All posts in “Software”

Facebook may begin testing a paywall for selected media stories as soon as October

Facebook could begin testing a paywall for subscription news stories as early as October, according to a top company executive.

Campbell Brown, who heads up the social network’s new partnerships business, made the reveal at the Digital Publishing Innovation Summit on Tuesday, The Street reported. We have independently confirmed that, too.

“We are in early talks with several news publishers about how we might better support subscription business models on Facebook. As part of the Facebook Journalism Project, we are taking the time to work closely together with our partners and understand their needs,” Brown told TechCrunch in a statement via a spokesperson.

The project is still in its infancy, and it may be subject to change, but TechCrunch understands that the current plan is to work with a handful of publishers to introduce a system that would limit free viewing to 10 articles per month, as Digiday previously reported. After viewing 10 articles from the media company, a user would be promoted to sign up for a subscription to that publication or log into an active one.

That number is rigid at 10, despite the fact that publishers that operate a paywall allow varying numbers of free articles for visitors per month. A source to Facebook said the number would be the same across all partners to ensure consistency for users.

The source stressed that Facebook would allow participating media partners to maintain full control over which stories are locked behind the paywall and which aren’t, and full control of their subscriber data, too. At this point it is unclear exactly what access to reading data and history, which can help increase engagement, the media partners would get.

Equally, it isn’t clear how payment will be taken for subscribers who sign up via the Facebook paywall. Digiday reports the social network is considering bypassing Google Play and Apple’s App Store to avoid the mandatory 30 percent cut that each operator takes from digital payments. That may require a mobile web payment option, which would add friction to the user experience, potentially impacting the effectiveness of the program.

There’s certainly much to be confirmed. For one thing, which media firms will participate.

Facebook remains in talks with prospective partners, some of which have had one-on-one briefings while others were engaged via roundtables staged in New York and Paris last week. All being well, our source said that Facebook will look to broaden the paywall feature to more users next year, but there’s some way to go before that happens.

Featured Image: Bryce Durbin/TechCrunch

Stox to launch token sale for its new prediction market is’s prediction market product and it’s getting a little boost through a newly-opened token sale using Bancor’s smart token protocol. This announcement, while full of jargon, means that Stox will be able to raise money to develop infrastructure and increase its marketing and sales groups.

Stox is a spin-off of, an established player in the financial market. Invest sees $50 million in annual revenue and 3 million registered clients. Stox will be an “open source, Ethereum-based prediction market platform” according to the team.

“The biggest difference, is that there is a real, substantial, experienced company behind this,” said CEO Ophir Gertner. “This isn’t a few folks and a whitepaper that have never managed a company, dealt with user acquisition, weather the ups and downs, etc.”

The team is calling its raise a “token generation event,” a move that distances them from the concept of the initial coin offering or ICO so popular in crypto jargon. Users can use the single token on to “trade” on the outcome of “finance, sports, politics and even the weather.” Because it is open source anyone can connect to the platform and post a trade.

“Stox will feature as its debut provider, but will be built in such a way that allows independent operators to join and partake in its ecosystem as well,” said Gertner.

The team isn’t concerned about the recent dip in cryptocurrencies.

“Rather than a negative signal for the space, we see it as supporting our assertion that this is exactly why you need real companies involved,” said Gertner. “Teams that have weathered the ups and downs of running a real business, that are experienced in user acquisition, and so forth.”

BloomAPI locks down $2.4M to fix medical record releases

Seattle-based BloomAPI is announcing a $2.4 million seed round led by Founders’ Co-op this morning for its solution to the broken medical records release process. It’s no secret that the entire U.S. healthcare system is held back by antiquated technology — but unlike many competitors, BloomAPI offers a solution that works with, and not against, the old-school technologies that are still the unfortunate reality for the industry.

BloomAPI sits on top of existing systems, integrates quickly and doesn’t cost doctors a dime. As a result of this orientation, the solution doesn’t functionally change any existing human processes. When it comes to privacy, patients are still expected to sign all the same documentation and waivers they traditionally would for record releases — it’s just the conduit for the actual document transfer that has been streamlined.

Michael Wasser, founder and CEO of BloomAPI

The company makes its money by charging third parties, like insurance companies and other vendors, for API access. This allows the company to scale faster across doctors’ offices to give the myriad medical record salve startups a run for their money.

“With BloomAPI, data sharing just becomes simple,” asserted Michael Wasser, founder of BloomAPI in an interview. “This way you don’t even have to question whether a medical record is available.”

To date, BloomAPI has onboarded 300 doctors with access to more than 1 million individuals. That process is clearly more difficult and decentralized than a traditional big-ticket enterprise SaaS contract, but Wasser tells me this is part of his secret sauce.

Other competitors have taken a top-down approach, promising to fix the massive medical records problem by promising interoperability across major hospital groups. Wasser believes this is the wrong strategy, and many players attempting to make it work are getting caught up in complex negotiations with maligned incentives.

“Doctors hear ‘interoperability’ and say this will come but it never actually shows up,” explained Wasser. “We are saying, you already do medical record releases, we just want to make it happen better.”

The company plans to continue to simplify the onboarding process for doctors and begin introducing some machine learning capabilities. If BloomAPI is able to sit on top of disparate systems of record, it would have the opportunity to take a more active role in organizing medical records. Some day this could mean pulling diagnosis codes from paper documents and classifying documents.

Today’s round also included Y Combinator, Slow Ventures, Founders’ Co-Op, Section 32 (Bill Maris’s new fund), Liquid 2 Ventures, Fifty Years Fund, TWB Investment Partnership, Wei Fund, Parker Conrad and other angels.

Featured Image: Medioimages/Photodisc/Getty Images

MateLabs mixes machine learning with IFTTT

If you’ve ever wanted to train a machine learning model and integrate it with IFTTT, you now can with a new offering from MateLabs. MateVerse, a platform where novices can spin out machine learning models, now works with IFTTT so that you can automatically set up models to run based on conditional statements.

If you’re not familiar with IFTTT, it’s an automation tool for creating your own if/then statements without any programming knowledge. The service makes it possible to say, receive a notification if the temperature outside rises above 50 degrees or post pictures directly to Twitter.

MateLabs’ integration works much the same way, but with machine learning. As of now, the company is offering computer vision and natural language processing tools that can respond to Twitter, Slack, Google Drive, Facebook and more. Hypothetically, you could set up a process to analyze a Twitter mention to determine why the mention occurred.

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Of course you can build your own models — if you would like you can upload your own data on the MateVerse platform and train your own models for specific use cases. All of this is useful for those who might be unfamiliar with complex machine learning frameworks, but that doesn’t mean more advanced developers couldn’t also benefit from the streamlined experience.

As this technology matures it will be cool to see what hackers are able to do with it. I can imagine that one could build some weird IFTTT integrations with hardware — i.e. a camera that can turn on specific lights depending on whether you or your cat walks into a room.

Featured Image: Bryce Durbin

Codota raises $2M from Khosla as autocomplete for developers

In recent years, GitHub has fundamentally changed developer workflows. By centralizing code on an easily accessible platform, the company was able to rapidly change the way people code. Following in these footsteps, Israeli startup Codota wants to further optimize workflows for the often neglected developer community — this time with machine intelligence. The company is announcing a $2 million seed round from Khosla Ventures for its autocomplete tool that helps engineers push better code in less time.

Codota interfaces with integrated development environments like Eclipse, expanding on intelligent code completion. Instead of just offering up brief suggestions of intended code, Codota can recommend larger chunks.

Co-founders Dror Weiss and Eran Yahav took advantage of open source code on the internet from GitHub and StackOverflow to build Codota. All of this public code was fed into machine learning models to enable them to recognize higher-level meaning across blocks of code.

The Codota team at its Tel Aviv headquarters

Programing languages share a lot of structural similarities with their distant spoken cousins. Words can be arranged in infinitely many ways to express a single thought or sentiment. Likewise, the same command can be represented in code in a number of ways. This is why it’s so critical that Codota understands the macro picture of what code is doing.

Of course natural language and code are not completely analogous. The team explained in an interview that in natural language processing, meaning is determined by looking at nearby words. Programs are more structured and meaning isn’t always strongly correlated with locality. So instead of just training on text, Codota also focused on the behaviors of a program.

Aside from improving speed and accuracy, Codota can help with discovery and education. Because Codota has been trained on millions of API implementations, it can help offer up best practices to developers. When open side-by-side with an IDE, the tool can highlight irregularities and demonstrate better ways to write code, lessons often pulled straight from the original creators of libraries.

The startup makes its money by allowing enterprises to keep their internal code private while benefitting from Codota’s insights. Right now the tool is limited to Java, but in the future additional languages will be added.

Featured Image: maciek905/Getty Images