Starting in July, you might have to pay a little extra to see the newest blockbusters when using MoviePass . The movie subscription service has plans to instate surge pricing for non-annual subscribers starting at $2 for movies and times the app deems “very popular,” Business Insider reports.
This comes one day after AMC announced its plan for a competing movie subscription service called AMC Stubs A-List, coming in June. In MoviePass CEO Mitch Lowe’s statement to Business Insider, he seemed unfazed by AMC’s entrance into the subscription game, saying instead it “validates that subscription is really here to stay.”
But for MoviePass to stay, it might have to start changing it business plan. The subscription service’s parent company Helios and Matheson Analytics announced today that MoviePass’ monthly losses soared to $40 million in May. The company also expects its cash deficit to reach $45 million by June. These numbers are in part a reflection of the 545,000 new users who joined the service between May 1st and June 15th.
In addition to a few additional dollars to see the next dinosaur movie or superhero film this summer, MoviePass said it plans to roll out two new programs come August that will bring in a little extra money as well. Starting at the end of August, users will be able to use the app to watch IMAX or Real 3D movies for an additional $2 to $6 and have the option to bring a friend (though, they’ll have to pay almost full price for the additional ticket) through the app. To start, these features will have to be applied to separate films, but MoviePass has plans to combine them.
Payment provider PayPal continues apace with its acquisitions streak to bring more modern tools into its platform to serve its 237 million customers. Today the company announced that it is buying Simility, a fraud prevention specialist, for $120 million in cash.
PayPal had been an investor in Simility (it owns three percent of the company, it says), along with Accel, Trinity Ventures and others. The startup had raised just under $25 million and was last valued at $52.75 million, according to figures from PitchBook, making this a decent return for its backers. The deal is expected to close in Q3.
Online fraud involving either buyers or sellers has been one of the biggest limiting factors to the growth of e-commerce, and it has only grown as e-commerce has become more mature and spread to more platforms.
Simility’s approach is to use a set of APIs and beacons that essentially monitor digital transactions and buying activity wherever they happen to take place: on mobile, web or in physical environments Augmenting these with machine learning and feeds from other data sources, it creates something it calls “adaptive” risk management: a changing approach and protection strategy based on what the threat of the moment might be.
Acquiring a company like this makes sense on two levels for PayPal: not just for its own systems, but for that of its customers, who make PayPal-powered transactions on the web, on mobile and at physical points of sales.
“Digital commerce has exploded, and fraudsters have taken note, adapting and developing new methods to carry out their crimes,” said Bill Ready, chief operating officer, PayPal, in a statement. “PayPal has been at the forefront of developing innovative fraud prevention and risk management solutions for nearly 20 years, but until now, merchants haven’t been able to configure those solutions to manage the unique complexities of their businesses. Together with Simility, we will be able to put more control in the hands of our merchants to fight fraud while helping make commerce experiences faster and more secure.”
Ready in a separate blog described the company’s strategy currently as an effort to create a one-stop shop for all things commerce, and simplification is also an aspect of this deal: Simility already has a number of customers that also work with PayPal such as PayPal’s former owner eBay/StubHub, OfferUp, Dicks Sporting Goods and Rebtel. The acquisition will mean a more integrated approach for them where their PayPal services have a stronger layer of fraud protection on them, and they also get used to help form a bigger picture about the overall state of fraud that the companies.
PayPal said that after the deal closes, it will also extend Simility’s tools to the rest of the merchants on its platform.
“Our vision for Simility was to create an adaptive risk management platform that empowers organizations operating in a digital world to manage an evolving fraud and risk landscape where data breaches are the new normal,” said Rahul Pangam, co-founder and CEO, Simility, in a statement. “We are excited to enter the next phase of our growth with PayPal and are thrilled to join them to help drive the next generation of payment and commerce solutions while scaling our business together.”
PayPal has made a number of acquisitions over the last few weeks, all pointing to adding in new technologies and tools to reflect our changing times and how that is playing out in the world of payments. They have included European mobile payments and financial services business iZettle, payments aggregator Hyperwallet and AI-based CRM specialist Jetlore.
Payment provider PayPal continues apace with its acquisitions streak to bring more modern tools into its platform to serve its 237 million customers. Today the company announced that it is buying Simility, a fraud prevention specialist, for $120 million in cash.
PayPal had been an investor in Simility (it owns three percent of the company, it says), along with Accel, Trinity Ventures and others. The startup had raised just under $25 million and was last valued at $52.75 million, according to figures from PitchBook, making this a decent return for its backers. The deal is expected to close in Q3.
Online fraud involving either buyers or sellers has been one of the biggest limiting factors to the growth of e-commerce, and it has only grown as e-commerce has become more mature and spread to more platforms.
Simility’s approach is to use a set of APIs and beacons that essentially monitor digital transactions and buying activity wherever they happen to take place: on mobile, web or in physical environments Augmenting these with machine learning and feeds from other data sources, it creates something it calls “adaptive” risk management: a changing approach and protection strategy based on what the threat of the moment might be.
Acquiring a company like this makes sense on two levels for PayPal: not just for its own systems, but for that of its customers, who make PayPal-powered transactions on the web, on mobile and at physical points of sales.
“Digital commerce has exploded, and fraudsters have taken note, adapting and developing new methods to carry out their crimes,” said Bill Ready, chief operating officer, PayPal, in a statement. “PayPal has been at the forefront of developing innovative fraud prevention and risk management solutions for nearly 20 years, but until now, merchants haven’t been able to configure those solutions to manage the unique complexities of their businesses. Together with Simility, we will be able to put more control in the hands of our merchants to fight fraud while helping make commerce experiences faster and more secure.”
Ready in a separate blog described the company’s strategy currently as an effort to create a one-stop shop for all things commerce, and simplification is also an aspect of this deal: Simility already has a number of customers that also work with PayPal such as PayPal’s former owner eBay/StubHub, OfferUp, Dicks Sporting Goods and Rebtel. The acquisition will mean a more integrated approach for them where their PayPal services have a stronger layer of fraud protection on them, and they also get used to help form a bigger picture about the overall state of fraud that the companies.
PayPal said that after the deal closes, it will also extend Simility’s tools to the rest of the merchants on its platform.
“Our vision for Simility was to create an adaptive risk management platform that empowers organizations operating in a digital world to manage an evolving fraud and risk landscape where data breaches are the new normal,” said Rahul Pangam, co-founder and CEO, Simility, in a statement. “We are excited to enter the next phase of our growth with PayPal and are thrilled to join them to help drive the next generation of payment and commerce solutions while scaling our business together.”
PayPal has made a number of acquisitions over the last few weeks, all pointing to adding in new technologies and tools to reflect our changing times and how that is playing out in the world of payments. They have included European mobile payments and financial services business iZettle, payments aggregator Hyperwallet and AI-based CRM specialist Jetlore.
If you were still waiting patiently for the virtual reality features that Microsoft promised in 2016, then I have some bad news for you. During E3 last week, Microsoft’s chief marketing officer for gaming, Mike Nichols, told GamesIndustry.biz that the company had no plans to fulfill that promise.
“We don’t have any plans specific to Xbox consoles in virtual reality or mixed reality,” Nichols told GamesIndustry.biz.
This goes against a promise that Microsoft made two years ago when Xbox chief Phil Spencer told The Verge that the Xbox One X (then dramatically known as Xbox Scorpio) would support “[the kind of] high-end VR that you see happening in the PC space.”
The release of the Xbox One X came and went without any news of VR integration, but in the interim, Microsoft did make strides toward VR and mixed reality tech for PC gaming with the release of the Windows Mixed Reality headsets for Windows 10.
According to Nichols, it seems like Microsoft may be sticking to this PC gaming territory for awhile.
“PC is probably the best platform for more immersive VR and MR … but as it relates to Xbox, no,” he said.
If you were still waiting patiently for the virtual reality features that Microsoft promised in 2016, then I have some bad news for you. During E3 last week, Microsoft’s chief marketing officer for gaming, Mike Nichols, told GamesIndustry.biz that the company had no plans to fulfill that promise.
“We don’t have any plans specific to Xbox consoles in virtual reality or mixed reality,” Nichols told GamesIndustry.biz.
This goes against a promise that Microsoft made two years ago when Xbox chief Phil Spencer told The Verge that the Xbox One X (then dramatically known as Xbox Scorpio) would support “[the kind of] high-end VR that you see happening in the PC space.”
The release of the Xbox One X came and went without any news of VR integration, but in the interim, Microsoft did make strides toward VR and mixed reality tech for PC gaming with the release of the Windows Mixed Reality headsets for Windows 10.
According to Nichols, it seems like Microsoft may be sticking to this PC gaming territory for awhile.
“PC is probably the best platform for more immersive VR and MR … but as it relates to Xbox, no,” he said.
Someday we’ll have an app that you can point at a weird bug or unfamiliar fern and have it spit out the genus and species. But right now computer vision systems just aren’t up to the task. To help things along, researchers have assembled hundreds of thousands of images taken by regular folks of critters in real life situations — and by studying these, our AI helpers may be able to get a handle on biodiversity.
Many computer vision algorithms have been trained on one of several large sets of images, which may have everything from people to household objects to fruits and vegetables in them. That’s great for learning a little about a lot of things, but what if you want to go deep on a specific subject or type of image? You need a special set of lots of that kind of image.
For some specialties, we have that already: FaceNet, for instance, is the standard set for learning how to recognize or replicate faces. But while computers may have trouble recognizing faces, we rarely do — while on the other hand, I can never remember the name of the birds that land on my feeder in the spring.
Fortunately, I’m not the only one with this problem, and for years the community of the iNaturalist app has been collecting pictures of common and uncommon animals for identification. And it turns out that these images are the perfect way to teach a system how to recognize plants and animals in the wild.
Could you tell the difference?
You might think that a computer could learn all it needs to from biology textbooks, field guides, and National Geographic. But when you or I take a picture of a sea lion, it looks a lot different from a professional shot: the background is different, the angle isn’t perfect, the focus is probably off, and there may even be other animals in the shot. Even a good computer vision algorithm might not see much in common between the two.
The photos taken through the iNaturalist app, however, are all of the amateur type — yet they have also been validated and identified by professionals who, far better than any computer, can recognize a species even when it’s occluded, poorly lit, or blurry.
The researchers, from Caltech, Google, Cornell, and iNaturalist itself, put together a limited subset of the more than 1.6 million images in the app’s databases, presented this week at CVPR in Salt Lake City. They decided that in order for the set to be robust, it should have lots of different angles and situations, so they searched for species that have had at least 20 different people spot them.
The resulting set of images (PDF) still has over 859,000 pictures of over 5,000 species. These they had people annotate by drawing boxes around the critter in the picture, so the computer would know what to pay attention to. A set of images was set aside for training the system, another set for testing it.
Examples of bounding boxes being put on images.
Ironically, they can tell it’s a good set because existing image recognition engines perform so poorly on it, not even reaching 70 percent first-guess accuracy. The very qualities that make the images themselves so amateurish and difficult to parse make them extremely valuable as raw data; these pictures haven’t been sanitized or set up to make it any easier for the algorithms to sort through.
Even the systems created by the researchers with the iNat2017 set didn’t fare so well. But that’s okay — finding where there’s room to improve is part of defining the problem space.
The set is expanding, as others like it do, and the researchers note that the number of species with 20 independent observations has more than doubled since they started working on the dataset. That means iNat2018, already under development, will be much larger and will likely lead to more robust recognition systems.
The team says they’re working on adding more attributes to the set so that a system will be able to report not just species, but sex, life stage, habitat notes, and other metadata. And if it fails to nail down the species, it could in the future at least make a guess at the genus or whatever taxonomic rank it’s confident about — e.g. it may not be able to tell if it’s anthopleura elegantissima or anthopleura xanthogrammica, but it’s definitely an anemone.
A massive database of current U.S. Immigration and Customs Enforcement (ICE) employees scraped from public LinkedIn profiles has been removed from the tech platforms hosting the data. The project was undertaken by Sam Lavigne, self-described artist, programmer and researcher in response to recent revelations around ICE’s detention practices at the southern U.S. border.
Lavigne posted the database to GitHub on Tuesday and by Wednesday the repository had been removed. The database included the name, profile photo, title and city area of every ICE employee who listed the agency as their employer on the professional networking site. A more in-depth version of the data pulled all public LinkedIn data from the pool of users, including previous employment, education history and any other information those users opted to make public. The total database lists this information for 1,595 ICE employees, from the company’s CTO on down to low-level workers.
The project accompanied a Medium post about the project’s aims that has since been removed by the platform:
While I don’t have a precise idea of what should be done with this data set, I leave it here with the hope that researchers, journalists and activists will find it useful…
I find it helpful to remember that as much as internet companies use data to spy on and exploit their users, we can at times reverse the story, and leverage those very same online platforms as a means to investigate or even undermine entrenched power structures. It’s a strange side effect of our reliance on private companies and semi-public platforms to mediate nearly all aspects of our lives.
The data set appears to have violated GitHub and Medium guidelines against doxing. Medium’s anti-harassment policy specifically forbids doxing and defines it broadly, preventing “the aggregation of publicly available information to target, shame, blackmail, harass, intimidate, threaten, or endanger.”
Because it doesn’t include personal identifying information like home addresses, phone numbers or other non-public details, Lavigne’s project isn’t really doxing in the normal sense of the word, though that hasn’t made it less controversial.
GitHub’s own policy leading to the data’s removal is less clear, though the company told The Verge the repository was removed due to “doxxing and harassment.” The platform’s terms of service forbid uses of GitHub that “violate the privacy of any third party, such as by posting another person’s personal information without consent.” This leaves some room for interpretation, and it is not clear that data from a public-facing social media profile is “personal” under this definition. GitHub allows researchers to scrape data from external sites in order to aggregate it “only if any publications resulting from that research are open access.”
While Lavigne’s aggregation efforts were deemed off-limits by some tech platforms, they do raise compelling questions. What kinds of public data, in aggregate, run afoul of anti-harassment rules? Why can this kind of data be scraped for the purposes of targeted advertising or surveillance by law enforcement but not be collected in a user-facing way? The ICE database raised these questions and plenty more, but for some tech companies the question of hosting the data proved too provocative from the start.
Dating app Happn, whose “missed connections” type of dating experience connects people who have crossed paths in real life, is fighting back at Tinder. Seemingly inspired by Happn’s location-based features, Tinder recently began piloting something called Tinder Places – a feature that tracks your location to match you with those people who visit your same haunts – like a favorite bar, bookshop, gym, restaurant, and more.
Of course Tinder’s move into location-based dating should worry Happn, which had built its entire dating app around the idea of matching up people who could have met in real life, but just missed doing so.
Now, Happn is challenging Tinder Places with a new feature of its own. It’s debuting an interactive map where users can discover those people they’ve crossed paths with over the past seven days.
Happn founder, French entrepreneur Didier Rappaport, dismisses the Tinder threat.
“We don’t see it as a threat at all but as a good thing,” he tells TechCrunch. “Find the people you’ve crossed paths with has always been in Happn’s DNA since the beginning….We are very flattered that Tinder wants to include the same feature in its product. However, we will never use the swipe in our product,” he says.
Rappaport believes swiping is wrong because it makes you think of the other person as a product, and that’s not Happn’s philosophy.
“We want to [give our users a chance] to interact or not with a person, to take their time to decide, to be able to move back in their timeline if suddenly they change their mind and want to have a second chance,” he notes.
To use Happn’s map, you’ll tap on a specific location you’ve visited, and are then presented with potential matches who have been there too, or within 250 meters of that spot. The map will use the same geolocation data that Happn already uses to create its timeline, but just displays it in another form.
For those who aren’t comfortable sharing their location all the time with a dating app (um, everyone?), Happn also offers an “invisibility” mode that lets people hide their location during particular parts of the day – for example, while they’re at work.
While Happn’s new feature is a nice upgrade for regular users, Tinder’s location-based features – we’re sorry to report – are more elegantly designed.
Today, Happn’s invisibility mode has to be turned on when you want to use it, or you have to pay for a subscription to schedule to come on automatically at certain times. That means it requires more effort to use on a day-to-day basis.
Meanwhile, Tinder Places lets you block a regular place you visit – like, say, the gym – from ever being recorded as a place you want to show up for matches. It also automatically removes places that would be inappropriate, including your home and work addresses, and alerts you when it’s adding a new one – so you can quickly take action to remove it, if you choose. Tinder Places is also free. (It’s just not rolled out worldwide at this time).
Happn, however, does offer a way to hide your profile information and other details from select users, and never shows your current location in real time, also like Tinder.
Happn, which launched back in 2014, now claims nearly 50 million users worldwide, across 50 major cities and 40 countries. It claims to have 6.5 million monthly users – but that’s much smaller, compared with Tinder’s estimated 50 million actives.
From next month two Google StreetView cars will be driving around London’s streets fitted with sensors that take air quality readings every 30 meters to map and monitor air quality in the UK capital.
There will also be 100 fixed sensors fitted to lampposts and buildings in pollution blackspots and sensitive locations in the city — creating a new air quality monitoring network that Sadiq Khan, London’s mayor, is billing as “the most sophisticated in the world”.
The goal with the year-long project is to generate hyperlocal data to help feed policy responses. Khan has made tackling air pollution one of his priorities.
It’s not the first time StreetView cars have been used as a vehicle for pollution monitoring. Three years ago sensors made by San Francisco startup Aclima were fitted to the cars to map air quality in the Bay Area.
The London project is using sensors made by UK company Air Monitors.
The air quality monitoring project is a partnership between the Greater London Authority and C40 Cities network — a coalition of major cities around the world which is focused on tackling climate change and increasing health and well-being.
The project is being led by the charity Environmental Defense Fund Europe, in partnership with Air Monitors, Google Earth Outreach, Cambridge Environmental Research Consultants, University of Cambridge, National Physical Laboratory, and the Environmental Defense Fund team in the United States.
King’s College London will also be undertaking a linked study focused on schools.
Results will be shared with members of the C40 Cities network — with the ambition of developing policy responses that help improve air quality for hundreds of millions of city dwellers around the world.
We hope you’ve saved the date for the TechCrunch Summer Party at August Capital on July 27, because we’re releasing our second batch of tickets today. Jump on this opportunity, folks, because our first group of tickets sold out in a flash — and these babies, available on a first-come, first-served basis, won’t last long, either. Buy your ticket today.
If you haven’t attended our classic summer fete — this is our thirteenth year — you’re in for a treat. Enjoy the beautiful grounds and patio deck at August Capital in Menlo Park, lovely libations and a delicious snack or two. And do it all in the company of your peers, celebrating entrepreneurship and possibility.
Networking is always a part of every TechCrunch event, and you never know when you’ll meet the perfect future investor, founder or collaborator. True fact: Box founders Aaron Levie and Dylan Smith met one of their first investors, DFJ, at a backyard party hosted by TechCrunch founder, Michael Arrington.
Here are the when, where and how much details for the TechCrunch Summer Party at August Capital:
July 27, 5:30 p.m. – 9:00 p.m.
August Capital in Menlo Park
Ticket price: $95
Of course, there’s more than one way to enjoy this party. If you have an early-stage startup, buy a Summer Party demo table. It’s a great opportunity to showcase your business in front of all the right people in a relaxed, convivial atmosphere. Each demo table includes four Summer Party tickets. Learn more about demo tables here.
Come and share a friendly evening of cocktails and relaxed networking in a beautiful setting. Who knows, you might win nifty door prizes, including TechCrunch swag, Amazon Echos and tickets to Disrupt San Francisco 2018.
The second round of TechCrunch Summer Party at August Capital tickets is available now, and you can buy yours today. We hope to see you there!
