In 2020, the r/Datahoarder community on reddit is almost 200,000 members strong, with around 1,000 or so idling or posting in the subreddit at any time. The communal purpose here is exactly what it sounds like: these amateur archivists set out to collect and capture data and to preserve it for record, reference, and future reading. Often, the goal is to retain this information both online and off, through physical media or terabytes of personal harddrives and storage. In a way, you can think of r/Datahoarder like thousands of haphazard individual Internet Archives—though each member tends to have a few specific niche areas of focus.
On r/Datahoarder, you’ll find people storing data on everything from YouTube videos to game install discs. One person was even planning to copy all Australia-based websites even as the country burned in the worst wildfires in history. The post was deleted after it was pointed out that the physical servers for Australian websites are located outside the country. They’re safe for now—phew.
False-negative results from coronavirus tests are becoming an increasing concern, say doctors trying to diagnose patients and get a grip on the outbreak, as a surprising number of people show up with obvious symptoms only to be told by the tests that they don’t have the disease.
While still more research is necessary to determine the true prevalence of such false-negative results, experts agree that the problem is significant. False negatives not only impede the diagnosis of disease in individual patients and an accurate understanding of the extent of its proliferation, but also risk patients who think they aren’t ill further spreading the virus.
Some doctors described situations in which patients show up with clear symptoms such as a cough and fever, test negative, and then test positive later on. It’s a particular issue in New York, where the disease has likely infected far more than the 174,000 people confirmed through limited testing. At Jacobi Medical Center in the Bronx, doctor Jeremy Sperling says so-called false-negative tests are now a frequent occurrence in the emergency room.
As the coronavirus pandemic drags on, tech companies are stepping into the void left by a reluctant or incapable federal government — enabling contact tracing, wrestling with testing, and ramping up the capacity of government operations like unemployment services.
Why it matters: In the U.S., these giant firms — teeming with creative and restless employees, cushioned by big financial reserves and spurred on by the urgency of the moment — have stopped waiting for the government to move and begun taking their own initiative.
The co-workers were early links in what was to be the first documented chain of multiple human-to-human transmissions outside Asia of COVID-19, the disease caused by the coronavirus.
They are based in Stockdorf, a German town of 4,000 near Munich in Bavaria, and they work at car parts supplier Webasto Group. The company was thrust under a global microscope after it disclosed that one of its employees, a Chinese woman, caught the virus and brought it to Webasto headquarters. There, it was passed to colleagues – including, scientists would learn, a person lunching in the canteen with whom the Chinese patient had no contact.
The Jan. 22 canteen scene was one of dozens of mundane incidents that scientists have logged in a medical manhunt to trace, test and isolate infected workers so that the regional government of Bavaria could stop the virus from spreading.
That hunt has helped Germany win crucial time to build its COVID-19 defences.
During my time of self-isolation, I happened to come across a relatively new A.I. solution that seeks to dramatically alter the digital landscape for those with disabilities. Speaking from personal experience, I’ve spent the last eight-years caring for my neighbor (now close-friend) who is blind. By observing how she is able to use her iPhone, Amazon Echo, and JAWS programs to help her stay updated with what’s going on around her, it’s also taught me how necessary it is for our digital landscape to provide a more accessible means to information–because at the end of the day, it does make it difficult.
That’s where accessiBE comes into play. Though the needs of those with disabilities have historically been largely overlooked in the digital sphere, increased awareness of the issues those with disabilities face and powerful solutions like accessiBe have brought “web accessibility” front and center.
If I had to pick two companies to work together on this, it would be Apple and Google.
They essentially have the entire phone platform market with Android and iOS. Apple is considered better on personal data privacy but I figure that if Google goes along, Apple wouldn’t let such an effort devolve into a data-mining scheme for targeted ads. Put another way: I can’t think of any other large technology companies with the reach of Apple and Google that people trust with personal health data in some capacity.
Trump’s Easter forecast came more than two months after the first U.S. case of COVID-19 was identified, in Washington State, and more than a hundred days after the novel coronavirus emerged, first from bats and then from a live-animal market in the Chinese city of Wuhan. Every day, more people were falling sick and dying. Despite a catastrophic lack of testing capacity, it was clear that the virus had reached every corner of the nation. With the Easter holiday just a few weeks away, there was not a single public-health official in the United States who appeared to share the President’s rosy surmises.
Anthony Fauci certainly did not. At seventy-nine, Fauci has run the National Institute of Allergy and Infectious Diseases for thirty-six years, through six Administrations and a long procession of viral epidemics: H.I.V., SARS, avian influenza, swine flu, Zika, and Ebola among them. As a member of the Administration’s coronavirus task force, Fauci seemed to believe that the government’s actions could be directed, even if the President’s pronouncements could not. At White House briefings, it has regularly fallen to Fauci to gently amend Trump’s absurdities, half-truths, and outright lies. No, there is no evidence that the malaria drug hydroxychloroquine will provide a “miracle” treatment to stave off the infection. No, there won’t be a vaccine for at least a year. When the President insisted for many weeks on denying the government’s inability to deliver test kits for the virus, Fauci, testifying before Congress, put the matter bluntly. “That’s a failing,” he said. “Let’s admit it.”
The French Competition Authority (FCA) has told Google to negotiate with French news companies to determine fees due for the re-use their content.
In a statement, the FCA said, Google’s practices were “likely to constitute an abuse of a dominant position, and caused serious and immediate harm to the press sector.”
The ruling gives Google three months to come to reach an acceptable price with French publishers for using snippets of their articles in Google News, Google Search, and other services.
Boston University may delay reopening its campus until January 2021, the school said in a university news article Friday. The move comes as universities across New England and the country evaluate ways to keep their fall semesters intact while adhering to best practices for public health.
Massachusetts universities shuttered one after another in March as the coronavirus outbreak intensified, cancelling in-person classes and asking students to move out of on-campus housing to stem the virus’ spread. Since then, some schools have begun repurposing facilities to contribute to the state’s response efforts.
Just this week, Northeastern University and Tufts University opened up campus dormitories to house patients, medical professionals and first responders unable or unwilling to return home for fear of infecting their families.
Apple used to be about changing the world one magic box at a time. Now it’s fighting to conquer TV drama, healthcare, money, news and much else besides
Just a few weeks ago, McAfee researchers tricked a Tesla into accelerating 50 miles per hour above its intended speed by adding a two-inch piece of tape on a speed limit sign. The research was one of the first examples of manipulating a device’s machine learning algorithms.
That’s where DARPA hopes to come into play. The research arm said earlier this year that it’s working on a program known as GARD, or the Guaranteeing AI Robustness against Deception. The existing mitigations against machine learning attacks are typically rule-based and pre-defined, but DARPA hopes it can develop GARD into a system that will have broader defenses to address a number of different kinds of attacks.
Intel said today it’ll serve as the prime contractor for the four-year program alongside Georgia Tech.
After a change in the rules of the bold open-access (OA) initiative known as Plan S, publisher Springer Nature said on 8 April that many of its non-OA journals — including Nature — were now committed to joining the plan, pending discussion of further technical details.
This means that Nature and other Nature-branded journals that publish original research will now look to offer an immediate OA route after January 2021 to scientists who want it, or whose funders require it, a spokesperson says. (Nature is editorially independent of its publisher, Springer Nature.)
The announcement marks the first time that the publisher has said its most prestigious journals will be compliant with Plan S, meaning that researchers whose funders have joined the OA initiative should be able to continue publishing there. Previously, Springer Nature had said it wanted to offer an OA route in these titles, but not unless Plan S rules changed.
Online The conference “has been turned into an online event to provide an opportunity for our legal tech community to connect and learn about legal tech innovations from around the world. On this webpage, you can access podcasts and videos featuring the academics, entrepreneurs, lawyers, investors, policymakers, and engineers spearheading the tech-driven transformation of our legal systems.”
Online Late-April. “NYCCSS is a monthly event series aimed at building a community of researchers, practitioners, and students interested in Computational Social Science in New York City.” [registration required]
Raleigh, NC October 18-20. “We are seeking submissions from established technologists with many years of experience, technologists and community members that may be new to “open”, and everything in between.” Deadline for proposals is April 17.
Using data from the widely circulated Johns Hopkins COVID-19 tracking map, a cross-disciplinary team of JHU researchers recently began developing an array of new data visualization tools to help animate and explain the trends driving the pandemic, giving users real-time insights into how it is evolving around the world.
The effort is led by the Johns Hopkins Centers for Civic Impact, in partnership with the Johns Hopkins Applied Physics Laboratory, the Whiting School of Engineering, and the Bloomberg School of Public Health. The Johns Hopkins COVID-19 tracking map, developed by associate professor Lauren Gardner and her team at the Center for Systems Science and Engineering, has become a definitive source of information about confirmed cases of novel coronavirus and related deaths around the world. Launched in January and shared on an open source platform to invite collaboration across the globe, the map’s data is currently accessed more than a billion times each day.
Proceedings of the National Academy of Sciences; Mayank Agrawal, Joshua C. Peterson, and Thomas L. Griffiths
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Do large datasets provide value to psychologists? Without a systematic methodology for working with such datasets, there is a valid concern that analyses will produce noise artifacts rather than true effects. In this paper, we offer a way to enable researchers to systematically build models and identify novel phenomena in large datasets. One traditional approach is to analyze the residuals of models—the biggest errors they make in predicting the data—to discover what might be missing from those models. However, once a dataset is sufficiently large, machine learning algorithms approximate the true underlying function better than the data, suggesting, instead, that the predictions of these data-driven models should be used to guide model building. We call this approach “Scientific Regret Minimization” (SRM), as it focuses on minimizing errors for cases that we know should have been predictable. We apply this exploratory method on a subset of the Moral Machine dataset, a public collection of roughly 40 million moral decisions. Using SRM, we find that incorporating a set of deontological principles that capture dimensions along which groups of agents can vary (e.g., sex and age) improves a computational model of human moral judgment. Furthermore, we are able to identify and independently validate three interesting moral phenomena: criminal dehumanization, age of responsibility, and asymmetric notions of responsibility.
The first lesson on leading a remote team when the world’s on fire is the most obvious one, but it’s shockingly easy to miss: the operative phrase is not remote team but world’s on fire. This is true whether you’re a veteran of remote practices or you have recently had to instruct people in the correct use of the mute button on video calls. If you’re in the latter camp, it’s likely you’ve had to deal with all kinds of unfamiliar and annoying logistical challenges these past few weeks, but don’t let them distract you: remote practices are a MacGuffin. Your attention must be turned to managing through the fire.
The second lesson is harder, I’m afraid. You have no idea how to do this. I’ve managed remote teams for a decade and I have no idea how to do this. None of us has experience leading a team through a global pandemic. You are going to get more things wrong than you get right.
“Wait, how did Netflix know I wanted to watch that? Spooky… right? Well, not exactly. Through the use of Machine Learning, Collaborative Filtering, NLP and more, Netflix undertake a 5 step process to not only enhance UX, but to create a tailored and personalised platform to maximise engagement, retention and enjoyment.”
