1010Computers | Computer Repair & IT Support

Halo Infinite now scheduled for release in ‘Fall 2021’

We already knew that Halo Infinite was delayed until next year. Initially intended to launch alongside the new Xboxes, Microsoft announced back in August that it would instead ship in 2021.

Exactly when in 2021, though, was still anyone’s guess. A new blog post from 343 Industries narrows it down a bit: it’ll be released in Fall.

Assuming they mean Fall in the Northern Hemisphere (which, well, they probably do,) this narrows the launch window to sometime between the end of September and the end of December. So it’ll be a while… but a late game is better than a bad game, right?

343 has a blog post and interview outlining the team’s thinking on the timing (and a bit about what they’re still working on) but it really all boils down to one point: they “needed more time to do things right.”

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FTC sues to block P&G’s acquisition of Billie, a razor startup for women

The Federal Trade Commission has sued to block Procter & Gamble’s acquisition of Billie, a NY-based startup that sells razors and body wash.

In the notice, the FTC alleged that the merger would “eliminate innovative nascent competitors for wet shave razors” to the loss of consumers.

Billie was founded in 2017 with the goal of fighting the “pink tax” on goods marketed to women, including razors and body wash. It went up against companies like P&G and Edgewell Personal Care by offering high-quality and cheap razors. The company announced its intent to be acquired by P&G after raising just $35 million in venture capital in June.

“As its sales grew, Billie was likely to expand into brick-and-mortar stores, posing a serious threat to P&G. If P&G can snuff out Billie’s rapid competitive growth, consumers will likely face higher prices,” Ian Conner, director of the FTC’s Bureau of Competition said in a statement.

P&G has been on a buying spree as of late. Along with the Billie news, Procter & Gamble acquired Walker & Company, which created Bevel, a grooming line for men of color, and Form, a hair-care line for women of color. In February 2019, P&G announced plans to acquire This is L, a feminine-care brand that sells tampons, pads and wipes.

If the FTC wins, this is another blow for direct-to-consumer brands on the base of competition dynamics. In May 2019, Edgewell Personal Care announced it intended to buy Harry’s, another direct-to-consumer shaving brand. In February 2020, the FTC filed a lawsuit to block the deal from happening, similarly citing how the deal would limit competition and innovation in the razor market.

Unlike Harry’s, Billie was bought before it broke into brick-and-mortar retail stores. If the deal doesn’t close, Billie lost precious time it could have used to expand into new locations and markets — and P&G will lose some of its competitive advantage in the women’s shaving world.

Harry’s and Billie’s blocks could negatively trickle down to hurt direct-to-consumer products looking at health and wellness more broadly.

Note that exit market isn’t as dull for all companies in the consumer packaged goods (CPG) world. We’ve seen deals close like Blue Bunny’s buy of Halo Top, Mars’ acquisition of Kind Bars and, of course, Unilever’s $1 billion acquisition of Dollar Shave Club.

Andrea Hernández, a founder and consultant on food and beverage CPG, says that DTC companies often need to partner with mega-businesses to get the distribution scale they need, focusing more on omni-channel presence versus a single seller point.

“It’s very limited for these companies to scale at the same level and grow without incurring debt or needing constant injections of [money],” she said. “Or [you can go] the preferred route which is having BigDaddyCorp come whisk you away. You get a success story and the resources to continue your journey.”

That said, the coronavirus has even impacted food CPG companies by forcing them to slash SKUs (or stock keeping units) and prioritize essential goods. Whereas before, CPG companies might stock a variety of goods for a variety of customer needs, they’re now prioritizing a smaller slice of the pie to manage uncertainty among consumer behavior. Long-term, this means that CPGs might be buying fewer of the Billies and Harry’s of the world and just focusing on what’s working now.

Regardless of how this plays out, today’s news shows that the FTC is paying more attention than ever to consumer and tech.

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DoorDash said to price at $102 per share, doubling its final private price

According to media reports, food-delivery giant DoorDash priced its IPO at $102 per share, ahead of its final IPO pricing range of $90 to $95 per share.

The company’s debut has been warmly anticipated by public investors, as evinced by the company raising its range from an initial target of $75 to $85.

While we’re still waiting for official pricing, the price point makes DoorDash worth $32 billion at the time of its IPO price on a non-diluted basis (we’re using the company’s final S-1/A share count of 317,656,521). That valuation rises if one includes options that have vested but not been exercised, and even more if shares set aside for future compensation are also tallied. CNBC calculates DoorDash’s valuation to be $38.7 billion on a diluted basis.

Regardless, any of the valuation marks for DoorDash at $102 per share are far and away greater than its final pre-IPO valuation of around $16 billion, set this summer when the company took on additional capital. The unicorn raised more money during a growth boom, allowing it to add to its cash reserves ahead of its IPO with limited dilution.

DoorDash, which doubled its private startup valuation, is now incredibly well-capitalized to take on rivals Uber Eats and others. And at a price far above its raised range, it has more cash than it probably hoped for. How it uses that cash to preserve pandemic-driven gains will be a key narrative from the company in 2021.

More when we get official numbers.

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Uber sells air taxi business Elevate to Joby Aviation, shedding its last moonshot

Uber has offloaded its air taxi enterprise Elevate to Joby Aviation, the last of several moonshots to be sold by the ride-hailing company in a pursuit to stick to its core business and reach profitability.

The transaction announced Tuesday is part of a complex deal that includes Uber investing $75 million into Joby and an expanded partnership between the two companies. Last year, Uber and Joby, which is developing an all-electric, vertical take-off and landing passenger aircraft, signed on as a vehicle partner for Uber’s Elevate initiative. Joby was the first partner to commit to deploying air taxi services by 2023.

The $75 million investment comes in addition to a previously undisclosed $50 million investment made as part of Joby’s Series C financing round in January 2020, Uber said. To date, Joby Aviation has raised $820 million. Uber has invested a total of $125 million into the startup.

Under the deal, which is expected to close in early 2021, the two parent companies have agreed to integrate their respective services into each other’s apps.

“Advanced air mobility has the potential to be exponentially positive for the environment and future generations,” Uber CEO Dara Khosrowshahi said in a statement. “This deal allows us to deepen our partnership with Joby, the clear leader in this field, to accelerate the path to market for these technologies.”

While Joby is considered one of the leaders, Elevate did play a role in shaping the nascent industry, including establishing some of the benchmarks used by competitors.

“The team at Uber Elevate has not only played an important role in our industry, they have also developed a remarkable set of software tools that build on more than a decade of experience enabling on-demand mobility,” Joby Aviation CEO JoeBen Bevirt said in a statement.” These tools and new team members will be invaluable to us as we accelerate our plans for commercial launch.”

One year ago, Uber’s business model could be categorized as an “all of the above approach,” a strategy to generate revenue from all forms of transportation, including ride-hailing, micromobility, logistics and package and food delivery. The COVID-19 pandemic and Khosrowshahi’s focus on profitability prompted the company to dump its moonshots and double down on delivery with its acquisition of Postmates.

Today, Uber is a company focused on ride-hailing and delivery while keeping its hand in micromobility, logistics and autonomous vehicles through a series of deals struck in 2020.

The Joby-Elevate terms are similar to two other Uber deals this year. In the spring, Uber led a $170 million funding round in micromobility startup Lime. As part of the deal, Lime acquired Uber’s micromobility subsidiary Jump. The majority of Jump’s 400 employees were laid off. Earlier this week, autonomous vehicle startup Aurora Innovation reached an agreement with Uber to buy the ride-hailing firm’s self-driving unit in a complex deal that will value the combined company at $10 billion.

Just like Uber’s deals with Lime and now Joby, Aurora isn’t paying cash for Uber ATG, a company that was last valued at $7.25 billion. Instead, Uber is handing over its equity in ATG and investing $400 million into Aurora, which will give it a 26% stake in the combined company, according to a filing with the U.S. Securities and Exchange Commission.

Uber said in October that it sold off a $500 million stake in its Uber Freight business to an investor group led by New York-based investment firm Greenbriar Equity Group. The deal valued the unit at $3.3 billion on a post-money basis. Uber has maintained its majority stake in Uber Freight, unlike the Jump, Elevate and ATG deals.

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AWS expands on SageMaker capabilities with end-to-end features for machine learning

Nearly three years after it was first launched, Amazon Web Services’ SageMaker platform has gotten a significant upgrade in the form of new features, making it easier for developers to automate and scale each step of the process to build new automation and machine learning capabilities, the company said.

As machine learning moves into the mainstream, business units across organizations will find applications for automation, and AWS is trying to make the development of those bespoke applications easier for its customers.

“One of the best parts of having such a widely adopted service like SageMaker is that we get lots of customer suggestions which fuel our next set of deliverables,” said AWS vice president of machine learning, Swami Sivasubramanian. “Today, we are announcing a set of tools for Amazon SageMaker that makes it much easier for developers to build end-to-end machine learning pipelines to prepare, build, train, explain, inspect, monitor, debug and run custom machine learning models with greater visibility, explainability and automation at scale.”

Already companies like 3M, ADP, AstraZeneca, Avis, Bayer, Capital One, Cerner, Domino’s Pizza, Fidelity Investments, Lenovo, Lyft, T-Mobile and Thomson Reuters are using SageMaker tools in their own operations, according to AWS.

The company’s new products include Amazon SageMaker Data Wrangler, which the company said was providing a way to normalize data from disparate sources so the data is consistently easy to use. Data Wrangler can also ease the process of grouping disparate data sources into features to highlight certain types of data. The Data Wrangler tool contains more than 300 built-in data transformers that can help customers normalize, transform and combine features without having to write any code.

Amazon also unveiled the Feature Store, which allows customers to create repositories that make it easier to store, update, retrieve and share machine learning features for training and inference.

Another new tool that Amazon Web Services touted was Pipelines, its workflow management and automation toolkit. The Pipelines tech is designed to provide orchestration and automation features not dissimilar from traditional programming. Using pipelines, developers can define each step of an end-to-end machine learning workflow, the company said in a statement. Developers can use the tools to re-run an end-to-end workflow from SageMaker Studio using the same settings to get the same model every time, or they can re-run the workflow with new data to update their models.

To address the longstanding issues with data bias in artificial intelligence and machine learning models, Amazon launched SageMaker Clarify. First announced today, this tool allegedly provides bias detection across the machine learning workflow, so developers can build with an eye toward better transparency on how models were set up. There are open-source tools that can do these tests, Amazon acknowledged, but the tools are manual and require a lot of lifting from developers, according to the company.

Other products designed to simplify the machine learning application development process include SageMaker Debugger, which enables developers to train models faster by monitoring system resource utilization and alerting developers to potential bottlenecks; Distributed Training, which makes it possible to train large, complex, deep learning models faster than current approaches by automatically splitting data across multiple GPUs to accelerate training times; and SageMaker Edge Manager, a machine learning model management tool for edge devices, which allows developers to optimize, secure, monitor and manage models deployed on fleets of edge devices.

Last but not least, Amazon unveiled SageMaker JumpStart, which provides developers with a searchable interface to find algorithms and sample notebooks so they can get started on their machine learning journey. The company said it would give developers new to machine learning the option to select several pre-built machine learning solutions and deploy them into SageMaker environments.

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Cyberpunk 2077 draws criticism for seizure-inducing sequence with no warning or mitigation

One of the biggest games of the year, “Cyberpunk 2077,” is about to be released, but developer CD Projekt Red is already under fire for an early game sequence with the potential to induce seizures. Players with epilepsy should be warned that there is currently no way to skip this, and the visual feature will be repeated throughout the game.

Strobing lights can induce seizures in some people prone to them, but that hasn’t stopped many high-profile games from including them for effect. Usually there is a boilerplate warning on boot saying this is a possibility, but in most games it’s more of a warning that there may potentially be flashing lights of this type, for example if several flashbang grenades went off one after the other. Many games also offer an option to reduce the intensity of flashing lights or otherwise change their appearance, along with other options for accessibility.

“Cyberpunk” seems to tread especially dangerous territory fundamentally, as its game world is full of the kind of seedy, flickering-neon lighting one associates with a grimy, futuristic dystopia. But within the first few hours of the game there is a much more severe and thoughtlessly designed event that has already caused a reviewer at Game Informer to experience a seizure. It involves the (otherwise quite interesting) “braindances,” or BDs, which let your character relive experiences recorded by others, by donning a special headset… that boots up with intense flashing lights:

When “suiting up” for a BD, especially with Judy, V will be given a headset that is meant to onset the instance. The headset fits over both eyes and features a rapid onslaught of white and red blinking LEDs, much like the actual device neurologists use in real life to trigger a seizure when they need to trigger one for diagnosis purposes. If not modeled off of the IRL design, it’s a very spot-on coincidence, and because of that this is one aspect that I would personally advise you to avoid altogether. When you notice the headset come into play, look away completely or close your eyes. This is a pattern of lights designed to trigger an epileptic episode and it very much did that in my own personal playthrough.

You can see the event referred to in the screenshot above (taken afterwards, but you can see the device). I recall this moment quite clearly from my own playthrough, and remember thinking it was rather an intense lightshow indeed. Unfortunately for this person, it caused a serious episode and could do so for many others upon its release on the 10th.

Among the many options for changing the appearance of “Cyberpunk 2077,” there isn’t one for reducing flashing lights that I could find. I’ve asked CD Projekt Red about this and hopefully they can ship something to mitigate the issue at or near launch. The company did say on Twitter that it was looking into a solution.

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Sunshine Contacts may have given out your home address, even if you’re not using the app

A third-party contacts app you’re not using may be handing out your home address to its users. In November, former Yahoo CEO and Google veteran Marissa Mayer and co-founder Enrique Muñoz Torres introduced their newly rebranded startup Sunshine, and its first product, Sunshine Contacts. The new iOS app offers to organize your address book by handling duplicates and merges using AI technology, as well as fill in some of the missing bits of information by gathering data from the web — like LinkedIn profiles, for example.

But some users were surprised to find they suddenly had home addresses for their contacts, too, including for those who were not already Sunshine users.

TechCrunch reached out to Sunshine to better understand the situation, given the potential privacy concerns.

We understand there are several ways that users may encounter someone’s home address in the Sunshine app. A user may already have the address on file in their phone’s address book, of course, or they may have opted in to allow Sunshine to scan their inbox in order to extract information from email signature lines. This is a feature common to other personal CRM solutions, too, like Evercontact.

In the event that someone had signed an email with their home address included in this field, that data could then be added to their contact card in the Sunshine app. In this case, the contact card is updated in the Sunshine Contacts app, which then syncs with your phone’s address book. But this data is not distributed to any other app users.

Image Credits: Sunshine

The app also augments contact cards with information acquired by other means. For example, it may use the information you do have to complete missing fields — like adding a last name, when you had other data that indicated what someone’s full name is, but hadn’t completed filling out the card. The app may also be able to pull in data from a LinkedIn profile, if available.

For home addresses, Sunshine is using the Whitepages API.

The company confirmed to TechCrunch it’s augmenting contact cards with home addresses under some circumstances, even if that contact is not a Sunshine Contacts user. Sunshine says it doesn’t believe this to be any different from a user going to Google to look for someone’s contact information on the web — it’s just automating the process.

Of course, some would argue when you’re talking about automating the collection of home addresses for hundreds or potentially thousands of users — depending on the size of your personal address book database — it’s a bit different than if you went googling to find your aunt’s address so you can mail a Christmas card or called your old college roommate to find out where to send their birthday gift.

However, Sunshine clarified to TechCrunch that it won’t add the home address except in cases when it determines you have a personal connection to the contact in question.

Here, though, Sunshine enters a gray area where the app and its technology will try to figure out who you know well enough to need a home address.

Before adding the address, Sunshine requires you to have the contact’s phone number on file in your address book, not just their email. That would eliminate some people you only have a loose connection with through work, for instance. And it only updates with the home address if the partner API is able to associate that address with a phone number you have.

Image Credits: Sunshine

In addition, Sunshine says that it’s generally able to understand the type of phone number you have on file — like if it’s a residential or business line, or if it’s a landline or mobile number. (It uses APIs to do this, similar to StrikeIron’s though not that particular one.) It also knows who the phone number belongs to. Using this information and further context, the app tries to determine if a phone number is a personal or a professional number and it will try to understand your relationship with the person who owns that number.

In practice, what this means is that if all the information you had on file for a contact was professional information — where they worked, a job title, a work email and a phone number, perhaps — then that person’s contact card would not be updated to include their home address, too.

And because many people use their personal cell for work, Sunshine won’t consider someone a “personal” relationship just because you have their mobile phone number. For example, if you had only a contact’s name and a cell number, you wouldn’t be able to use the app to get their home address.

The result of all this automated analysis is that Sunshine, in theory, only updates contact cards with home addresses where it’s determined there’s a personal relationship.

This, of course, doesn’t take into account some scenarios like bad exes, stalking or a general desire for privacy. Arguably, there are times when someone may have a lot of personal information for a contact in their address book, but the contact in question would rather not have their home address distributed to that person.

The only way to prevent this, presumably, would be to opt out at the source: Whitepages.com. (Once you have your profile URL from the Whitepages website, you can use this online form to have your information suppressed.)

Image Credits: Sunshine

The way the app functions raises questions about what is truly private information these days.

Sunshine points out that people’s home addresses are not as hidden from the world as they may think, which makes them fair game.

It’s true that our home addresses are often publicly available. Although it’s been years since most of us have had a telephone directory dropped on our doorstep with phone and address listings for people in our city, home addresses today are relatively trivial to find when you know where to look online.

In addition to public records — like voter registration databases — there are web-based people finders, too.

Sunshine’s partner, Whitepages.com, makes visitors pay for its data, but others like TruePeopleSearch.com don’t have the same paywall. With someone’s first and last name and city, its website provides access to someone’s home address, prior addresses, cell phone, age and the names of family members and other close associates. (TruePeopleSearch is not a Sunshine partner, we should clarify.)

Even though this data is “public,” it’s uncomfortable to see it casually distributed in an app, as that makes it even easier to get to than before.

Plus, after years of being burned by data breaches and data privacy scandals, people tend to be more protective of their personal information than before. And, had they been asked, many would probably decline to have their home addresses shared with Sunshine’s user base. Generally speaking, people appreciate the courtesy of having someone come ask for a home address, when it’s needed — they may not want an app creeping the web to find it and hand it out.

Sunshine Contacts is in an invite-only beta in the U.S., so the company has time to reconsider how this feature is implemented based on user feedback before it becomes widely available.

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Former Salesforce chief scientist announces new search engine to take on Google

Richard Socher, former chief scientist at Salesforce, who helped build the Einstein artificial intelligence platform, is taking on a new challenge — and it’s a doozy. Socher wants to fix consumer search and today he announced you.com, a new search engine to take on the mighty Google.

“We are building you.com. You can already go to it today. And it’s a trusted search engine. We want to work on having more click trust and less clickbait on the internet,” he said. He added that in addition to trust, he wants it to be built on kindness and facts, three worthy but difficult goals to achieve.

He said that there were several major issues that led him and his co-founders to build a new search tool. For starters, he says that there is too much information and nobody can possibly process it all. What’s more, as you find this information, it’s impossible to know what you can trust as accurate, and he believes that issue is having a major impact on society at large. Finally, as we navigate the internet in 2020, the privacy question looms large as is how you balance the convenience-privacy trade-off.

He believes his background in AI can help in a consumer-focused search tool. For starters the search engine, while general in nature, will concentrate on complex consumer purchases where you have to open several tabs to compare information.

“The biggest impact thing we can do in our lives right now is to build a trusted search engine with AI and natural language processing superpowers to help everyone with the various complex decisions of their lives, starting with complex product purchases, but also being general from the get-go as well,” he said.

While Socher was light on details, preferring to wait until GA in a couple of months to share some more, he said he wants to differentiate from Google by not relying on advertising and what you know about the user. He said he learned from working with Marc Benioff at Salesforce that you can make money and still build trust with the people buying your product.

He certainly recognizes that it’s tough to take on an entrenched incumbent, but he and his team believe that by building something they believe is fundamentally different, they can undermine the incumbent with a classic “Innovator’s Dilemma” kind of play where they’re doing something that is hard for Google to reproduce without undermining their primary revenue model.

He also sees Google running into antitrust issues moving forward and that could help create an opening for a startup like this. “I think a lot of stuff that Google [has been doing] … with the looming antitrust will be somewhat harder for them to get away with on a continued basis,” he said.

He acknowledges that trust and accuracy elements could get tricky as social networks have found out. Socher hinted at some social sharing elements they plan to build into the search tool including allowing you to have your own custom you.com URL with your name to facilitate that sharing.

Socher said he has funding and a team together working actively on the product, but wouldn’t share how much or how many employees at this point. He did say that Benioff and venture capitalist Jim Breyer are primary backers and he would have more information to share in the coming months.

For now, if you’re interested, you can go to the website and sign up for early access.

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AWS announces SageMaker Clarify to help reduce bias in machine learning models

As companies rely increasingly on machine learning models to run their businesses, it’s imperative to include anti-bias measures to ensure these models are not making false or misleading assumptions. Today at AWS re:Invent, AWS introduced Amazon SageMaker Clarify to help reduce bias in machine learning models.

“We are launching Amazon SageMaker Clarify. And what that does is it allows you to have insight into your data and models throughout your machine learning lifecycle,” Bratin Saha, Amazon VP and general manager of machine learning told TechCrunch.

He says that it is designed to analyze the data for bias before you start data prep, so you can find these kinds of problems before you even start building your model.

“Once I have my training data set, I can [look at things like if I have] an equal number of various classes, like do I have equal numbers of males and females or do I have equal numbers of other kinds of classes, and we have a set of several metrics that you can use for the statistical analysis so you get real insight into easier data set balance,” Saha explained.

After you build your model, you can run SageMaker Clarify again to look for similar factors that might have crept into your model as you built it. “So you start off by doing statistical bias analysis on your data, and then post training you can again do analysis on the model,” he said.

There are multiple types of bias that can enter a model due to the background of the data scientists building the model, the nature of the data and how they data scientists interpret that data through the model they built. While this can be problematic in general it can also lead to racial stereotypes being extended to algorithms. As an example, facial recognition systems have proven quite accurate at identifying white faces, but much less so when it comes to recognizing people of color.

It may be difficult to identify these kinds of biases with software as it often has to do with team makeup and other factors outside the purview of a software analysis tool, but Saha says they are trying to make that software approach as comprehensive as possible.

“If you look at SageMaker Clarify it gives you data bias analysis, it gives you model bias analysis, it gives you model explainability it gives you per inference explainability it gives you a global explainability,” Saha said.

Saha says that Amazon is aware of the bias problem and that is why it created this tool to help, but he recognizes that this tool alone won’t eliminate all of the bias issues that can crop up in machine learning models, and they offer other ways to help too.

“We are also working with our customers in various ways. So we have documentation, best practices, and we point our customers to how to be able to architect their systems and work with the system so they get the desired results,” he said.

SageMaker Clarify is available starting to day in multiple regions.

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Calm raises $75M more at $2B valuation

Calm, a well-known meditation app, has raised new capital at a valuation of $2 billion. The round was anticipated after the company was reported to be hunting for up to $150 million at a valuation of $2.2 billion; perhaps Calm will follow in the steps of Robinhood and add a second tranche to the round in time.

Prior investor Lightspeed Venture Partners led the investment, which also saw participation from Insight, TPG and Salesforce CEO and new Slack owner Marc Benioff, among others.

That Calm was able to secure more capital is not surprising. The company has a history of quick revenue growth, and is reportedly profitable, to boot. And the investment comes after mental health-focused startups as a category have performed well from a venture capital perspective.

The coronavirus pandemic has likely also played into Calm’s attractiveness as an investment. Since the beginning, researchers have warned about the psychological toll that a pandemic could have on humanity. A recent Pew Research study suggested that people who have lost their jobs during the pandemic might be feeling higher levels of distress during this time. Rival service Headspace offered an annual subscription to its platform for free for those that are unemployed.

Calm responded to the toll of coronavirus by launching a page of free resources, and focusing on a partnership with nonprofit health system Kaiser Permanente. Kaiser was the first health system to make Calm app’s Premium subscription free for its members.

The startups sells a consumer service for around $70 per year, or $15 per month. And the startup has built out a corporate arm, “Calm for Business,” that likely brings revenue stability that augments its consumer efforts.

As part of a release concerning today’s news, Calm detailed a number of nearly useful growth metrics. The service has over 100 million downloads, up from 40 million downloads in February 2019. It also grew up from 1 million paying users to 4 million paying users in the same time period (we asked if that data was inclusive of any Calm for Business customers, a question Calm did not answer).

Other TechCrunch queries regarding the company’s economics, revenue growth and performance compared to its pre-COVID plan also went unanswered.

Calm and rival service Headspace have now raised a combined $434 million according to Crunchbase data, underscoring how attractive their models have proved to venture capitalists. According to a Bloomberg interview, Calm is considering acquiring smaller companies in the wake of its new capital event.

Regardless, Calm now has a refreshed war chest heading into 2021 and a plan to go hunting. That should generate a headline or two.

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