Apple is planning a big announcement to unveil its new video strategy next week, and there is a long list of unknowns about Apple’s plans. Now we know one thing: Netflix won’t be a part of them.
Online dating isn’t for the faint of heart or those easily discouraged, says Harry Reis, PhD, Professor of Psychology and Dean’s Professor in Arts, Sciences, and Engineering, at University of Rochester. “There’s the old saying that you have to kiss a lot of frogs to find a prince — and I think that really applies to online dating.”
Reis studies social interactions and the factors that influence the quantity and closeness of our relationships. He coauthored a 2012 review article that analyzed how psychology can explain some of the online dating dynamics.
Elsevier, the company behind scientific journals such as The Lancet, left a server open to the public internet, exposing user email addresses and passwords. The impacted users include people from universities and educational institutions from across the world.
It’s not entirely clear how long the server was exposed or how many accounts were impacted, but it provided a rolling list of passwords as well as password reset links when a user requested to change their login credentials.
“Most users are .edu [educational institute] accounts, either students or teachers,” Mossab Hussein, chief security officer at cybersecurity company SpiderSilk who found the issue, told Motherboard in an online chat. “They could be using the same password for their emails, iCloud, etc.”
Fishery‐dependent data are integral to sustainable fisheries management. A paucity of fishery data leads to uncertainty about stock status, which may compromise and threaten the economic and food security of the users dependent upon that stock and increase the chances of overfishing. Recent developments in the technology available to collect, manage and analyse fishery‐relevant data provide a suite of possible solutions to update and modernize fisheries data systems and greatly expand data collection and analysis. Yet, despite the proliferation of relevant consumer technology, integration of technologically advanced data systems into fisheries management remains the exception rather than the rule. In this study, we describe the current status, challenges and future directions of high‐tech data systems in fisheries management in order to understand what has limited their adoption. By reviewing the application of fishery‐dependent data technology in multiple fisheries sectors globally, we show that innovation is stagnating as a result of lack of trust and cooperation between fishers and managers. We propose a solution based on a transdisciplinary approach to fishery management that emphasizes the need for collaborative problem‐solving among stakeholders. In our proposed system, data feedbacks are a key component to effective fishery data systems, ensuring that fishers and managers collect, have access to and benefit from fisheries data as they work towards a mutually agreed‐upon goal. A new approach to fisheries data systems will promote innovation to increase data coverage, accuracy and resolution, while reducing costs and allowing adaptive, responsive, near real‐time management decision‐making to improve fisheries outcomes. [full text]
Claiming that unconstrained advances in meat-sauce application was as far beyond human calculation as its potential to harm future generations, KC Masterpiece CEO Benno Dorer warned Monday against society’s increasing reliance on A1. “When applied correctly—and, crucially, in judicious amounts—it’s true that A1 can improve our lives, but we are a increasing risk of becoming wholly dependent on it,” said Dorer, noting that most Americans bring A1 into their homes without considering whether the benefits of the tangy, tomato-based condiment outweigh the costs. “This isn’t some science fiction fantasy. This is reality. A1 is already here, and we’re just handing over our flavor autonomy to this sauce even when we don’t fully understand it. At least with KC Masterpiece, the sweet heat you feel is real. Ask yourself—can you handle our new Wildflower Honey Habeñero?” Dorer further urged Americans to examine how A1 affects their lives and honestly try to imagine a life without it.
The biggest lesson that can be read from 70 years of AI research is that general methods that leverage computation are ultimately the most effective, and by a large margin. The ultimate reason for this is Moore’s law, or rather its generalization of continued exponentially falling cost per unit of computation. Most AI research has been conducted as if the computation available to the agent were constant (in which case leveraging human knowledge would be one of the only ways to improve performance) but, over a slightly longer time than a typical research project, massively more computation inevitably becomes available. Seeking an improvement that makes a difference in the shorter term, researchers seek to leverage their human knowledge of the domain, but the only thing that matters in the long run is the leveraging of computation. These two need not run counter to each other, but in practice they tend to. Time spent on one is time not spent on the other. There are psychological commitments to investment in one approach or the other. And the human-knowledge approach tends to complicate methods in ways that make them less suited to taking advantage of general methods leveraging computation. There were many examples of AI researchers’ belated learning of this bitter lesson, and it is instructive to review some of the most prominent.
To tell the Keck story, Caltech magazine turned to those oral histories, weaving one narrative from seven storytellers. The entire set of interviews may be found on the website of the Caltech Oral History Project. This is the first in a series of articles on the past, present, and future of the Keck Observatory and the science done there that will appear in Caltech’s print and online publications.
Faced with Wi-Fi that too often slowed to a crawl during the middle of class, Purdue University has taken a bold step to restore order to its network: It has banned Netflix.
Starting this week, the West Lafayette, Ind., campus is blocking the popular streaming video service in all of its academic buildings, along with other bandwidth-eating sites such as Hulu and HBO. The move comes after some faculty complained that the network had become so slow that academic applications were unusable during class.
The most powerful computer ever built in the United States will make its home at Argonne National Laboratory in 2021, the U.S. Department of Energy and Intel announced today. Aurora, the United States’ first exascale computer, will combine unprecedented processing power with the growing potential of artificial intelligence to help solve the world’s most important and complex scientific challenges.
As an exascale computer, Aurora will be capable of a quintillion—or one billion billion—calculations per second, 50 times quicker than today’s most powerful supercomputers. But the impact of the system goes beyond faster and larger data processing to new frontiers of scientific inquiry, supercharging modern artificial intelligence approaches for finding new cancer treatments, searching for dark matter, mapping the human brain and other massive breakthroughs.
Upon delivery, researchers will be able to use Aurora through the leadership computing facilities at Argonne, a U.S. Department of Energy laboratory operated by the University of Chicago.
Still depending on your kids to figure out why your smartphone’s acting weird? As a rule, children are wired to explore, experiment and get results through trial and error – usually more quickly than grownups. But why?
That and similar questions will be covered Tuesday, March 19, by UC Berkeley developmental psychologist Alison Gopnik, who is presenting one of the two talks at this year’s Martin Meyerson Faculty Research Lectures, a 106-year-old campus tradition.
San Diego, CA May 17. “The IEEE VIC Summit brings together leading innovators, visionaries, and disruptors in technology to discuss, explore, and uncover what is imminent, what is possible – and what these emerging technologies mean for our future.” [registration required]
Calvin College , Department of Mathematics and Statistics
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Grand Rapids, MI June 10-12 at Calvin College. “This three-day workshop will provide an introduction to using Stan for Bayesian data analysis. Stan® is a state-of-the-art platform for statistical modeling and high-performance statistical computation.” [$$$]
Atlanta, GA April 9-10. “The 2019 All Hands Meeting will bring the South Hub community together to share accomplishments and opportunities.” [registration required]
Ithaca, NY “Cornell Computing & Information Science has much to celebrate in 2019: steadily increasing class enrollments and declared majors, newsworthy improvements in student gender parity and diversity, and the commemoration of the founding of CIS 20 years ago this fall! We invite you to save the date for a 20th anniversary celebration planned for October 2-3, 2019 on campus. Conveniently, the event precedes Homecoming Weekend (October 4-6).”
Bridging the gap between computational photography and visual recognition. CVPR 2019 workshop in June. Competition tracks for problem challenges and for papers. [registration required for challenge tracks]
A number of our individual needs are knowable and addressable only in context. But there is more we can do at a baseline level to help our work communities thrive.
I’m going to focus on two such baseline categories: Environment (work space) and management (relationships). Lots has been said about the latter, and I’ll add my 2 cents in a follow-up post. For now, here are some thoughts about the former.
Computer science terms once exclusively used in scientific communities have become ubiquitously integrated into our daily lives—the news we read, products we consume, and the technology we use. Some are used interchangeably with one another (incorrectly), others are hazy in definition and application. In light of this, we thought we’d lend clarity to the top Machine Translation (MT) related computer science terms you may encounter.
If your organization is like most, you’ve been deploying systems for business process automation and treating the data generated from these deployments as a byproduct rather than as a business asset. It’s time to transform this data into a competitive advantage as giants such as Google and Amazon have. The way to accomplish this is with data operations (DataOps).
The question is where to begin. If you haven’t read Andy Palmer’s Upside interview about DataOps, do so now. It’s a terrific introduction and overview of DataOps, covering why it’s gaining traction, how it’s evolving, and why it’s so important in large enterprises. Palmer also addresses key components, challenges, examples of successful implementations, and what’s in store for DataOps over the next three to five years.
You might have read the infamous blog posts titled “Rails is Dead”, but I have seen development teams flounder over and over again when they try and reinvent the wheel using NodeJS on the backend.
Rails is Scalable
Despite the negative press, I’ll argue rails does scale.
On a typical day in the United States, police officers make more than 50,000 traffic stops. Our team is gathering, analyzing, and releasing records from millions of traffic stops by law enforcement agencies across the country. Our goal is to help researchers, journalists, and policymakers investigate and improve interactions between police and the public.