Little is known about how the tiny engineered objects known as nanoparticles affect the environment when they escape. A stream of new commercial applications for the diverse, super-tiny particles — in everything from paint and dental implants to sunscreen and scratch-proof eyeglasses — have far outstripped the environmental science.
New research from the University of Minnesota shows why that could be a problem.
Researchers found that a bacterium commonly found in soil and water adapts rapidly when exposed to certain nanoparticles that are used in lithium ion batteries, so that the bacterium that would have died on exposure became permanently resistant.
Hijacking IP addresses is an increasingly popular form of cyber-attack. This is done for a range of reasons, from sending spam and malware to stealing Bitcoin. It’s estimated that in 2017 alone, routing incidents such as IP hijacks affected more than 10 percent of all the world’s routing domains. There have been major incidents at Amazon and Google and even in nation-states — a study last year suggested that a Chinese telecom company used the approach to gather intelligence on western countries by rerouting their internet traffic through China.
Existing efforts to detect IP hijacks tend to look at specific cases when they’re already in process. But what if we could predict these incidents in advance by tracing things back to the hijackers themselves?
That’s the idea behind a new machine-learning system developed by researchers at MIT and the University of California at San Diego (UCSD). By illuminating some of the common qualities of what they call “serial hijackers,” the team trained their system to be able to identify roughly 800 suspicious networks — and found that some of them had been hijacking IP addresses for years.
Bezos’s ventures are by now so large and varied that it is difficult to truly comprehend the nature of his empire, much less the end point of his ambitions. What exactly does Jeff Bezos want? Or, to put it slightly differently, what does he believe? Given his power over the world, these are not small questions. Yet he largely keeps his intentions to himself; many longtime colleagues can’t recall him ever expressing a political opinion. To replay a loop of his interviews from Amazon’s quarter century of existence is to listen to him retell the same unrevealing anecdotes over and over.
To better understand him, I spent five months speaking with current and former Amazon executives, as well as people at the company’s rivals and scholarly observers. Bezos himself declined to participate in this story, and current employees would speak to me only off the record. Even former staffers largely preferred to remain anonymous, assuming that they might eventually wish to work for a business somehow entwined with Bezos’s sprawling concerns.
“But until we have a hint of a beginning of a design, with some visible path towards autonomous AI systems with non-trivial intelligence, we are arguing about the sex of angels.” Yann LeCun.
There’s yet another online debate raging between world-renowned AI experts. This time it’s the big one: will AI rise up and murder us all? While this isn’t a new topic – humans have postulated about AI overlords for centuries – the timing and people involved in this debate make it interesting.
Machines struggle to make sense of scenes and language without detailed accompanying annotations. Unfortunately, labeling is generally time-consuming and expensive, and even the best labels convey an understanding only of scenes and not of language.
In an attempt to remedy the problem, Microsoft researchers conceived of an AI system that trains on image-text pairs in a fashion mimicking the way humans improve their understanding of the world. They say that their single-model encoder-decoder Vision-Language Pre-training (VLP) model, which can both generate image descriptions and answer natural language questions about scenes, lays the groundwork for future frameworks that could reach human parity.
PLOS Biology; B. Ian Hutchins, Matthew T. Davis, Rebecca A. Meseroll, George M. Santangelo
from
Fundamental scientific advances can take decades to translate into improvements in human health. Shortening this interval would increase the rate at which scientific discoveries lead to successful treatment of human disease. One way to accomplish this would be to identify which advances in knowledge are most likely to translate into clinical research. Toward that end, we built a machine learning system that detects whether a paper is likely to be cited by a future clinical trial or guideline. Despite the noisiness of citation dynamics, as little as 2 years of postpublication data yield accurate predictions about a paper’s eventual citation by a clinical article (accuracy = 84%, F1 score = 0.56; compared to 19% accuracy by chance). We found that distinct knowledge flow trajectories are linked to papers that either succeed or fail to influence clinical research. Translational progress in biomedicine can therefore be assessed and predicted in real time based on information conveyed by the scientific community’s early reaction to a paper. [full text]
Stanford University, Stanford Medicine, News Center
from
As little as a daily ping on your phone can boost physical activity, researchers from the Stanford University School of Medicine and their collaborators report in a new study.
The finding comes by way of the first-ever entirely digital, randomized clinical trial, which sought to answer two overarching questions: Is it feasible to successfully run an entirely digital, randomized clinical trial? And is it possible to encourage people to exercise more by using a smartphone app?
Hans Rosling — a Swedish doctor, statistician, author and professor — will be a name associated with the University of Washington’s transformative work in population health. Today, the UW Board of Regents approved naming the $230 million building under construction on UW’s Seattle campus the Hans Rosling Center for Population Health.
“Hans Rosling was a visionary scholar who challenged the world to truly understand the health challenges we face, as well as the potential we have to overcome them. It was this unique combination of practicality and optimism that drove his work, and inspired so many to action,” said UW President Ana Mari Cauce. “I hope the faculty, students, staff and partners who come together in the building are equally inspired by Dr. Rosling’s legacy as they work to improve the well-being of people in Washington and around the world.”
The Daily Californian student newspaper, Sasha Langholz
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UC Berkeley received a $3 million grant Monday from the Public Interest Technology University Network, or PIT-UN, a partnership between 21 different universities intended to grow the field of public interest technology.
The partnership was announced in March and intends to advance public interest technology, or PIT, through the creation of a “robust pipeline” for students across disciplines. PIT-UN is a partnership between New America, the Ford Foundation and the Hewlett Foundation. It aims to facilitate collaboration between technologists and public policy leaders in “serving society,” Jennifer Mangold, principal investigator and director of the Fung Fellowship, said in a Fung Fellowship press release.
University of Maryland, The Diamondback student newspaper, Eric Neugeboren
from
[Amitabh] Varshney proposed a learning initiative offered through the university for professionals to take classes. And next month, Varshney’s idea will come to fruition with the launch of the University of Maryland’s Science Academy.
The Academy, which will be taught by staff from his college as well as the engineering school, will offer working professionals one of two master’s degrees of Professional Studies in Data Science and Machine Learning — concepts Varshney said are vital to the current STEM workforce.
“One of the big challenges now is that a lot of the fields that we are in are changing quite rapidly,” Varshney said. “Twenty years ago, [these subjects] barely existed. And it would be a shame for the working professionals of the area not to know the details of this.”
Over 65 companies, social organizations and research institutions on 8 October launched the Dutch AI Coalition (NL AIC). The parties want the Netherlands to be a force to be reckoned with when it comes to artificial intelligence. The participants include Albert Heijn, Booking, Google, IBM, KLM, KPN, Microsoft, Philips, Shell, TNO and Unilever.
Simultaneously, the Dutch government presented the Strategic Action Plan AI (SAPAI). This plan focuses on taking advantage of opportunities in AI and includes funding for researchers and entrepreneurs. It also discusses essential requirements for a successful application of AI, like education, data usage, digital infrastructure and the protection of civil rights.
Last year, “21 different teams participated in the forecasting initiative, submitting 30 different weekly forecasts. The Delphi group at Carnegie Mellon University contributed the most accurate national-, regional-, and state-level influenza-like illness and national-level hospitalization forecasts,” the CDC says.
This marks the fourth year in a row that CMU has come out on top.
In honor of that record of ace prognostication, the CDC announced this week that CMU has been named an Influenza Forecasting Center of Excellence, a designation that comes with $3 million in research funding over the next five years.
Right now, consumer data is the fuel that powers the information economy. Online banking, shopping and other services use personal data to authenticate customer identities and prevent fraud. Many companies use personal data to target ads to their audience, find prospective hires and more. These functions offer safety or convenience benefits to consumers. Without personal data, mobile banking wouldn’t be possible, and online advertising would be random and unhelpful. But handling personal data is a big responsibility. And over the past couple of years, there’s been story after story in the media of consumer data being stolen, mishandled or used in ways that consumers didn’t realize they’d agreed to.
London, England November 2-3. “An annual festival of over 90 sessions, Battle of Ideas will return to the Barbican in 2019 for another weekend of free-thinking and lively debate.” [$$]
London, England November 20-21. “The Facebook Testing and Verification (TAV) symposium brings together academia and industry to deliver a meaningful collaboration and exchange between testing and verification scientific research and practice.” [registration required]
“The ACM-W Rising Star Award recognizes a woman whose early-career research has had a significant impact on the computing discipline, as measured by factors such as frequent citation of their work, creation of a new research area, a high degree of technology transfer and/or other positive influences and societal impact.” Deadline for nominations is November 15.
“The program, led by NSF in partnership with the National Institute of Food and Agriculture, U.S. Department of Homeland Security’s Science & Technology Directorate, U.S. Department of Transportation’s Federal Highway Administration and U.S. Department of Veterans Affairs, has both planning and institute tracks. The planning track will support planning grants for up to two years and $500,000 to enable teams to develop collaborative plans and capacity for full institute operations. The institute track will support cooperative agreements of $16 million to $20 million for four to five years (up to $4 million per year) for the creation of AI Research Institutes in an initial set of high-priority areas.” Deadline for proposal submissions is January 28, 2020.
The NumFOCUS DISCOVER Cookbook (Diverse & Inclusive Spaces and Conferences: Overall Vision and Essential Resources) is produced by the NumFOCUS Diversity & Inclusion in Scientific Computing (DISC) Program, with support from the Moore Foundation.
Over the last 24 months we have gone on a hiring spree for data science talent to build the IBM Data Science Elite Team. In two hiring sprints of 3 months each, we hired about 100 data scientists globally (San Francisco, Austin, New York, London, Munich, Singapore and Sydney). In this round of hiring we built a team that has more than double the industry average female representation 1.
In this blog, I will lay out the hiring practices we followed to hire the team. Our efforts to drive diversity as part of this process will be detailed in a separate post.