Duke University School of Medicine, Department of Pediatrics
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When four Duke researchers developed an innovative technique for exploring the non-coding genome—the 98 percent of our DNA that does not encode protein sequences, often called the genome’s “dark matter”—the implications were clear. Their approach, using technologies including CRISPR gene editing to shed new light on gene regulation, has enormous potential to guide development of new drugs to combat a host of genetic diseases.
The question the researchers then faced was: How best to develop those new therapies in order to make them available to patients? The answer: Take the work beyond the academic lab and into the world of commercialization.
The four researchers—Greg Crawford, PhD, associate professor in the Department of Pediatrics; Charlie Gersbach, PhD, Rooney Family Associate Professor of Biomedical Engineering; Tim Reddy, PhD, associate professor of biostatistics and bioinformatics; and Kris Wood, PhD, assistant professor of pharmacology and cancer biology—launched a startup company called Element Genomics. Last spring, Element made big news when a global pharmaceutical firm, UCB, acquired it for $30 million.
There’s recent news about some really interesting hardware implants. I wanted to take a bit to share more technical thoughts and details that can’t be reduced to a mainstream article on the topic.
The core of the claim is that someone implanted extra components on some server motherboards that would do malicious stuff, subvert the system and possibly allow it to ‘phone home’. I looked at the claims through a technical and feasibility lens.
I’ve studied hardware implants for a few years now. I’ve done multiple reviews of server hardware looking for backdoors. I profit, via @securinghw and @SecureHardware, from people being more interested in hardware security.
That’s the extent of my knowledge. I have no specific information about the implants being reported on. I do feel like my background qualifies me to comment from a technical perspective.
Medium, Trust Medua & Democracy, Knight Foundation
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How did misinformation spread during the 2016 presidential election and has anything changed since? A new study of more than 10 million tweets from 700,000 Twitter accounts that linked to more than 600 misinformation and conspiracy news outlets answers this question.
The report reveals a concentrated “fake news” ecosystem, linking more than 6.6 million tweets to fake news and conspiracy news publishers in the month before the 2016 election. The problem persisted in the aftermath of the election with 4 million tweets to fake and conspiracy news publishers found from mid-March to mid-April 2017. A large majority of these accounts are still active today.
At the beginning of this year, we started an effort called Project Strobe—a root-and-branch review of third-party developer access to Google account and Android device data and of our philosophy around apps’ data access. This project looked at the operation of our privacy controls, platforms where users were not engaging with our APIs because of concerns around data privacy, areas where developers may have been granted overly broad access, and other areas in which our policies should be tightened.
We’re announcing the first four findings and actions from this review today.
Finding 1: There are significant challenges in creating and maintaining a successful Google+ product that meets consumers’ expectations.
Action 1: We are shutting down Google+ for consumers.
Apple, Amazon, and Supermicro each released a forceful denial that their systems were tampered with following the publication of a Bloomberg Businessweek report last week, which alleged that Chinese agents introduced microchips into servers manufactured in the country. In a letter to Congressional officials, Apple reiterated its denial, saying that it has found no sign of tampering.
Reuters obtained a letter written by George Stathakopoulos, Apple’s Vice President for Information Security, which he sent to the commerce committees for both the US Senate and US House. In it, he says that “Apple’s proprietary security tools are continuously scanning for precisely this kind of outbound traffic, as it indicates the existence of malware or other malicious activity. Nothing was ever found.” He also reiterated that Apple hadn’t contacted the FBI over such an issue, as alleged in the report, and indicated that he would be available to brief Congressional staff in the coming days.
At the Vdara Hotel and Spa in Las Vegas, robots are at the front line of room service. “Jett” and “Fetch” are delivery robots, designed to look like dogs, each about three feet high.
They can bring items from the hotel’s cafe right to your room. Among their many capabilities, they can travel alone across the lobby, remotely call for an elevator, and even alert guests when they arrive at their hotel room through an automated phone message.
It’s not just Vdara that’s experimenting with this technology. Other Las Vegas hotels, including the Renaissance Las Vegas, are using automation to cater to customers’ needs. So too was the Mandarin Oriental before changing over to the Waldorf Astoria this summer. And at bars like the Tipsy Robot, it’s the machines that are making the drinks. [audio, 7:24]
Stanford undergraduate Lena Zlock is developing a first-ever digital humanities study of Voltaire’s personal library, which contains over 6,700 books. She aims to make the library’s contents easily accessible and searchable online.
Churn rates (how fast users abandon your app / service) are really important in modelling a business. If the churn rate is too high, it’s hard to maintain growth. Since acquiring new customers is also typically much more expensive than expanding in existing accounts, churn hits you twice over. So it’s really important to understand what causes users to churn in your business, and ideally to be able to predict users likely to churn so that you can intervene. This paper describes ClusChurn, the churn prediction system deployed at Snapchat.
The Department of Transportation is getting a little more creative about how it defines “driver,” Secretary Elaine Chao announced Thursday. In the third version of the department’s official stance on self-driving, the department said it would “adapt the definitions of ‘driver’ and ‘operator’ to recognize that such terms to not refer exclusively to a human, but may in fact include an automated system.” The computers have a ticket to drive now—at least where federal regulations are concerned.
And while this is good news for everyone working on building, and eventually deploying, self-driving vehicles, it’s especially welcome for the automated trucking crowd. Waymo, Daimler, Volvo, Embark Trucks, Kache.ai, Starsky and Kodiak Robotics, TuSimple, Ike: Automated trucking companies have boomed this year, even after Uber got out of the trucking race. And all these VC-funded people would one day like to use their robot vehicles to transport the 50 million tons of freight shipped on American highways each day.
New York, NY October 13, starting at 12 noon, Music Education (45 W 18th St). “Music Community Lab presents an afternoon exploring the intersection of music, technology, education and creativity.” [free, rsvp required]
ArviZ is a Python package for exploratory analysis of Bayesian models. Includes functions for posterior analysis, sample diagnostics, model checking, and comparison.
Sara Belt and Peter Gilks respectively lead the Creator and Free Revenue Product Insights teams at Spotify. In this article, Sara will explore the practice of User Research at Spotify, and Peter will lay out how Data Science and User Research work together to drive product decisions.
SSRC, Parameters, Sarah Connell and Julia Flanders
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This collection is distinctively poised between digital genres: with over 400 texts (approximately 11 million words), the collection is sizeable and well beyond the scope of a typical scholarly edition, but the level of detail and human attention represented in the encoding distinguishes it from typical large-scale text digitization efforts. Given such size and complexity, the management of error and inconsistency while encoding these texts in XML is a crucial task.