diego, UC San Diego News Center
The San Diego Supercomputer Center (SDSC) located at UC San Diego has heeded the National Science Foundation’s call for a cyberinfrastructure ecosystem that meets the needs of today’s data-intensive science. Proposed as the Prototype National Research Platform (NRP), the innovative, all-in-one system—computing resources, research and education networks, edge computing devices and other instruments—is a testbed for science drivers as diverse as the platform itself to expedite science and enable transformative discoveries.
For this first-of-its-kind resource, the NSF awarded SDSC $5 million over five years, with matched funding for systems operation. The award will support hardware and deployment across three facilities: on the East Coast at the Massachusetts Green High Performance Computing Center (MGHPCC) in Mount Holyoke, MA; in the Midwest at the University of Nebraska–Lincoln (UNL) and on the West Coast at SDSC, as well as five data caches in the Internet2 network backbone.
In May, as part of an otherwise unremarkable corporate strategy meeting, Sony CEO Kenichiro Yoshida made an interesting announcement. The company’s artificial intelligence research division, Sony AI, would be collaborating with PlayStation developers to create intelligent computer-controlled characters. “By leveraging reinforcement learning,” he wrote, “we are developing game AI agents that can be a player’s in-game opponent or collaboration partner.” Reinforcement learning is an area of machine learning in which an AI effectively teaches itself how to act through trial and error. In short, these characters will mimic human players. To some extent, they will think.
Qualcomm said Monday that it recently acquired the assets of Twenty Billion Neurons, a Microsoft-backed artificial intelligence/computer vision startup that develops avatars that can see and interact with people in a human-like way.
The San Diego mobile technology company declined to say how much it paid for TwentyBN, which has locations in Berlin and Toronto. But it is likely a relatively small deal. Qualcomm said the company has under 20 employees. It raised about $10 million in venture capital from M12 — Microsoft’s venture capital fund— and others since it was founded in 2015 by Chief Executive Roland Memisevic.
Memisevic was the co-head of MILA, a well-respected AI research institute in Montreal. He will be joining Qualcomm with the rest of the TwentyBN team.
The “Eyes of Texas” turned into a polarizing topic last fall, and the Longhorns evidently spent a big amount to revamp the song’s image. The Texas Tribune revealed in a report published Monday morning that Houston-based consultant Brad Deutser was “quietly” added to a committee organized by university president Jay Hartzell — which included 24 athletes, historians, professors and students — tasked with chronicling the alma mater’s “full history.”
UT hired Deutser and his company on two contracts worth up to $1.1 million, the Tribune learned through an open records request. Deutser also was tasked with broader organizational projects, namely a new communication and engagement strategy for the university and clarifying “what it means to be a Longhorn.
Firsthand accounts and images of Black soldiers hold hidden chapters of U.S. history. Historians and computer scientists are harnessing technologies like virtual reality and AI to equip the public to immerse themselves in those perspectives, learn from them, and broaden historical dialogue.
… In the mid-2010s, lawmakers didn’t pay much notice as researchers and tech companies brought about a rapid increase in the capabilities and use of AI, from conquering champs at Go to ushering smart speakers into kitchens and bedrooms. The technology became a mascot for US innovation, and a talking point for some tech-centric lawmakers. Now the conversations have become more balanced and business-like, Toner says. “As this technology is being used in the real world you get problems that you need policy and government responses to.”
Face recognition, the subject of GAO’s first AI report of the summer, has drawn special focus from lawmakers and federal bureaucrats. Nearly two dozen US cities have banned local government use of the technology, usually citing concerns about accuracy, which studies have shown is often worse on people with darker skin.
More than 700 imaging satellites are orbiting the earth, and every day they beam vast oceans of information — including data that reflects climate change, health and poverty — to databases on the ground. There’s just one problem: While the geospatial data could help researchers and policymakers address critical challenges, only those with considerable wealth and expertise can access it.
Now, a team based at UC Berkeley has devised a machine learning system to tap the problem-solving potential of satellite imaging, using low-cost, easy-to-use technology that could bring access and analytical power to researchers and governments worldwide. The study, “A generalizable and accessible approach to machine learning with global satellite imagery,” was published today (Tuesday, July 20) in the journal Nature Communications.
The federal government would finally be able to hire specifically for “software development,” “software engineering,” “data management,” and “knowledge management” positions under new legislation before the House.
Over multiple administrations, the federal government has tried to get better at hiring and retaining tech-savvy employees but continues to meet challenges, including the lack of specific job roles for positions that are critical to creating a digitally-driven government.
The Federal Career Opportunities in Computer Science Work Act looks to remedy that for four such positions. The bill—introduced by Reps. Jay Obernolte, R-Calif., and Peter Welch, D-Vt.—would give the Office of Personnel Management 270 days to establish roles for software development, software engineering, data scientist and knowledge management.
Imagine logging on to your own account with the U.S. Federal Reserve. With your laptop or phone, you could zap cash anywhere instantly. There’d be no middlemen, no fees, no waiting for deposits or payments to clear.
That vision sums up the appeal of the digital dollar, the dream of futurists and the bane of bankers. It’s not the Bitcoin bros and other cryptocurrency fans pushing the disruptive idea but America’s financial and political elite. Fed Chair Jerome Powell promises fresh research and a set of policy questions for Congress to ponder this summer. J. Christopher Giancarlo, a former chairman of the Commodity Futures Trading Commission, is rallying support through the nonprofit Digital Dollar Project, a partnership with consulting giant Accenture Plc. To perpetuate American values such as free enterprise and the rule of law, “we should modernize the dollar,” he recently told a U.S. Senate banking subcommittee.
For many scientists, the transition from a PhD to a faculty position often happens when they are starting or building families, Moura says. It’s no wonder, she adds, that many early-career researchers make crucial, life-altering decisions based on institutions’ policies and attitudes around parenthood.
[Yhasmin] Moura was among 176 attendees from 46 nations at a virtual conference organized in May by Mothers in Science (MiS), an international non-profit organization that aims to boost recruiting and retention of women in science careers. The conference highlighted the well-documented ‘motherhood penalties’ that mothers in science, technology, engineering and mathematics (STEM) face as they try to build their careers. Scientist-mothers face discrimination1, drops in productivity2 and inequities in wages and promotion3,4, all of which contribute to them dropping out of the full-time STEM workforce5. The conference also pointed out that the COVID-19 pandemic revealed the stark pressures on mothers in STEM and highlighted the practices and policies that can help people to balance research and motherhood.
The Hechinger Report, Opinion, Wayne A. I. Frederick and Paul Decker
Consider the burgeoning field of artificial intelligence (AI), whose influence in our lives will exceed what many of us can even imagine. Harnessing AI has countless applications, from helping to map diseases to improving adaptive online learning platforms to supporting the work of law enforcement officers.
But without experts and policymakers at the table with diverse lived experiences, the use of those technologies is more likely to reinforce the unconscious biases already rampant in society than to address them.
The US higher education world is very excited about predatory master’s degrees. The conversation started with a well reported investigation but now master’s degrees are being called a scam. Almost on the wholesale. What should we make of that? I take a look at the place of master’s degrees in the US higher education landscape since 1980 and then think a bit about what the predatory master’s degrees mean and how we might think about the master’s degree in general. I’m not convinced the current conversation is productive.
Never Gonna Give You Up has 994,611,556 views on YouTube. To commemorate it hitting one billion views, we analyzed millions of comments, posts, and links to chart the definitive history of the Rickroll .
2/ Marketing often targets influencers who have many connections and who broker communities. But if the behavior is a complex contagion that requires influence from multiple peers (eg diet), then the connections of influencers may not be connected enough to trigger spread.
3/ We show that the people who are capable of spreading complex contagions to the largest number of people have surprisingly few connections and do not broker communities, but are rather deeply embedded within them. We provide formal methods for identifying these network hotspots
The sun provides a daunting source of electromagnetic disarray – chaotic, random energy emitted by the massive ball of gas arrives to Earth in a wide spectrum of radio frequencies. But in that randomness, Stanford researchers have discovered the makings of a powerful tool for monitoring ice and polar changes on Earth and across the solar system.
In a new study, a team of glaciologists and electrical engineers show how radio signals naturally emitted by the sun can be turned into a passive radar system for measuring the depth of ice sheets and successfully tested it on a glacier in Greenland. The technique, detailed in the journal Geophysical Research Letters on July 14, could lead to a cheaper, lower power and more pervasive alternative to current methods of collecting data, according to the researchers. The advance may offer large-scale, prolonged insight into melting ice sheets and glaciers, which are among the dominant causes of sea-level rise threatening coastal communities around the world.
The eScience Institute’s Data Science for Social Good program is now accepting applications for student fellows and project leads for the 2021 summer session. Fellows will work with academic researchers, data scientists and public stakeholder groups on data-intensive research projects that will leverage data science approaches to address societal challenges in areas such as public policy, environmental impacts and more. Student applications due 2/15 – learn more and apply here. DSSG is also soliciting project proposals from academic researchers, public agencies, nonprofit entities and industry who are looking for an opportunity to work closely with data science professionals and students on focused, collaborative projects to make better use of their data. Proposal submissions are due 2/22.
Computing Community Consortium, The CCC Blog, Maddy Hunter
“The CRA is excited to announce the launch of an Opportunity Board to enable recent new PhD graduates and members of the community that are looking for postdocs to connect. This is a continuation of the Opportunity Board used to match potential postdocs and mentors during the CIFellows 2021 process. The board allows for the posting of postdoc opportunities by potential mentors and posts by those looking for a postdoc opportunity.”
We’re collecting (an admittedly opinionated) list of resources and progress made in data-centric AI, with exciting directions past, present and future. This blog talks about our journey to data-centric AI.
At the 2021 International Conference on Machine Learning (ICML), we are releasing a new dataset for benchmarking AI intuition, along with two machine learning models representing different approaches to the problem. The research has been done with our colleagues at MIT and Harvard University to accelerate the development of AI that exhibits common sense. These tools rely on testing techniques that psychologists use to study the behavior of infants.