For those of us unlucky enough to be forced to accommodate mother nature’s whims on a monthly basis, you know that — in addition to cramps, headaches and mood swings — it can be a challenge to find time in your schedule to buy the period products you need.

Desperate trips to the pharmacy when disaster hits can suffice, but the co-founders of the tampon subscription service Athena Club, Maria Markina and Allie Griswold, thought there had to be a better way to provide women the products they need in a cheap and empowering way.

“We’ve both had our fair share of tampon war stories,” Griswold told TechCrunch. “It’s something that every woman goes through at some point in her life and it’s a universal problem that we wanted to make easier. There are so many other amazing things that women can and should be doing than worrying about [where to get tampons] every month.”

Athena Club launches today after receiving $3.8 million in seed funding from investors including Henry Kravis of KKR, the Desmarais Group, Cue Ball Capital, Philippe Laffont, Founder of Coatue Management and Robert Fetherstonhaugh. The company currently offers two tampon types (Premium and Organic) and a variety of absorbances (ranging from light to super+ for its Premium product and regular to super for its Organic one). The company also has plans to expand its products into pads and liners as the brand progresses.

In each order, customers can decide how many bags they need (each reusable bag includes 18 tampons), what type of tampon and what mix of absorbances they want, and how frequently they need them delivered. A selection of its Premium tampons cost $6.50/bag and its Organic selections are $7.50/bag.

For the founders, this level of customization was an important part of giving women autonomy over their periods.

“[We chose] the name Athena Club because we believe Athena is a really strong, fearless, independent woman and we’re very excited to bring that essence to our brand.” said Griswold. “Like Athena, women today have many passions and talents. They can’t all fit into one box and we want to provide [the option] to find the right customized package that works for their body.”

Athena Club also recognizes that for some women, access to tampons and period products is more than just a nuisance but a critical health issue. To help provide security and education surrounding periods and women’s health to women in need, Athena Club is committed to supporting groups like Period.org and Support the Girls. To date, Athena Club has already donated 10,000 tampons to women in need through Period.org and has plans to continue that support on a yearly basis.

Athena Club is joining a fairly crowded feminine care subscription space, but the founders say that its price point will help it stand apart from the crowd. Tampon subscription companies like LOLA offer a subscription plan priced at $10/box for 18 plastic applicator tampons (the same type and count as Athena Club) and Cora offers 18 tampons for $13/box. Other more extravagant boxes, like Hello Flo incorporate add-ons like chocolate or underwear in their boxes and can be priced upwards of $40.

And, all of these models are up against long-term, reusable period solutions like Thinx period underwear (which can cost up to $39 for two tampons worth of absorption per use) and plastic menstrual cups like the Diva Cup (which retails for $40.99.)

With so many options, Athena Club presents itself as the cheap, no-fuss solution for women who are through letting periods disrupt their lives.

Updated to reflect seed round funding contributions 

Sramana Mitra: How big did the company become revenue-wise? Ram Palaniappan: The company ended up with a private equity firm getting a stake in it. Subsequently, the company was acquired by a public...

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Joint pain is an ailment that has been around time immemorial and given the growing overweight population, it can be expected to be a challenge in the future as well. WellWrap is a wearable...

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As the economy has chugged along, so have retail sales, which last year capped their strongest year since 2014. Online sales have been especially brisk, growing 16 percent between 2016 and 2017 alone, according to the U.S. Commerce Department, which estimates that consumers spent $453.5 billion online last year.

Of course, with every booming market comes supporting cast members that benefit. Such is the case with eight-year-old, Washington, D.C.-based Optoro, which itself just rang up $75 million in new funding. A logistics company, Optoro’s software helps retailers — both online and off — more easily re-sell inventory that has been returned by customers.

That’s a big number. The overall amount of merchandise returned as a percent of total sales last year was 10 percent in 2017, according to the National Retail Federation. In dollars, that’s $351 billion.

Right now, that includes sales from big box retailers and many other “legacy” companies that allow shoppers to buy items — and return them — in their stores. But as online sales rise, so do online returns. Indeed, Optoro co-founder and CEO Tobin Moore tells the WSJ that the “return rate from e-commerce sales is two to three times the return rate of brick-and-mortar” and “sometimes higher in fashion and apparel.” And with most retailers also paying for shipping on returns — after all, a happy customer is a repeat customer — it’s a major logistics cost for these online brands.

Little wonder that Optoro, which uses data analytics and multi-channel online marketing to determine the best path for each item (ostensibly maximizing recovery and reducing environmental waste in the process) is a hit with a growing base of customers.

A growing number of investors is getting behind the company, too. Optoro’s newest round was led by Franklin Templeton Investments, but the company has now raised at least $200 million altogether, including from Revolution Growth, Generation Investment Management, Grotech Ventures and even the UPS Strategic Enterprise Fund.

Every artificial intelligence startup or corporate R&D lab has to reinvent the wheel when it comes to how humans annotate training data to teach algorithms what to look for. Whether it’s doctors assessing the size of cancer from a scan or drivers circling street signs in self-driving car footage, all this labeling has to happen somewhere. Often that means wasting six months and as much as a million dollars just developing a training data system. With nearly every type of business racing to adopt AI, that spend in cash and time adds up.

Labelbox builds artificial intelligence training data labeling software so nobody else has to. What Salesforce is to a sales team, Labelbox is to an AI engineering team. The software-as-a-service acts as the interface for human experts or crowdsourced labor to instruct computers how to spot relevant signals in data by themselves and continuously improve their algorithms’ accuracy.

Today, Labelbox is emerging from six months in stealth with a $3.9 million seed round led by Kleiner Perkins and joined by First Round and Google’s Gradient Ventures.

“There haven’t been seamless tools to allow AI teams to transfer institutional knowledge from their brains to software,” says co-founder Manu Sharma. “Now we have over 5,000 customers, and many big companies have replaced their own internal tools with Labelbox.”

Kleiner’s Ilya Fushman explains that “If you have these tools, you can ramp up to the AI curve much faster, allowing companies to realize the dream of AI.”

Inventing the best wheel

Sharma knew how annoying it was to try to forge training data systems from scratch because he’d seen it done before at Planet Labs, a satellite imaging startup. “One of the things that I observed was that Planet Labs has a superb AI team, but that team had been for over six months building labeling and training tools. Is this really how teams around the world are approaching building AI?,” he wondered.

Before that, he’d worked at DroneDeploy alongside Labelbox co-founder and CTO Daniel Rasmuson, who was leading the aerial data startup’s developer platform. “Many drone analytics companies that were also building AI were going through the same pain point,” Sharma tells me. In September, the two began to explore the idea and found that 20 other companies big and small were also burning talent and capital on the problem. “We thought we could make that much smarter so AI teams can focus on algorithms,” Sharma decided.

Labelbox launched its early alpha in January and saw swift pickup from the AI community that immediately asked for additional features. With time, the tool expanded with more and more ways to manually annotate data, from gradation levels like how sick a cow is for judging its milk production to matching systems like whether a dress fits a fashion brand’s aesthetic. Rigorous data science is applied to weed out discrepancies between reviewers’ decisions and identify edge cases that don’t fit the models.

“There are all these research studies about how to make training data” that Labelbox analyzes and applies, says co-founder and COO Ysiad Ferreiras, who’d led all of sales and revenue at fast-rising grassroots campaign texting startup Hustle. “We can let people tweak different settings so they can run their own machine learning program the way they want to, instead of being limited by what they can build really quickly.” When Norway mandated all citizens get colon cancer screenings, it had to build AI for recognizing polyps. Instead of spending half a year creating the training tool, they just signed up all the doctors on Labelbox.

Any organization can try Labelbox for free, and Ferreiras claims hundreds have. Once they hit a usage threshold, the startup works with them on appropriate SaaS pricing related to the revenue the client’s AI will generate. One called Lytx makes DriveCam, a system installed on half a million trucks with cameras that use AI to detect unsafe driver behavior so they can be coached to improve. Conde Nast is using Labelbox to match runway fashion to related items in their archive of content.

Eliminating redundancy, and jobs?

The big challenge is convincing companies that they’re better off leaving the training software to the experts instead of building it in-house where they’re intimately, though perhaps inefficiently, involved in every step of development. Some turn to crowdsourcing agencies like CrowdFlower, which has their own training data interface, but they only work with generalist labor, not the experts required for many fields. Labelbox wants to cooperate rather than compete here, serving as the management software that treats outsourcers as just another data input.

Long-term, the risk for Labelbox is that it’s arrived too early for the AI revolution. Most potential corporate customers are still in the R&D phase around AI, not at scaled deployment into real-world products. The big business isn’t selling the labeling software. That’s just the start. Labelbox wants to continuously manage the fine-tuning data to help optimize an algorithm through its entire life cycle. That requires AI being part of the actual engineering process. Right now it’s often stuck as an experiment in the lab. “We’re not concerned about our ability to build the tool to do that. Our concern is ‘will the industry get there fast enough?'” Ferreiras declares.

Their investor agrees. Last year’s big joke in venture capital was that suddenly you couldn’t hear a startup pitch without “AI” being referenced. “There was a big wave where everything was AI. I think at this point it’s almost a bit implied,” says Fushman. But it’s corporations that already have plenty of data, and plenty of human jobs to obfuscate, that are Labelbox’s opportunity. “The bigger question is ‘when does that [AI] reality reach consumers, not just from the Googles and Amazons of the world, but the mainstream corporations?'”

Labelbox is willing to wait it out, or better yet, accelerate that arrival — even if it means eliminating jobs. That’s because the team believes the benefits to humanity will outweigh the transition troubles.

“For a colonoscopy or mammogram, you only have a certain number of people in the world who can do that. That limits how many of those can be performed. In the future, that could only be limited by the computational power provided so it could be exponentially cheaper” says co-founder Brian Rieger. With Labelbox, tens of thousands of radiology exams can be quickly ingested to produce cancer-spotting algorithms that he says studies show can become more accurate than humans. Employment might get tougher to find, but hopefully life will get easier and cheaper too. Meanwhile, improving underwater pipeline inspections could protect the environment from its biggest threat: us.

“AI can solve such important problems in our society,” Sharma concludes. “We want to accelerate that by helping companies tell AI what to learn.”

Sramana Mitra: Talk about your current portfolio. What have you invested in? What are the highlights? As you’re describing, give us some insights into when they came to you, what did you see that...

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3D body scanning systems have hit the big time after years of stops and starts. Hot on the heels of Original Stitch’s Bodygram, another 3D scanner, 3DLOOK, has entered into the fray with a $1 million investment to measure bodies around the world.

The founders, Vadim Rogovskiy, Ivan Makeev, and Alex Arapovd, created 3DLOOK when they found that they could measure a human body using just a smartphone. The team found that other solutions couldn’t let them measure fits with any precision and depended on expensive hardware.

“After more than six years of building companies in the ad tech industry I wanted to build something new which was not a commodity,” said Rogovskiy. “I wanted to overcome growth obstacles and I learned that the apparel industry had mounting return problems in e-commerce. 3DLOOK’s co-founders spent over a year on pure R&D and testing new approaches and combinations of different technologies before creating SAIA (Scanning Artificial Intelligence for Apparel) in 2016.”

The team raised $400,000 to date and most recently raised a $1 million seed round to grow the company.

The team also collects “fit profiles” and is able to supply these profiles based on “geographic location, age, and gender groups.” This means that 3DLOOK can give you exact sizes based on your scanned measurements and tell you how clothes will fit on your body. They have 20,000 profiles already and are working with eight paying customers and five large enterprise systems. Lemonade Fashion and Koviem are both using the platform.

“3DLOOK is the first company that managed to build a technology that allows capturing human body measurements with just two casual photos, and plans to disrupt the market of online apparel sales, offering brands and small stores an API for desktop and SDK for mobile to gather clients measurements and build custom clothing proposals,” said Rogovskiy. “Additionally, the company collects the database of human body measurements so that brands could build better clothing for all types of body and solve fit and return problems. It will not only allow stores to sell more apparel, it will allow people get the quality apparel.”

3D scanners have gotten better and better over the years and it’s interesting to see companies being able to scan bodies just from a few photos. While these things can’t account for opinions of taste they can definitely make sure that your clothes fit before you order them.

The direct-to-consumer space has some stand-out players, both in newcomers like Brooklinen and old-timers like Warby Parker. But one company, Interior Define, has maintained a low profile over the four years of its existence.

The company offers fully customizable furniture, including couches, dining sets and bed frames, to customers through an online showroom. But ID also has guide shops in Chicago (its home market), LA, New York, and Austin.

Interior Define has also just opened up its biggest retail location yet, right in the middle of Hayes Valley in San Francisco. And this time, the store has a twist.

In the back of the showroom, Interior Define has built out a fully furnished two-story home called Studio ID. Alongside its own pieces, Studio ID includes pieces and products from other digitally native partners including Wright Bedding, Gantri, Snowe Home, Barn & Willow, 57st Design, Revival Rugs, Minted, Fireclay Tile, and Sonos.

The idea here is to show off ID’s pieces in their most natural setting, alongside offering partner companies better exposure via offline retail.

According to Interior Define cofounder and CEO Rob Royer, there is no exchange of cash for these partnerships.

Royer also told TechCrunch that San Francisco has been a priority market for the company for a while, but that the startup insisted on finding a great place within Hayes Valley, and waited until they found this newest location to move into the market.

When Interior Define first launched, the company simply sold customizable sofas. Users could choose the upholstery, the measurements, and the accents like sofa legs. The company has since expanded into dining sets and bed frames, but has also enhanced the overall experience with an Interior Define app.

The app lets users scan the floor of their home and place the item they’re customizing into the home via augmented reality. Interior Define also took a page out of the Warby Parker playbook, offering a free swatch program for users interested in purchasing online.

Interior Define has raised a total of $27.2 million from investors such as Fifth Wall, Pritzker Group, Breakout Capital, and Great Oaks.

Sramana Mitra: We’ve done stories on other companies from Oregon that have that dynamic of very capital-efficient execution. We did a story on ShareID, which you probably know. I think they’re...

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Fabric, a personal journaling app that emerged from Y Combinator’s 2016 batch of startups, is relaunching itself as a Facebook alternative. The app is giving itself a makeover in the wake of Facebook’s closure of the Moves location tracker, by offering its own tool to record your activities, photos, memories and other moments shared with friends and family. But unlike on Facebook, everything in Fabric is private by default and data isn’t shared with marketers.

Instead, the startup hopes to build something users will eventually pay for, via premium features or subscriptions.

The idea for the startup came from two people who helped create Facebook’s core features.

Co-founders Arun Vijayvergiya and Nikolay Valtchanov worked for several years at the social network, where Vijayvergiya built the product that would later become Facebook Timeline at an internal hackathon. He also worked on products like Friendship Pages, Year in Review and On This Day, while Valtchanov developed integrations between Facebook and fitness applications.

After leaving Facebook, both were inspired to work on Fabric because of their interest in personal journaling – and that became the key focus for the original version of the Fabric app. But while other journaling apps may offer a blank space for recording thoughts, Fabric automates the process by pulling in photos, posts from elsewhere on social media, places you visited, and more, and put those on its map interface.

The longer-term goal is that Fabric users will be able to look back across their personal history to answer any kind of question about where they had been, what they did, and who they were with – but in a more private environment than what’s available on Facebook.

Facebook could have built something similar, but its focus has been more on how personal profile data could be useful to advertisers.

Despite numerous check-ins, posts where you tagged friends, shared photos and more, there’s still not an easy way to ask Facebook about that great Indian restaurant you tried last March, or who was on that group beach trip with you a few years ago, for example. At best, Facebook offers memory flashbacks through its On This Day feature (now available at any time via the Memories tab), or round-ups and collages that appear at various times throughout the year.

As a search engine for your own memories, it’s not that great.

What’s New 

This is where Fabric comes in. It will automatically record your activities, checking you in to places you visit, to which you can then choose to add friends.

While the idea of automatic location gathering may turn off a good number of users, the difference is that Fabric’s data collection is meant for your eyes only, unless you explicitly choose to share something with friends.

Fabric doesn’t use third-party software for its location system – it’s written in-house, so the data is never touched by a third-party. It also uses industry standard encryption for data transfer and storage, and login information is stored in a separate system from the rest of your data as an added precaution.

Notably, Fabric doesn’t plan to generate revenue by selling data or offering it to advertisers for targeting purposes. Instead, the company hopes users will eventually pay for its product – perhaps as a subscription or through premium upgrades. (It’s not doing this yet, however.)

“The whole motivation behind Fabric is that many meaningful parts of your life do not belong in the public sphere,” explains Vijayvergiya. “In order to be able to capture these moments, user trust is essential and is something we have baked into our company culture. Internally, we refer to ourselves as a ‘private-first’ company. Everything on Fabric is private by default. You have to choose to include friends in your moments. We don’t share any data with marketers, and we don’t intend to share personally identifiable information with advertisers,” he says.

Since its 2016 release, Fabric has been downloaded 70,000 times by users across 117 countries, and has seen 112 million automatic check-ins.

The new version of the app has been redesigned to be something users engage with more often, as opposed to the more passive journaling app it was before.

The app now offers an outline of your activities, which it also calls Timeline. Here, you can add people, photos and memorable anecdotes to those automated entries. You can jump back to any day to see your history with any person or place that appears on the Timeline.

You can also turn any moment into one you collaborate on with friends, by allowing others to add photos and comments. That is, instead of broad post to a group of so-called “friends” on Facebook, you share the moment with those who really matter. This isn’t all that different from how people use private messaging apps and group chats today – in order to share things with people that aren’t necessarily meant for everyone to see.

In addition, Fabric allows you to add your friends to the app, so you can be automatically tagged when you both spend time together in the real world. This also simplifies sharing because you won’t have to think about which posts should be shared with which audience.

For instance, Vijayvergiya says, “this means you can add your mom as a friend, and only share with her the moments you spend together in the same place.”

The most compelling feature in the updated app may not be check-ins or sharing, but search.

In Fabric, you can now search for past events in your life similar to how you search the web. That is, you could type in “restaurant rome 2017” or “camila los angeles birthday” and find the matching posts, Vijayvergiya suggests. And because you can import your Facebook, Instagram, and Camera Roll to Fabric, it’s now offering the search engine that Facebook itself forgot to build. (You can import your Facebook Moves history, too, ahead of its shutdown.)

Fabric’s search will also be available on the desktop web, where it’s currently in beta.

Fabric’s real challenger, as it turns out, may not be Facebook, though. It’s Google Photos.

Because of advances in image recognition technology, Google Photos (and some other photo apps) have built advanced search capabilities that let you pull up not places, things, people, and more, using data recognized in the image itself. Users can also share those photos with others, collaborate on albums, and leave notes as comments.

The difference is that Fabric offers import from a variety of sources and encourages journaling. But that may not be enough to attract a large user base, especially when automatic check-ins rely on the app’s use of background location which has some impact on battery life.

Fabric is a free download on iOS.

Serverless, Inc came to the serverless game early, creating an open source framework for developers back in 2015. Today, they want to build on that earlier product to give developers more control over deployment and delivery of serverless applications. To that end, they announced a $10 million Series A round led by Lightspeed Ventures. They have now raised a total of $13 million, according to the company.

The company also announced the release of the Serverless Platform, which include the Serverless Framework, Serverless Dashboard and Serverless Gateway. The Framework lets developers set up their serverless code across different cloud platforms and set conditions on the deployment such as function rules and infrastructure dependencies. The dashboard gives visibility and information about the deployment, so that you can track and trace serverless functions over time, regardless of the cloud platform you’re using.

The gateway provides a method to pull in legacy tools into a serverless approach. As the company describes it, “The Serverless Gateway allows businesses to easily integrate serverless into their existing mesh of services, including containers, SaaS or other legacy systems. The Event Gateway, along with serverless compute, gives organizations a powerful way to react to all of their business events with code.”

Company founder and CEO Austen Collins says that as companies shift to a serverless-first mindset, we’re going to see a lower cost to build and deploy applications, but that is going to take some tooling to really work across a team or large organization, tooling his company wants to provide.

“I think now we are seeing widespread demand for tools to operationalize serverless development, tools to make developers across an entire team, or even across entire organization all practice serverless development in a safe and standard way,” Collins explained.

The framework and communications gateway are open source and always will be, Collins, explained. They will make money by charging companies to use the dashboard to get insights into their serverless code or to access a hosted version of the gateway. People can host their own version of the gateway through using the open source version of the product.

With serverless, developers no longer have to worry about the infrastructure required to run their applications. Instead, they create functions that trigger events and the cloud vendor takes care of deploying the necessary compute, memory and storage to run that event.

It offers a number of advantages including eliminating the need to worry about deploying the appropriate infrastructure and only paying for the infrastructure you use each time your function triggers a given event. This is in stark contrast to the traditional approach to development where you deploy a server for your application and pay for it 24/7 whether it happens to be in use or not.

While this approach undoubtedly has the potential to remove some of the complexity associated with developing and deploying applications, it doesn’t remove all of the requirements developers have to deploy and manage their code according to a set of defined policies. The kind of tool set Serverless Inc is offering provides some additional control and insight developers could be lacking with such a new approach.

The company launched in 2015 and currently has 22 employees in a distributed office approach. Their main office is in San Francisco. Customers include EA Sports, Nordstrom, Reuters and Coca-Cola. The new money should allow them to expand and build out the platform further.

In an age where people stream music instead of buying it, how do you build something equivalent to a pre-order campaign for upcoming releases? The answer is to create a “pre-save” campaign, akin to a landing page where fans can authorise you to automatically add a new song, EP or album to their steaming library or playlist of their choice as soon as it becomes available.

However, pre-save tools for Spotify — if you even knew they existed — are often perceived as expensive and solely for use at major labels or established music marketing companies. Now music marketing and technology startup Feature.fm wants to change that with its “Ultimate Pre-Save,’ a free tool for artists or labels of any size.

Better yet, the Ultimate Pre-Save tool also supports Apple’s newly launched “Pre-Add” feature, which works in a similar way to a Spotify pre-save. Deezer’s version of pre-save is supported too.

The set up process is simple. You register with Feature.fm as either an individual artist or label, select the Ultimate Pre-Save tool and click on create new pre-save. Next you are required to give the work a launch date and tell it which of the three services you plan to launch on. You then need to add a title, an image, preview link, and make any changes to the standard text. Later on, once you know the final URL for your new release on each respective service, you add that too.

And that’s pretty much it. Your fully functioning pre-save page is built, ready for you to start sharing/promoting and hopefully have a successful Day One launch.

Meanwhile, any fan who lands on your pre-save page can click “Pre-Save” or “Pre-Add” to get your music into their libraries on release day. They’ll also automatically follow your artist page if they don’t already. You also have the option to re-direct them to a different URL afterwards so you can reward fans with things like exclusive content or contests.

One other useful feature is that the Feature.fm pre-save link automatically converts to a “smart link” once the song/album is released. So up until release the message will be “pre-save on Spotify, Apple Music or Deezer” etc. and then after release day the link automatically switches to a “buy or stream on your preferred service” and pulls in other digital music services too e.g. Amazon and Tidal etc. The idea is that you only need one smart link for the entire life of a campaign.

Other than that, you can capture/collect up to 50 fan emails for free, and get access to click and pre-save counts. There is also the option to pay for some advanced features, such as custom domains, either monthly or as a one-off campaign. And of course Feature.fm wants to up-sell you to a host of other marketing tech features, such as its incredibly easy to use music ad tools, deeper analytics, and the ability to send remarketing data to your Facebook Ads, Google AdWords, and other ad programs.

Amazon (NASDAQ: AMZN) reported a mixed second quarter last week. While it missed estimates of revenue, earnings estimates blew past estimates. This was the third straight quarter of profit above $1...

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Twitter is partnering with two groups of academic researchers to figure out how to measure the health of conversations happening on the platform.

It’s all part of the company’s continuing long game for social relevance. Despite the fact that it lost 1 million users, the company also posted $100 million in profit during last week’s earnings. But neither of these numbers seem to change the fact that Twitter needs to make some adjustments to the way people use the social network.

In March, Twitter called for proposals from researchers to see how they might approach the issue of analytics around the types and manner of conversations on Twitter. These proposals were thoroughly reviewed by Twitter employees from a variety of departments at the company, including Engineering, Product, Machine Learning, Data Science, Trust and Safety, Legal and Research. Twitter also says that the review committee was organized to include representatives from diverse groups across the company. (Reminder: less than 10 percent of Twitter employees are diverse, so it was likely a busy few months for those people.)

Well, the review process is now over and Twitter has decided on two research teams that will focus on two different issues.

The first team, led by scholars from Leiden University, will look at how echo chambers form and their effect, as well as the difference between incivility and intolerance within Twitter conversations. The team — including Dr. Rebekah Tromble, Assistant Professor of Political Science at Leiden University, Dr. Michael Meffert at Leiden, Dr. Patricia Rossini and Dr. Jennifer Stromer-Galley at Syracuse University, Dr. Nava Tintarev at Delft University of Technology, and Dr. Dirk Hovy at Bocconi University — has found in past research that echo chambers can cause hostility and promote resentment towards those not having the same conversation.

The first set of metrics this team is focusing on will look at the extent to which people acknowledge and engage with diverse viewpoints on Twitter. The second set of metrics will look at the difference between incivility and intolerance. Past research by this group shows that incivility can serve important functions in political dialogue, though not without spurring its own problems. On the other hand, intolerant speech (hate speech, racism, xenophobia) threatens our democracy. The team plans to develop algorithms that will distinguish between more useful incivility and the very useless intolerance we encounter daily on Twitter.

Professor Miles Hewstone and John Gallacher at The University of Oxford, in partnership with Marc Heerdink at the University of Amsterdam, will lead the second research project. The work will be an extension of Hewstone’s long-standing work to study intergroup conflict. The current findings from this study show that when conversation contains more positive sentiments, cooperative emotions, and more complex thinking and reasoning from multiple perspectives, prejudice will go down and the quality of the relationships will go up.

“As part of the project, text classifiers for language commonly associated with positive sentiment, cooperative emotionality, and integrative complexity will be adapted to the structure of communication on Twitter,” the Twitter blog says.

Just like any social network, Twitter provides scaffolding. Users, on the other hand, construct buildings made of dialogue. How exactly Twitter will be able to adjust the scaffolding to produce more useful, empathetic conversations is still a mystery. But bringing in the academic community to help is an excellent next step.

Shuttl, a service that lets Indian city dwellers find seats on multiple bus routes through one app, announced today that it has raised a $11 million Series B led by Amazon India, Amazon Alexa Fund and Dentsu Ventures. Returning investors Sequoia Capital, Times Internet and Lightspeed Ventures also participated.

The Gurgaon-based startup’s last round of funding was a $20 million Series A announced in December 2015, just eight months after it launched.

The Amazon Alexa Fund was created in 2016 to fund new voice technology. One of Shuttl’s most interesting features is “Chirp,” which verifies passengers by sending a sound from their mobile phones to the driver’s version of its app. The idea is that “chirping” is quicker than using tickets or passes and can therefore decrease delays on bus routes. The feature is powered by startup Chirp.io, which recently released a free version of its SDK.

Shuttl, which is owned by Super Highway Labs, was created with the goal of reducing pollution and traffic in major cities like Delhi by encouraging people to take public transportation. In order to compete with Uber and Ola, its tech platform optimizes routes and capacity, while its app enables users to track the location of their bus, giving them similar convenience and reliability to on-demand ride services (as long as they remember to book their seat a day in advance).

Shuttl’s platform now includes 800 buses and it claims to have 60,000 monthly active users and provide 45,000 rides per day in five cities. Its new funding will be used to expand into two new cities.

When people have to live paycheck to paycheck, life can easily get unbearable. Earnin offers loans against paychecks as collateral to alleviate this incessant pressure to low income families at...

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Facebook's founder and CEO Mark Zuckerberg speaks at the Viva Tech start-up and technology summit in Paris, France, May 24, 2018. REUTERS/Charles Platiau

John Oliver. Getty Images/Bryan Bedder