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Enlarge (credit: StickerGiant / Flickr)
Hackers are actively exploiting a vulnerability that allows them to execute commands and malicious scripts on Websites running File Manager, a WordPress plugin with more than 700,000 active installations, researchers said on Tuesday. Word of the attacks came a few hours after the security flaw was patched.
Attackers are using the exploit to upload files that contain webshells that are hidden in an image. From there, they have a convenient interface that allows them to run commands in plugins/wp-file-manager/lib/files/, the directory where the File Manager plugin resides. While that restriction prevents hackers from executing commands on files outside of the directory, hackers may be able to exact more damage by uploading scripts that can carry out actions on other parts of a vulnerable site.
NinTechNet, a website security firm in Bangkok, Thailand, was among the first to report the in-the-wild attacks. The post said that a hacker was exploiting the vulnerability to upload a script titled hardfork.php and then using it to inject code into the WordPress scripts /wp-admin/admin-ajax.php and /wp-includes/user.php.
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Pakistan says it has blocked dating apps Tinder, Grindr, Tagged, Skout, and SayHi for violating local laws and streaming “immoral content” — KARACHI, Pakistan (Reuters) - Pakistan said on Tuesday it has blocked Tinder, Grindr and three other dating apps for not adhering to local laws …
Amazon is spying on private Facebook Groups for Flex drivers in US, UK, and Spain, monitoring for complaints and labor actions, per internal reports left online — The company is surveilling dozens of private Facebook groups in the United States, the United Kingdom, and Spain …
Biden campaign releases official yard signs for Animal Crossing that players can use to decorate their virtual homes, as politicians try to reach voters online — It's the campaign's latest foray into online organizing — Starting today, September 1st, Animal Crossing …
Apple allows Facebook, Instagram, and Twitter to sell ads, which are digital goods, in their iOS apps via direct transactions, avoiding IAP and the 30% cut — Why should Facebook—the biggest beneficiary of the iPhone, its tools, and its infrastructure—pay $99.-, when small developers have to pay tens and hundreds of thousands?
Walmart unveils its new membership service Walmart+, launching Sept. 15 for $98 per year, will offer free, unlimited same-day delivery, fuel discounts, and more — Walmart today officially unveiled its new membership service and Amazon Prime rival, which it's calling “Walmart+.”
Stanford launches Cable TV News Analyzer, a free AI-powered online service for querying the screen time of public figures or specific topics on cable TV news — A new AI-powered tool can show you how much screen time different public figures and topics are getting on TV.
The Walmart+ membership program launches September 15. Can it offer an alternative to Amazon Prime? | Walmart
One Walmart executive says the new program is “the ultimate life hack”
Walmart’s much-anticipated membership program, Walmart+, will finally launch nationwide September 15, the company announced today, about six months after the Covid-19 pandemic pushed the retailer to delay its original timing. The brick-and-mortar retail giant needs the program to be successful to stop top-spending customers from fleeing to Amazon Prime.
Walmart+ will cost $98 a year, or $12.95 a month, and focus mainly on unlimited delivery of groceries and other general merchandise from Walmart stores that will be delivered as soon as the same day they are ordered. Members also get fuel discounts at Walmart gas stations and those of partners, as well as access to “Scan & Go” technology which allows shoppers to use smartphones to scan goods at Walmart stores and exit without stopping to pay a cashier. The company says it will add more perks in the future. Recode previously reported these may include a branded credit card, early availability on product deals, and potentially access to a popular streaming video service.
Walmart wants the membership program to be “the ultimate life hack” for customers, Walmart Chief Customer Officer Janey Whiteside told Recode in an interview on Monday, arguing that its perks will save customers both time and money.
At the same time, Walmart+ will undoubtedly attract comparisons to Amazon’s Prime program, the ultra popular delivery and entertainment membership program that boasts more than 150 million members worldwide and has developed into a retail industry wrecking ball since its launch in 2005. Amazon Prime includes express delivery of millions of products (including groceries), video streaming of a large library of TV shows and movies, music streaming, and other perks. It now costs $119 a year, and Prime customers spend more and shop more frequently than non-Prime members.
And, most importantly for Walmart, more than half of Walmart’s top-spending families are now Prime members, as Recode previously reported. Which begs the question: Will they really subscribe to both membership programs?
When asked about comparisons to Prime on Monday, Whiteside told Recode that “we didn’t necessarily launch Walmart+ to compete with anything else.” And that answer makes sense; the head-to-head comparison between the services does not look great for Walmart when considering online customers who value the widest selection of goods or the longest list of perks.
In addition to the unlimited delivery perk — which is basically just a rebrand of Walmart’s existing Delivery Unlimited membership — Walmart+ only features two other benefits at launch. One is fuel discounts of up to 5 cents per gallon at Walmart, Murphy USA, and Murphy Express gas stations (Sam’s Club gas stations are slated to be included soon). The other perk is access to Walmart’s “Scan & Go” technology for in-store shopping, which allows shoppers to scan items with their phone, scan their phone at a self-checkout kiosk, and walk out of the store without stopping to pay. Walmart briefly tested, but discontinued the tool, two years ago. Walmart’s bet is that the mix of online, in-store, and on-the-go perks, like fuel discounts, will carry unique appeal. Whiteside said that “deepening a relationship further will mean we will get an even greater share of wallet from those customers.” Of course, some Walmart shoppers will also value the $21 difference between the annual fee of Walmart+ and Amazon Prime.
Amazon has made moves in recent years for Prime to appeal to households with less disposable income that historically have favored shopping at Walmart. Amazon added a monthly payment option for Prime fees in 2016, a 45 percent Prime fee discount for those on government assistance in 2017, and most recently, ways for Prime customers to pay for orders with cash. By early 2017, Amazon Prime membership growth was strongest in the US for households making less than $50,000 a year, according to a study by Robert W. Baird & Co.
The success of Walmart+ will likely hinge on how many customers are attracted to the core grocery delivery component of it. While Walmart’s overall grocery business is larger than Amazon’s and its prices are often cheaper, one fear is that top Walmart customers could eventually turn to Amazon for groceries as they get sucked further into the Prime suite of perks. Sources previously told Recode that some Walmart execs believe that top-spending Walmart families that subscribe to Amazon Prime will still be attracted to Walmart+ because its fresh grocery prices are often lower than those Amazon offers.
In the past, some Walmart executives have opposed a paid membership program, seeing Walmart’s competitive advantage as giving shoppers everyday low prices without the need to splurge on a membership fee. Whiteside promised that the low prices will remain even for those who don’t splurge for the bonus services.
“In no way does this membership program take anything away from customer who don’t choose to, or can’t afford to, engage with this,” he said.
On the company’s earnings call earlier this month, CEO Doug McMillon stressed the flexibility of Walmart’s customer offerings.
“We’re going to have multiple ways to serve them, and those families will decide in that moment how they want to shop,” McMillon said. “And sometimes they’ll be in the store, and sometimes they’ll do pickup, and sometimes they’ll do delivery, and many of them will buy a membership, and when they do they’ll get benefits from that.”
The health care system today largely focuses on helping people after they have problems. When they do receive treatment, it’s based on what has worked best on average across a huge, diverse group of patients.
Now the company Health at Scale is making health care more proactive and personalized — and, true to its name, it’s doing so for millions of people.
Health at Scale uses a new approach for making care recommendations based on new classes of machine-learning models that work even when only small amounts of data on individual patients, providers, and treatments are available.
The company is already working with health plans, insurers, and employers to match patients with doctors. It’s also helping to identify people at rising risk of visiting the emergency department or being hospitalized in the future, and to predict the progression of chronic diseases. Recently, Health at Scale showed its models can identify people at risk of severe respiratory infections like influenza or pneumonia, or, potentially, Covid-19.
“From the beginning, we decided all of our predictions would be related to achieving better outcomes for patients,” says John Guttag, chief technology officer of Health at Scale and the Dugald C. Jackson Professor of Computer Science and Electrical Engineering at MIT. “We’re trying to predict what treatment or physician or intervention would lead to better outcomes for people.”
A new approach to improving health
Health at Scale co-founder and CEO Zeeshan Syed met Guttag while studying electrical engineering and computer science at MIT. Guttag served as Syed’s advisor for his bachelor’s and master’s degrees. When Syed decided to pursue his PhD, he only applied to one school, and his advisor was easy to choose.
Syed did his PhD through the Harvard-MIT Program in Health Sciences and Technology (HST). During that time, he looked at how patients who’d had heart attacks could be better managed. The work was personal for Syed: His father had recently suffered a serious heart attack.
Through the work, Syed met Mohammed Saeed SM ’97, PhD ’07, who was also in the HST program. Syed, Guttag, and Saeed founded Health at Scale in 2015 along with David Guttag ’05, focusing on using core advances in machine learning to solve some of health care’s hardest problems.
“It started with the burning itch to address real challenges in health care about personalization and prediction,” Syed says.
From the beginning, the founders knew their solutions needed to work with widely available data like health care claims, which include information on diagnoses, tests, prescriptions, and more. They also sought to build tools for cleaning up and processing raw data sets, so that their models would be part of what Guttag refers to as a “full machine-learning stack for health care.”
Finally, to deliver effective, personalized solutions, the founders knew their models needed to work with small numbers of encounters for individual physicians, clinics, and patients, which posed severe challenges for conventional AI and machine learning.
“The large companies getting into [the health care AI] space had it wrong in that they viewed it as a big data problem,” Guttag says. “They thought, ‘We’re the experts. No one’s better at crunching large amounts of data than us.’ We thought if you want to make the right decision for individuals, the problem was a small data problem: Each patient is different, and we didn’t want to recommend to patients what was best on average. We wanted what was best for each individual.”
The company’s first models helped recommend skilled nursing facilities for post-acute care patients. Many such patients experience further health problems and return to the hospital. Health at Scale’s models showed that some facilities were better at helping specific kinds of people with specific health problems. For example, a 64-year-old man with a history of cardiovascular disease may fare better at one facility compared to another.
Today the company’s recommendations help guide patients to the primary care physicians, surgeons, and specialists that are best suited for them. Guttag even used the service when he got his hip replaced last year.
Health at Scale also helps organizations identify people at rising risk of specific adverse health events, like heart attacks, in the future.
“We’ve gone beyond the notion of identifying people who have frequently visited emergency departments or hospitals in the past, to get to the much more actionable problem of finding those people at an inflection point, where they are likely to experience worse outcomes and higher costs,” Syed says.
The company’s other solutions help determine the best treatment options for patients and help reduce health care fraud, waste, and abuse. Each use case is designed to improve patient health outcomes by giving health care organizations decision-support for action.
“Broadly speaking, we are interested in building models that can be used to help avoid problems, rather than simply predict them,” says Guttag. “For example, identifying those individuals at highest risk for serious complications of a respiratory infection [enables care providers] to target them for interventions that reduce their chance of developing such an infection.”
Impact at scale
Earlier this year, as the scope of the Covid-19 pandemic was becoming clear, Health at Scale began considering ways its models could help.
“The lack of data in the beginning of the pandemic motivated us to look at the experiences we have gained from combatting other respiratory infections like influenza and pneumonia,” says Saeed, who serves as Health at Scale’s chief medical officer.
The idea led to a peer-reviewed paper where researchers affiliated with the company, the University of Michigan, and MIT showed Health at Scale’s models could accurately predict hospitalizations and visits to the emergency department related to respiratory infections.
“We did the work on the paper using the tech we’d already built,” Guttag says. “We had interception products deployed for predicting patients at-risk of emergent hospitalizations for a variety of causes, and we saw that we could extend that approach. We had customers that we gave the solution to for free.”
The paper proved out another use case for a technology that is already being used by some of the largest health plans in the U.S. That’s an impressive customer base for a five-year-old company of only 20 people — about half of which have MIT affiliations.
“The culture MIT creates to solve problems that are worth solving, to go after impact, I think that’s been reflected in the way the company got together and has operated,” Syed says. “I’m deeply proud that we’ve maintained that MIT spirit.”
And, Syed believes, there’s much more to come.
“We set out with the goal of driving impact,” Syed says. “We currently run some of the largest production deployments of machine learning at scale, affecting millions, if not tens of millions, of patients, and we are only just getting started.”
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American citizens are inundated with political messages—on social networks, in their news feeds, through email, text messages, and phone calls. It’s not an accident that people get bombarded: political groups prefer a “multimodal” voter contact strategy, where they use many platforms and multiple attempts to persuade a citizen to engage with their cause or candidate. An ad is followed by an email, which is followed by a text message—all designed to reinforce the message.
These strategies are employed by political campaigns, political action committees, advocacy groups, and nonprofits alike. These different groups are subject to very different rules and regulations, but they all rely on capturing and devouring data about millions of people in America.
Almost everyone. Most campaigns get their voter information from a handful of data vendors, either nonpartisan or partisan. These companies try to provide data on all US adults, regardless of whether they are registered voters. It’s unlikely that an individual vendor has comprehensive files on all eligible US voters, but the Pew Research Center, which released a report on commercial voter files in 2018, found that over 90% of people in its own sample of US adults could be found on at least one registry.
The main source of voter data is public voting records, which include a voter’s names, address, and party affiliation. But voter data is very patchy and decentralized: each state holds its own database, and they often have different attributes. So vendors supplement it with other sources, like phone books and credit data.
It’s hard to get a full picture of everything that is fed into the vendors’ databases: the recipe each one uses is usually considered a trade secret. Pew’s study explained that the registries are “an amalgamation of administrative data from states about registration and voting, modeled data about partisanship, political engagement and political support provided by vendors; and demographic, financial and lifestyle data culled from a wide range of sources.”
Data vendors attempt to match up and reconcile these different data sets to create one comprehensive record for each person in the US based on key identifiers like name, address, gender, and date of birth.
L2 is one of the largest companies trading in this information, and it claims to have more than 600 data attributes pulled from census data, emails from commercial sources, donor data sets, and more. Experts say that most vendors provide hundreds of data points about each voter.
It’s up for debate. Some data points are very accurate, but others are really just predictions or guesses. Party and race, for example, are often inferred on the basis of someone’s name and location. Somebody with the last name Ryan is assumed to be white, while somebody in a heavily Republican district is assumed to be a Republican voter.
The accuracy of specific attributes varies a lot: Pew found that race was accurate 79% of the time, education 51%, and religion 52%. Household income, meanwhile, was accurate just 37% of the time. There was also measurable bias, with higher error rates for younger, highly mobile, unregistered, and Hispanic voters.
Eitan Hersh, a professor at Tufts who testified to Congress after the Cambridge Analytica scandal in 2016, believes the data—particularly the modeled attributes—is inaccurate to the point of hindering its usefulness for campaigns. In his testimony, he noted that models he’d studied assumed a person’s race incorrectly 25% of the time. And race is much easier to predict than a person’s swing issue.
Campaigns and other political groups purchase data from vendors, but they often combine information and attach additional data sets to it. Campaigns will also create data sets themselves from social-media testing and advertisement data, though it’s not clear just how common this practice is.
They often use all this to try to identify adults who will respond to a specific issue. For example, a campaign might develop a model to find voters who support climate change legislation. The model might use these data sets to spit out a list of voters ranked on a scale from 1 to 100, with 100 being those most likely to strongly support the cause. The campaign could then choose to send a message to voters with a score higher than 70 in an effort to encourage mobilization.
Although it’s arguable whether targeted advertising shifts the way people vote, it has proved extremely useful in harvesting other contact information, like email addresses, and in raising money.
Your social-media information—such as the public Facebook posts you’ve liked or the Twitter hashtags you’ve used—can be combined with other data at many different stages. Some vendors integrate social-media data into their main data set, especially for people whose profile matches their name. That information can help build better predictive models.
Infamously, Cambridge Analytica gamed Facebook by acquiring information on 270,000 users from a third-party app, and pulled the friend networks of those users until it had a data set covering 87 million people, most of whom had not consented and were not aware this was happening. It claimed to run models on that data to generate personalized and predictive political pictures of users.
But the effectiveness of such techniques is up for debate.
A 2013 study by psychologist Michal Kosinski, on which Cambridge Analytica based many of its methods, argued that the data from 150 likes on Facebook is enough for an algorithm to know your “sensitive personal attributes” better than a family member does. But Cambridge Analytica was not able to produce any evidence that it succeeded in creating these algorithms, or that any of its targeting persuaded anybody. It’s incredibly hard to attribute any vote to a particular ad, article, or tweet.
One of the most important uses of social-media information is to refine and target messaging. A/B testing has gotten so precise that campaigns can keep tweaking a given ad until it becomes hyper-specific to the user.
Targeted ads are messages directed to people on the basis of their confirmed or suspected political identities. Many focus on issue persuasion, voter mobilization, or fundraising, and some groups use much more sophisticated approaches than others.
Targeting methods include email, telephone, and text message, but much of the advertising takes place online—on Facebook, Google, and Instagram. Twitter banned political ads this November, though 501c(3) nonprofit groups are still able to use targeting on the platform. In order to target a voter, groups will use specific filters in order to reach exactly who they want—for example, women on college campuses in Michigan. On Facebook, and possibly on other social platforms as well, campaigns can actually target individuals directly by uploading a list of accounts—perhaps just a tiny number of people, if the advertiser wants to do extremely specific personalized messaging.
Different groups are subject to different rules. 501c(3) groups like Turning Point USA or the Tides Foundation can’t advance any electoral or candidate messages. They are also exempt from donor-disclosure laws. Political campaigns, on the other hand, are subject to campaign finance laws and oversight by the Federal Election Commission.
But although campaign-sponsored advertisements must be identified as such, on the internet it is often unclear who exactly is trying to grab your attention and support. Misinformation and manipulation get confused with official campaign messaging, while campaigns can skirt accountability by distancing themselves from more controversial groups with parallel messages.
Polling data suggests it is likely that this election will be decided in the suburbs. In 2016, it was suburban counties that gave Trump the electoral edge even while he trailed in the popular vote. And suburban voters use Facebook … a lot. Campaigns and advocacy groups can use the growing power of data crunching to speak directly to those voters. So far, Donald Trump has spent twice as much on Facebook ads as Joe Biden.
