The survey by North Carolina State University, in partnership with the Aspen Institute’s Project Play, Utah State University and George Mason University, shows that 59% of African American parents worry their child will get sick. They also are concerned about their own health as parents who attend events – 56% fear they will fall ill. Among all parents, 50% worry their child will get sick and 46% are concerned they will become ill.
When you think of learning another language, you probably think of French, Spanish, or Chinese. But what about Python or Java? The two processes might be more similar than you’d think.
A recent study published from researchers at the University of Washington showed that language ability and problem solving skills best predict how quickly people learn Python, a popular programming language. Their research, published in Scientific Reports, used behavioral tests and measures of brain activity to see how they correlated with how fast and well participants learned programming.
Atul Gawande on Wednesday confirmed that he will step down as chief executive of the health care company formed by Amazon, JPMorgan Chase & Co., and Berkshire Hathaway, saying it will allow him to devote more time to addressing the threats posed by Covid-19.
Gawande said in a statement posted on Haven’s website that he will stay on as chairman of Haven’s board of directors and that a search has begun for a new chief executive officer. Mitch Betses, a longtime executive with CVS Health who became Haven’s chief operating officer in March, will oversee day-to-day operations.
I’m a data scientist at the University of San Francisco and teach courses online in machine learning for fast.ai. In late March, I decided to use public mask-wearing as a case study to show my students how to combine and analyze diverse types of data and evidence.
Much to my surprise, I discovered that the evidence for wearing masks in public was very strong. It appeared that universal mask-wearing could be one of the most important tools in tackling the spread of COVID-19. Yet the people around me weren’t wearing masks and health organizations in the U.S. weren’t recommending their use.
I, along with 18 other experts from a variety of disciplines, conducted a review of the research on public mask-wearing as a tool to slow the spread SARS-CoV-2. We published a preprint of our paper on April 12 and it is now awaiting peer review at the Proceedings of the National Academy of Sciences.
“We know that the future of work is all about collaboration and problem solving,” says Peter Baeck, who leads the Centre for Collective Intelligence Design at Nesta, a UK charity that funds and promotes research into groundbreaking ideas. “One of the most obvious opportunities is using AI to better create connections within often quite chaotic messy networks of people who are working on a common challenge.”
The biggest factor affecting how collectively intelligent a group can be is the degree of coordination among its members, says Anita Woolley, a leading expert in organisational behaviour at Carnegie Mellon University. Smart tools can be a boon in this area, which is why Woolley is working with colleagues to develop AI-powered coaches that can track group members and provide prompts to help them work better as a team.
Minneapolis Star Tribune, Joe Carlson and Glenn Howatt S
from
Michael Osterholm, director of the University of Minnesota Center for Infectious Disease Research and Policy, said special attention needs to be paid to the 36% or more of Minnesota’s population who are at increased risk for severe or fatal COVID-19 disease because of conditions including advanced age, heart disease, chronic obstructive pulmonary disease, uncontrolled asthma, diabetes, and obesity with a BMI of more than 40.
New York-based data scientist and machine-learning expert Youyang Gu has produced national and state-specific models that show Minnesota’s social distancing and mitigation strategies have successfully brought the state’s level of transmission just a hair below a self-sustaining outbreak.
The model — one of a dozen tracked by the Centers for Disease Control and Prevention — uses death data to conclude that Minnesota has moved just slightly below 1.0 in a critical threshold that measures how many people a person with the virus is expected to infect, known as the virus’ reproductive rate.
Analyzing how people collaborate in AGU’s meetings and publications according to gender, age, and ethnicity provides clear evidence for diversifying networks and collaborating with new people.
Lawrence Berkeley National Laboratory, News Center
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A new study by an international team of scientists revealed 335 new strong lensing candidates based on a deep dive into data collected for a U.S. Department of Energy-supported telescope project in Arizona called the Dark Energy Spectroscopic Instrument (DESI). The study, published May 7 in The Astrophysical Journal, benefited from the winning machine-learning algorithm in an international science competition.
“Finding these objects is like finding telescopes that are the size of a galaxy,” said David Schlegel, a senior scientist in Lawrence Berkeley National Laboratory’s (Berkeley Lab’s) Physics Division who participated in the study. “They’re powerful probes of dark matter and dark energy.”
Along with its toll on human lives across the planet, the COVID-19 pandemic has also produced untold amounts of data, in the form of medical records and news articles.
For Colorado State University Professor of Computer Science Indrakshi Ray, these mountains of data are an opportunity and a challenge to sift through the noise and help determine what’s true and what’s false.
Ray, a cybersecurity and database systems researcher, and a team of data science and medical experts, have received support from the National Science Foundation via an “NSF RAPID” proposal. They will spend the next year refining machine learning-based tools that help ensure the integrity of COVID-19 data and news across regions.
As the coronavirus crisis has dragged on, understaffed government agencies, grocery stores, and financial services have all scrambled to set up similar systems for handling a new influx of calls. IBM saw a 40% increase in traffic to Watson Assistant from February to April of this year. In April, Google also launched the Rapid Response Virtual Agent, a special version of its Contact Center AI, and lowered the price of its service in response to client demand.
While call centers have long been a frontier of workplace automation, the pandemic has accelerated the process. Organizations under pressure are more willing to try new tools. AI firms keen to take advantage are sweetening the incentives. Over the last few years, advances in natural-language processing have also dramatically improved on the clunky automated call systems of the past. The newest generation of chatbots and voice-based agents are easier to build, faster to deploy, and more responsive to user inquiries. Once adopted, in other words, these systems will likely be here to stay, proving their value through their ease of use and affordability.
NVIDIA today set out a vision for the next generation of computing that shifts the focus of the global information economy from servers to a new class of powerful, flexible data centers.
In a keynote delivered in nine simultaneously released episodes recorded from the kitchen of his California home, NVIDIA founder and CEO Jensen Huang discussed NVIDIA’s recent Mellanox acquisition, new products based on the company’s much-awaited NVIDIA Ampere GPU architecture and important new software technologies.
Multiple AI researchers from different companies told CNBC that they see Musk’s AI comments as inappropriate and urged the public not to take his views on AI too seriously. The smartest computers can still only excel at a “narrow” selection of tasks and there’s a long way to go before human-level AI is achieved.
“A large proportion of the community think he’s a negative distraction,” said an AI executive with close ties to the community who wished to remain anonymous because their company may work for one of Musk’s businesses.
“He is sensationalist, he veers wildly between openly worrying about the downside risk of the technology and then hyping the AGI (artificial general intelligence) agenda. Whilst his very real accomplishments are acknowledged, his loose remarks lead to the general public having an unrealistic understanding of the state of AI maturity.”
One of the difficult aspects of sheltered life during the coronavirus pandemic has been our inability to make plans. It is hard to plan when there is so much we just do not know, such as when we can next travel on a plane, when we can start seeing friends and extended family in person again, and if and when an event still on the calendar will occur. We also do not know yet when we can restart research in our laboratories.
Yet, as the Spring semester draws to a close and teaching obligations no longer top our priority list, we are beginning to think about how we would go about opening laboratories back up, once we get the go-ahead from university and government leadership. It is pretty clear that any effort to restart research operations will have to be careful and deliberate, with a lot of thoughtful planning to ensure the safety, security, and well-being of our community of graduate students, postdoctoral associates, staff, and faculty, as they begin to come back to campus and work in proximity.
In the Department of Chemistry at Washington University in St. Louis, MO, we are developing planning documents with guidelines for principal investigators to follow as they ramp up research and we are asking Principal Investigators (PIs) to implement new processes and procedures specific to laboratory life during the pandemic.
Scientists in Spain are expecting to begin regularly analyzing sewage for traces of the coronavirus that causes COVID-19, The Scientist has learned. Pending budget approval from AXA or national funds in Spain, researchers will carry out the work for at least a whole year, having signed a special agreement with authorities in the Valencian Community, a region on Spain’s eastern coast that is home to nearly 5 million people.
It will involve the twice-weekly collection of samples from more than 250 wastewater treatment plants, says lead researcher Pilar Domingo-Calap, a biologist at the University of Valencia. Already, her team is sampling from 20 facilities in a preliminary phase of the project.
Online May 18, starting at 3 p.m. EDT. “Join #CSforALL with @TheBSD405
, @cs4allcps
, @LPSorg
, @CSforAllNYC
in a discuss on how districts and schools are supporting equitable computer science education during #COVID” [registration required]
“The ACM Special Interest Group on Economics and Computation, with financial support from Facebook, is announcing a call to support investigation into important theoretical problems and new research applications for economics and computation (EC). We hope to support pilot and early stage research that leverages advances in EC for broader societal benefit, and encourage emerging scholars with diverse perspectives to apply.” Deadline for submissions is May 22.
“The Computing Research Association (CRA) and Computing Community Consortium (CCC) are pleased to announce a new Computing Innovation Fellows (CIFellows) Program for 2020. This program recognizes the significant disruption to the academic job search caused by the COVID-19 pandemic and associated economic uncertainty and aims to provide a career-enhancing bridge experience for recent and soon-to-be PhD graduates in computing.” Deadline for applications is mid-June.
“The data challenge is specifically focused on testing the relationships between COVID-19 and other health conditions, as well as health disparities and social determinants of health that bring a higher burden of illness or mortality based on factors such as ethnicity, gender, geography or income.” Deadline for Stage One participation is June 12.
Last week, GitHub announced four new products on its official blog. The most eye-catching of the lot is the tool Codespaces. Released in conjunction with the GitHub Satellite 2020 Virtual Conference, Codespaces is an in-browser integrated development environment (IDE) that lets users type their code directly on a GitHub website page.
University of Chicago, Department of Computer Science
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Computational scientific research is no longer one-size-fits-all. The massive datasets created by today’s cutting-edge instruments and experiments—telescopes, particle accelerators, sensor networks and molecular simulations—aren’t best processed and analyzed by a single type of machine. For faster and more efficient discovery, data can be chopped up and shipped to specialized resources, including supercomputers, campus clusters, cloud data centers, and “accelerators” optimized for specific tasks such as machine learning or visualization.
But delegating chunks of data and analysis functions to their ideal destination isn’t trivial. A team led by UChicago CS researchers Ian Foster and Kyle Chard and Daniel S. Katz of the National Center for Supercomputing Applications at the University of Illinois seeks to streamline the process with funcX, a new distributed “function-as-a-service” (FaaS) platform that makes it easier for researchers to easily and automatically delegate their computational workload.