More than 100 aspiring entrepreneurs at the University of Virginia recently celebrated the opening of a new space for them to meet, make plans and find ways to change the world.
The Lighthouse, a repurposed storage room in Thornton Hall, is the new home of Works in Progress, a program sponsored by the Department of Engineering and Society that aims to bring together student entrepreneurs and support them at any stage of their endeavors.
Moore Foundation grantees at JILA, a joint institute of the University of Colorado, Boulder and the National Institute of Standards and Technology, have developed a new technique to image tiny structures too small to be seen with visible light microscopes. Remarkably, this technique doesn’t require any optical components such as lenses or mirrors.
Led by Margaret Murnane, a professor of physics at CU Boulder and investigator through the foundation’s Emergent Phenomena in Quantum Physics initiative, the team used a technique called extreme ultraviolet light (EUV) imaging, which leverages coherent beams of extreme ultraviolet light to examine nanoscale materials.
“I had a whole sequence of logic and explanation prepared,” [Meenakshi] Narain says. “When I presented it, I remember everybody was very supportive. I had expected some pushback or some criticism and nothing like that happened.”
This, she says, is the scientific process: A multitude of steps designed to help us explore the world we live in.
“In the end the process wins. It’s not about you or me, because we’re all going after the same thing. We want to discover that particle or phenomenon or whatever else is out there collaboratively. That’s the goal.”
Narain’s group’s analysis was essential to the collaboration’s understanding of a signal that turned out to be the elusive top quark.
Software Sustainability Institute (UK), Will Usher
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Plagiarism is a serious issue, and we are all familiar with the horror stories of students unceremoniously ejected from courses for copying essays. Any undergraduate degree worth its salt teaches students how to cite work correctly, acceptable bounds on quotation and how to attribute ideas and concepts to their sources. But in the growing world of open-source research software, best practices have yet to be universally understood, as I recently found out.
Business intelligence company Looker has closed an $81.5 million Series D funding round led by CapitalG, the equity investment fund of Google parent company Alphabet, Inc. Other new investors include Goldman Sachs and Geodesic Capital. The company has now raised a total of $177.5 million since 2013.
Looker provides a data platform that uses real-time analytics, exploration and insights aimed at better decision making for enterprises, the company stated.
The Trump administration’s plan to cut billions of dollars in research spending by eliminating indirect cost reimbursements would devastate university science, especially at public institutions, experts warned.
The U.S. secretary for health and human services, Tom Price, told Congress this week that the idea is to save taxpayers money while giving them the same amount of research activity. Indirect cost payments are funds spent on “something other than the research that’s being done,” Dr. Price told a House of Representatives subcommittee on health appropriations on Wednesday.
But university representatives made clear Thursday that it simply does not work that way. Indirect costs reflect the legitimate expenses of providing scientists with labs and complying with a host of essential services that somehow will still need to be paid, the representatives said.
A shortage of job candidates with fluency in data science and analytics is among the nation’s most yawning of skills gaps, one requiring substantial changes by higher education institutions and employers alike.
That’s the central finding of a new report from the Business-Higher Education Forum, a nonprofit membership group of Fortune 500 CEOs and college leaders, and PricewaterhouseCoopers, a large consulting and audit company.
An estimated 2.72 million new job postings in 2020 will seek workers with skills in data science and analytics, according to an analysis from Burning Glass Technologies that the forum and PwC commissioned.
Sea otters have the distinction of using tools, such as rocks, to break open hard-to-access food sources. A new study — in which two University of Wyoming researchers participated — reveals that, unlike bottlenose dolphins, California sea otters’ frequent use of tools has little to do with genetic ties and more to do with ecological conditions.
“Within marine mammals, the best examples of tool use are sea otters and Indo-Pacific bottlenose dolphins. In both species, tool use is not implemented by all individuals even within a population,” says Roderick (Erick) Gagne, a postdoctoral research associate in UW’s Department of Veterinary Sciences. “Genetic analyses of the bottlenose dolphins revealed that tool use was strongly related to a single matriline (lineage from the mother’s family tree line) and that tool-use transmission is likely cultural. In sea otters, however, we found no association between relatedness and mitochondrial haplotypes (part of the DNA genome inherited from the mother) with tool use. Instead, our work suggests a predisposition of all sea otters to use tools when faced with certain ecological conditions.”
When I first met Cloudera CEO Tom Reilly in 2015 at the Intel Capital Summit, we were about to go onstage for a fireside chat to discuss, among other things, Intel’s massive investment in his company.
While onstage, the conversation inevitably turned to when the company might go public. As you might expect, he gave me the standard startup CEO answer. While Cloudera was certainly of sufficient size to IPO, they had just raised more than a billion dollars and had plenty of cash. He was willing to wait until, in his words, “when we feel it’s the right time.”
Apparently it was yesterday when the company filed its S-1 paperwork with the SEC indicating its plans to go public. The announcement had been rumored for some time, and made sense, especially given the number of enterprise tech companies that have gone public (or announced their intentions to do so) recently.
It’s hard to visit a tech site these days without seeing a headline about deep learning for X, and that AI is on the verge of solving all our problems. Gary Marcus remains skeptical.
Marcus, a best-selling author, entrepreneur and professor of psychology at NYU, has spent decades studying how children learn, and believes that throwing more data at problems won’t necessarily lead to progress in areas such as understanding language, not to speak of getting us to AGI — artificial general intelligence.
Marcus is the voice of anti-hype at a time when AI is all the hype, and in 2015 he translated his thinking into a startup, Geometric Intelligence, which uses insights from cognitive psychology to build better-performing, less-data-hungry machine learning systems. The team was acquired by Uber in December to run Uber’s AI labs, where his co-founder Zoubin Ghahramani has now been appointed chief scientist. So what did the tech giant see that was so important?
Periodical journals have been the principal means of disseminating science since the 17th century. Over the intervening three-and-a-half centuries journals have established conventions for publication—such as insisting on independent (and usually anonymous) peer review of submissions—that are intended to preserve the integrity of the scientific process. But they have come under increasing attack in recent years. What is wrong with scientific publishing in journals, and how can it be fixed?
The problems stem from the fact that journal publication now plays a role that was not part of the original job description: as indicators of a researcher’s prowess, and thus determinants of academic careers. The incentive to withhold results for months or years until research is published is therefore powerful. But such delays can do real harm: during the Zika crisis, sponsors of research had to persuade publishers to declare that scientists would not be penalised for releasing their findings early. Nor are elite journals (such as Nature and Science) the guardians of quality that they often claim to be. The number of papers so flawed that they need to be retracted has risen sharply in the past two decades, with glitzier journals pulling more papers than lower-profile counterparts. Worse, studies in elite journals are no more statistically robust than those in lesser ones.
Three sensible reforms could change this system, ensuring that researchers’ results are made public more quickly and without any compromise on quality.
Last August, Andrea Giacobbe logged on to Skyscanner, a European metasearch engine like Expedia and Travelocity that scans multiple travel websites and surfaces the cheapest fare. Giacobbe, a 52-year-old management consultant, was looking to book a flight from New York City to Genoa, Italy—a trip he’s made numerous times for family visits. He’d always relied on Skyscanner for a discount.
This time, the cheapest fare wasn’t that cheap: It was for an Alitalia flight that made two stops, through Milan and Rome, for $2,050. Surprised at the high quote, he decided to call Alitalia. Immediately, the airline offered a $1,550 flight with only one stop in Rome. It was cheaper. It would get there faster. They even offered him a discounted car rental.
Through the careful study of excavation records dating back some 40 years, Michigan State University’s Jon Frey has discovered an ancient gymnasium at the archaeological site of Isthmia, Greece. Frey and his team are performing a “digital dig” of sorts. Rather than using shovels and tools to excavate the site, the researchers are studying a backlog of evidence housed in remote storage.
“The neat part is there are many moments when we discover things that the original excavators missed,” says Frey, assistant professor of classical studies in the College of Arts and Letters. “So it’s kind of like our research has shifted from digging to detective work. We’re essentially re-excavating the archives.”
New York, NY Join the Science Alliance as we discuss the postdoctoral programs outside Academ ia.Thursday, April 27, starting at 6 p.m., The New York Academy of Sciences [$$]
What can artificial intelligence learn from biological brains? At this Wednesday’s lunch seminar series at CDS, Professor Partha Mithra from the Cold Spring Harbor Laboratory explained how he has been mapping biological brain connectivity in his Mouse Brain Architecture Project to discover how we can transfer biological brain architectures to machine brains.
AI has made major strides in the last decade but, as Mithra explained, they still have some drawbacks when compared to biological brains. Not only do they use more power (100,000 W compared to 10 W!), but machine brains also require a much larger data set to train on than biological brains, and have non-biological fragilities.