Microsoft commits to putting more water than it consumes back into the ecosystems where it operates by 2030

One good trend in 2020 has been large technology companies almost falling over one another to make ever-bolder commitments regarding their ecological impact. A cynic might argue that just doing without most of the things they make could have a much greater impact, but Microsoft is the latest to make a commitment that not only focuses on minimizing its impact, but actually on reversing it. The Windows-maker has committed to achieving a net positive water footprint by 2030, by which it means it wants to be contributing more energy back into environment in the places it operates than it is drawing out, as measured across all “basins” that span its footprint.

Microsoft hopes to achieve this goal through two main types of initiatives: First, it’ll be reducing the “intensity” of its water use across its operations, as measured by the amount of water used per megawatt of energy consumed by the company. Second, it will also be looking to actually replenish water in the areas of the world where Microsoft operations are located in “water-stressed” regions, through efforts like investment in area wetland restoration, or the removal and replacement of certain surfaces, including asphalt, which are not water-permeable and therefore prevent water from natural sources like rainfall from being absorbed back into a region’s overall available basin.

Apple says its supply chains and products will be carbon neutral by 2030

The company says that how much water it will return will vary, and depend on how much Microsoft consumes in each region, as well as how much the local basin is under duress in terms of overall consumption. Microsoft isn’t going to rely solely on external sources for this info, however: It plans to put its artificial intelligence technology to work to provide better information around what areas are under stress in terms of water usage, and where optimization projects would have the greatest impact. It’s already working towards these goals with a number of industry groups, including The Freshwater Trust.

Microsoft has made a number of commitments towards improving its global ecological impact, including a commitment from earlier this year to become ‘carbon negative’ by 2030. Meanwhile, Apple said in July that its products, including the supply chains that produce them, will be net carbon neutral by 2030, while Google made a commitment just last week to use only energy from carbon-free sources by that same year.

Google claims net zero carbon footprint over its entire lifetime, aims to only use carbon-free energy by 2030

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Why I fight for climate justice | Xiye Bastida

Why I fight for climate justice | Xiye Bastida

In a deeply moving letter to her grandmother, Xiye Bastida reflects on what led her to become a leading voice for global climate activism -- from mobilizing school climate strikes to speaking at the United Nations Climate Summit alongside Greta Thunberg -- and traces her resolve, resilience and profound love of the earth to the values passed down to her. "Thank you for inviting me to love the world since the moment I was born," she says.

https://ift.tt/3kBj19B

Click this link to view the TED Talk

Illumina buying cancer-screening spinout Grail in blockbuster $8B biotech deal

Biotech has become one of the hottest areas of venture investment in recent years, as progress in machine learning, genetics, medical devices, and biology fuse together into new products for the gargantuan health industry.

Case in point: Grail, which began in 2016 as a spinoff from genetic sequencing giant Illumina and co-founded by longtime Google executive Jeff Huber (who was involved in the creation of the company’s experimental laboratory Google[x]), is now being spun back in to the tune of an $8 billion acquisition announced this morning.

Illumina originally invested $100 million in the spinout, and Grail would go on to raise more than a billion dollars in funding from prominent biotech firm ARCH, one of China’s top VCs Hillhouse Capital, among many others according to Crunchbase.

Grail’s technology was designed to use modern genetic sequencing tools coupled with data science to detect cancer earlier than other competing products on the market.

As we discussed on TechCrunch back in 2017 when the company raised $900 million, “while liquid biopsies to detect cancer aren’t anything new and GRAIL will have to compete with several other contenders both large and small, the technology to take a blood sample and detect the early, free-floating cancer DNA floating in your bloodstream is revolutionary in the industry and only made possible through new DNA sequencing machinery.”

Early cancer detection startup GRAIL closes on $900 million in Series B funding

Cancer screening is a $100 billion market and growing rapidly, particularly internationally as countries like China and India develop economically and more patients require active screening. Detecting cancer early is pivotal for reducing mortality risk, and so Grail’s promise was to offer the “holy grail” (couldn’t help myself) for saving these lives. According to the U.S. government, roughly 600,000 people will die this year from cancer, and it is a leading cause of death.

As part of the deal, Grail will receive $3.5 billion in cash, with another $4.5 billion earmarked for Illumina stock. The company set a deadline of December 20th for consummating the acquisition, at which point Illumina will begin offering Grail $35 million per month in cash payments until the deal closes. The two companies have signed a $315 million merger termination agreement as part of the deal.

The acquisition is subject to customary regulatory review.

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The Lumos Matrix is the ideal urban bike helmet for a smarter, safer day trip

With many of us are still more or less confined to our own homes and limited social spaces for the foreseeable future, and for a lot of you, that has led to a rediscovery of the joys of biking. Bike riding is a great way to spend time outdoors exploring your own town or city, and if you’re just getting into exploring this hobby, or if you’re a long-time bike rider looking for an upgrade, the Lumos Matrix smart helmet is a sensible piece of tech with a solid design that combines a number of connected features into one great package.

The basics

The Matrix is a version of Lumos’ smart helmet updated with modern, urban helmet aesthetics and a new large LED display on the back that can be programmed to show a variety of different patterns, including simple images. It includes a built-in front light in addition to the rear light panel, as well as integrated turn signals that work with an included physical handlebar remote, or in concert with an Apple Watch app. It’s available in either a gloss white finish, or a matte black (as reviewed).

Lumos has designed the Matrix to work with a wide range of head sizes, thanks in part to two sets of included velcro pads for the inside of the helmet, but due mostly to the adjustable, ratcheting sizing harness on the inside. This can be easily dialled to tighten or loosen the helmet, helping it fit heads ranging between 22 and 24-inches in size.

The exterior of the Lumos is made of an ABS plastic that provides full weatherproofing, so that you can wear it in the rain without having to worry about the condition of the embedded electronics. There’s also a MIPS (Multi-directional Impact Protection System) option that you can add on if you want an additional level of safety and security, though that’s not yet shipping and should be “available soon” according to the company.

A button integrated into the helmet’s strap lets you turn it on and off, and cycle between the built-in patters. You can pair the helmet via Bluetooth with your smartphone, too, and use the dedicated app to customize features including brightness, and even creating your own custom patterns for the rear display. In the box, you’ll also find a charging cable with a standard USB A connector on one end, and a proprietary magnetic charging surface on the other for powering up both your helmet and the handlebar remote.

Design and performance

The Lumos Matrix features a mostly continuous surface, with four vents on the top of the helmet for airflow, with an integrated brim built into the shell. As mentioned, there’s a front-facing light built-in to the helmet and protected by a transparent plastic covering, as well as a rear panel of 7×11 led lights, which create a dot matrix-style display that can display images or animations, including scrolling text. These LEDs are all full RGB, allowing the user to take full advantage for their own, or built-in display creations.

Lumos also makes the Kickstart, which features a more aerodynamic, thoroughly vented design. The look of the Matrix is more akin to helmets used in skateboarding, and for urban commuter bicyclists. Despite its more solid-looking design, in testing I found that it was actually very comfortable and cool, allowing plenty of airflow. The helmet sits a bit high on the head, but has ample hard foam padding and definitely feels like a solid piece of protective gear. Overall, the extreme quality of the construction and level of the finishes on the Matrix help it earn its higher price tag.

The Matrix is also comfortable, and the adjustable sizing straps ensure a snug fit that means the helmet won’t be shifting around at all while worn. The activation button located on the chin strap near your ear is easy to find and press, with a tactile response combined with an auditory signal so you’ll know it’s on. There’s also a built-in magnetic holder for the included two-button handlebar turn signal remote in the rear interior of the helmet itself, which is super useful when wearing the helmet out on errands.

In terms of the smart features, Lumos has created a very sensible set of defaults for the on-board lighting that make it easy to just turn on the helmet and get riding. The built-in patterns offer a range of options, but all do the job of increasing your visibility – and the bright lighting means that it adds to your ability to be seen by motorists, other cyclists and pedestrians even while you’re biking in bright daylight.

The customizability of the rear dot matrix display is also super handy. Even if you’re not interested in creating colorful designs to express your artistic self, you can use it for much more practical reasons – like displaying a simple scrolling message (ie. ‘biking with kids’) in order to alert anyone else around to reasons to pay heightened attention.

The included Lumos handlebar remote is paired out of the box, and is extremely reliable in terms of activating the turn signals on the helmet. Lumos’ smartwatch app was much more hit-or-miss for me in terms of recognizing my arm gestures reliably to automate the signalling, but that’s really a value-add feature anyway, and totally not necessary to get the full benefit of the helmet. The app’s integration with Apple Health for workout tracking while biking is also fantastic, and really adds to the overall experience of using the Matrix helmet.

Bottom line

The Lumos Matrix is a fantastic bike helmet, with an amazing integrated smart lighting system that’s both bright and highly customizable. There’s a reason this thing is carried at Apple Stores – it’s top quality in terms of construction, software integration and design. That said, its retail price starts at $249.95 – which is a lot when you consider that a good quality MIPS helmet without smart features will only set you back about $60 or so.

When you consider just how much technology is onboard the Matrix, however, the pricing becomes a lot easier to swallow. It’s true that dedicated lights also aren’t expensive, but the ones on the Matrix are very high quality and extremely visible in all lighting conditions. And the Matrix offers unique features you won’t find anywhere else, including active turn signals and automated brake lights, which really add to your ability to safely share the road with other cyclists and vehicles.

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With $100M in funding, Playco is already a mobile gaming unicorn

Playco is a new mobile gaming startup created by Game Closure co-founder Michael Carter and Zynga co-founder Justin Waldron, as well as game producers Takeshi Otsuka and Teddy Cross.

Although the Tokyo-headquartered company is only announcing its existence today, it’s already a unicorn — it says it’s raised $100 million in Series A funding, at a valuation “just north of $1 billion.”

The round was led by Josh Buckley and Sequoia Capital, with participation from Sozo Ventures, Raymond Tonsing’s Caffeinated Capital, Keisuke Honda’s KSK Angel Fund, Taizo Son’s Mistletoe Singapore, Digital Garage, Will Smith’s Dreamers, Makers Fund and others.

Carter (Playco’s CEO) said the startup will be revealing its first games later this year. For now, he wants to talk about Playco’s vision: It’s trying to address the fact that “it’s very difficult to get two people into a single game in the App Store.” After all, downloading an app is a pretty big hurdle, especially compared to the early days of web and social gaming, when all you needed was a link.

“We’re going to bring that back,” Carter said — with Playco’s titles, sharing and playing a mobile game with your friend should be as simple as texting or calling them. “All it really takes is a hyperlink.”

He pointed to a number of technologies that can enable this “instant play” experience on mobile, including cloud gaming, HTML5 and platform-specific tools like Apple’s new App Clips. He claimed the team is “very good at this cutting edge technology” — and the company has created its own game engine — but he said technology is not the sole focus: “That’s just table stakes.”

Waldron (Playco’s president) argued that this represents the next big platform shift in gaming, and it will require “reinventing a lot of the most popular genres today” while also creating entirely new genres, in the same way that social gaming enabled new types of games.

The future (and past) of mobile gaming

“If you think about FarmVille, there were no farm games being advertised being in local console games store,” Waldron said. “They don’t market well; if you put up a poster for a farm game, no one wants to play.” But if your friends invite you by sending you some digital crops, then you absolutely want to play.

Carter added that enabling instant play also means that the games themselves have to be fairly straightforward, at least at first glance.

“Ultimately, as we build up the portfolio, we think about what makes the game accessible to anyone on the planet, any ethnicity, any language,” he said. “And the answer is: It has to be broadly appealing. That doesn’t mean we can’t build into it relatively interesting and deep features, but the initial impression has to be the right sort of experience that people can easily relate to.”

Carter also acknowledged that it’s unusual for a startup to raise so much money in its Series A (“It’s not your typical company, and it’s not your typical Series A”), but he said that being more ambitious with fundraising allowed Playco to quickly grow the team to 75 people.

“Bringing talented people together is the most important thing, and [thanks to the funding,] we haven’t had to make any really hard decisions,” he said.

As for how its games will make money, Waldron suggested that Playco will borrow from (but also potentially evolve) many of the existing business models in gaming.

“We don’t need to reinvent the wheel,” he said. “There’s going to be amazing things we can learn from my last company — we ended up inventing a lot of the ways these games are monetizing today … But these new technologies available today create new opportunities. The world has changed a lot since then, and I don’t think everything has caught up.”

Mobile gaming is a $68.5 billion global business, and investors are buying in

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Ireland’s data watchdog slammed for letting adtech carry on ‘biggest breach of all time’

A dossier of evidence detailing how the online ad targeting industry profiles Internet users’ intimate characteristics without their knowledge or consent has been published today by the Irish Council for Civil Liberties (ICCL), piling more pressure on the country’s data watchdog to take enforcement action over what complainants contend is the “biggest data breach of all time”.

The publication follows a now two-year-old complaint lodged with Ireland’s Data Protection Commission (DPC) claiming unlawful exploitation of personal data via the programmatic advertising Real-Time Bidding (RTB) process — including dominant RTB systems devised by Google and the Internet Advertising Bureau (IAB).

The Irish DPC opened an investigation into Google’s online Ad Exchange in May 2019, following a complaint filed by Dr Johnny Ryan (then at Brave, now a senior fellow at the ICCL) in September 2018 — but two years on that complaint, like so many major cross-border GDPR cases, remains unresolved.

And, indeed, multiple RTB complaints have been filed with regulators across the EU but none have yet been resolved. It’s a major black mark against the bloc’s flagship data protection framework.

“September 2020 marks two years since my formal complaint to the Irish Data Protection Commission about the “Real-Time Bidding” data breach. This submission demonstrates the consequences of two years of failure to enforce,” writes Ryan in the report.

Today, we release new data on the consequences of the biggest data breach of all time: Real-Time Bidding. Two years after my complaint about the RTB privacy crisis, @DPCIreland has failed to end it. @ICCLtweet https://t.co/4zj476UT3t pic.twitter.com/RvagTloWk4

— Johnny Ryan (@johnnyryan) September 21, 2020

Among hair-raising highlights in the ICCL dossier are that:

• Google’s RTB system sends data to 968 companies;
• that a data broker company which uses RTB data to profile people influenced the 2019 Polish Parliamentary Election by targeting LGBTQ+ people; 
• that a profile built by a data broker with RTB data allows users of Google’s system to target 1,200 people in Ireland profiled in a “Substance abuse” category, with other health condition profiles offered by the same data broker available via Google reported to include “Diabetes”, “Chronic Pain”, and “Sleep Disorders”;
• that the IAB’s RTB system allows users to target 1,300 people in Ireland profiled in a “AIDS & HIV” category, based on a data broker profile build with RTB data, while other categories from the same data broker include “Incest & Abuse Support”, “Brain Tumor”, “Incontinence”, and “Depression”;
• that a data broker that gathers RTB data tracked the movements of people in Italy to see if they observed the Covid-19 lockdown;
• that a data broker that illicitly profiled Black Lives Matters protesters in the US has also been allowed to gather RTB data about Europeans;
• that the industry template for profiles includes intimate personal characteristics such as “Infertility”, “STD”, and “Conservative” politics;

Under EU data protection law, personal information that relates to highly sensitive and intimate topics — such as health, sexuality and politics — is what’s known as special category personal data. Processing this type of information generally requires explicit consent from users — with only very narrow exceptions, such as for protecting the vital interests of the data subjects (and serving behavioral ads clearly wouldn’t meet such a bar).

So it’s hard to see how the current practices of the targeted ad industry can possibly be compliant with EU law, in spite of the massive scale on which Internet users’ data is being processed.

In the report, the ICCL estimates that just three ad exchanges (OpenX, IndexExchange and PubMatic) have made around 113.9 trillion RTB broadcasts in the past year.

“Google’s RTB system now sends people’s private data to more companies, and from more websites than when the DPC was notified two years ago,” it writes. “A single ad exchange using the IAB RTB system now sends 120 billion RTB broadcasts in a day, an increase of 140% over two years ago when the DPC was notified.”

“Real-Time Bidding operates behind the scenes on websites and apps. It constantly broadcasts the private things we do and watch online, and where we are in the real-world, to countless companies. As a result, we are all an open book to data broker companies, and others, who can build intimate dossiers about each of us,” it adds. 

Reached for a response to the report, Google sent us the following statement:

We enforce strict privacy protocols and standards to protect people’s personal information, including industry-leading safeguards on the use of data for real-time bidding. We do not allow advertisers to select ads based on sensitive personal data and we do not share people’s sensitive personal data, browsing histories or profiles with advertisers. We perform audits of ad buyers on Google’s ad exchange and if we find breaches of our policies we take action.

We also reached out to the IAB Europe for comment on the report. A spokeswoman told us it would issue a response tomorrow.

Responding to the ICCL submission, the DPC’s deputy commissioner Graham Doyle sent this statement: “Extensive recent updates and correspondence on this matter, including a meeting, have been provided by the DPC. The investigation has progressed and a full update on the next steps provided to the concerned party.”

However in a follow up to Doyle’s remarks, Ryan told TechCrunch he has “no idea” what the DPC is referring to when it mentions a “full update”. On “next steps” he said the regulator informed him it will produce a document setting out what it believes the issues are — within four weeks of its letter, dated September 15.

Ryan expressed particular concern that the DPC’s enquiry does not appear to cover security — which is the crux of the RTB complaints, since GDPR’s security principle puts an obligation on processors to ensure data is handled securely and protected against unauthorized processing or loss. (Whereas RTB broadcasts personal data across the Internet, leaking highly sensitive information in the process, per earlier evidence gathered by the complainants.)

He told TechCrunch the regulator finally sent him a letter, in May 2020, in response to his request to know what the scope of the inquiry is — saying then that it is examining the following issues:

• Whether Google has a lawful basis for processing of personal data, including special category data, for the purposes of targeted advertising via the Authorised Buyers mechanism and, specifically, for the sourcing, sharing and combining of the personal data collected by Google with other companies / partners;
• How Google complies with its transparency obligations, particularly with regard to Art. 5(1), 12, 13 and 14 of the GDPR;
• The legal basis / bases for Google’s retention of personal data processed in the context of the Authorised Buyers mechanism and how it complies with Article 5(1)(c) in respect of its retention of personal data processed through the Authorised Buyers mechanism;

We’ve asked the DPC to confirm whether its investigation of Google’s adtech is also examining compliance with GDPR Article 5(1)f and will update this report with any response.

The DPC did not respond to our question about the timing for any draft decision on Ryan’s two-year-old complaint. But Doyle also pointed us to work this year around cookies and other tracking technologies — including guidance on compliant usage — adding that it has set out its intention to begin related enforcement from next month, when a six-month grace period for industry to comply with the rules on tracking elapses.

The regulator also pointed to another related open enquiry — into adtech veteran Quantcast, also beginning in May 2019. (That enquiry followed a submission by privacy rights advocacy group, Privacy International.)

The DPC has said the Quantcast enquiry is examining the lawful basis claimed for processing Internet users’ data for ad targeting purposes, as well as considering whether transparency and data retention obligations are being fulfilled. It’s not clear whether the regulator is looking at the security of the data in that case, either. A summary of the scope of Quantcast enquiry in the DPC’s annual report states:

In particular, the DPC is examining whether Quantcast has discharged its obligations in connection with the processing and aggregating of personal data which it conducts for the purposes of profiling and utilising the profiles generated for targeted advertising. The inquiry is examining how, and to what extent, Quantcast fulfils its obligation to be transparent to individuals in relation to what it does with personal data (including sources of collection, combining and making the data available to its customers) as well as Quantcast’s personal data retention practices. The inquiry will also examine the lawful basis pursuant to which processing occurs.

While Ireland remains under huge pressure over the glacial pace of cross-border GDPR investigations, given it’s the lead regulator for many major tech platforms, it’s not the only EU regulator accused of sitting on its hands where enforcement is concerned.

The UK’s data watchdog has similarly faced anger for failing to act over RTB complaints — despite acknowledging systematic breaches. In its case, after months of regulatory inaction, the ICO announced earlier this year that it had ‘paused ‘its investigation into the industry’s processing of Internet users’ personal data — owing to disruption to businesses as a result of the COVID-19 pandemic.

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JavaPipe Web Hosting 101: How To Choose The Best One For Your Business Needs

A web hosting service is a kind of Internet-based service that enables organizations to create their own website on the Internet. This service can be very useful to a business or organization as it provides the services and features needed for running and maintaining a website. It also enables you to store your files on […]

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Benefits of Self-service Car Wash Technology

We all like to keep our cars in good condition. And one good way to do that is by visiting the car wash regularly. However, you may want to save some money by washing your car on your own. It is good, but the downside is that you may not have the proper equipment required […]

The post Benefits of Self-service Car Wash Technology appeared first on ALL TECH BUZZ.

Thanks to Google, app store monopoly concerns have now reached India

Last week, as Epic Games, Facebook, and Microsoft continued to express concerns about Apple’s “monopolistic” hold over what a billion people can download on their iPhones, a similar story unfolded in India, the world’s second largest internet market, between a giant developer and the operator of the only other large mobile app store.

Google pulled Paytm, the app from India’s most valuable startup, off of the Play Store on Friday. The app returned to the store eight hours later, but the controversy and acrimony Google has stirred up in the country will linger for years.

TechCrunch reported on Friday that Google pulled Paytm app from its app store after a repeat pattern of violations of Google Play Store guidelines by the Indian firm.

Paytm, which is locked in a battle against Google to win India’s payments market, has been frustrated at Google’s policies — which it argues gives Google an unfair advantage — for several past quarters over how the Android-maker is limiting its marketing campaigns to acquire new users, sources familiar with the matter told TechCrunch.

The explanation provided by Google to Paytm for why it pulled the Indian firm’s app this week from its app store is the latest attempt by the company to thwart the Noida-headquartered firm’s ability to acquire new users, Paytm executives said.

In a blog post Paytm posted Sunday evening (local India time), the Indian firm said Google took issue with the company for giving customers cashbacks and scratch cards for initiating transactions over UPI, a government-backed payments infrastructure in India that has become the most popular way for people to exchange money digitally in the country.

Paytm said it rolled out this new version of scratch cards that are linked to cricket on September 11. Users collected these cricket-themed stickers for sending money to others, or making transactions such as topping up credit on their phone or paying their broadband or electricity bill.

In a statement on Sunday evening, a Google spokesperson said, “offering cashbacks and vouchers alone do not constitute a violation of our Google Play gambling policies” and that Play Store “policies are applied and enforced on all developers consistently.”

But it’s arguably anything but consistent.

On September 18, Google told Paytm that it had pulled its app for not complying with Play Store’s “gambling policy” as it offered games with “loyalty points.” Paytm said that Google had not expressed any concerns over Paytm’s new marketing campaign prior to its notice on Friday, in which it revealed that Paytm app had been temporarily removed from the Play Store.

But Google itself is running a similar campaign linked to cricket in India, Paytm argues. (Why cricket? Cricket is immensely popular in India and one of the biggest cricket tournaments globally, Indian Premier League, kicked off its latest season on Saturday.)

Cricket-themed cashback offered by Paytm (left) and Google Pay (right) in India

Google Play Store in India has long prohibited apps that promote gambling such as betting on sporting events, and Google has raised concerns about Paytm’s marquee app promoting Paytm First Games, a fantasy sports app run by Paytm, in the past.

Paytm executives argued that PhonePe, a Walmart-owned payments app in India, also promoted Dream11, the most popular fantasy sports app in the country, and got away without any action.

Google also permits fantasy sports app operators — including Paytm — to advertise on Search in India.

Where is Google hypocritical? Fantasy games not allowed on the play store. But they can advertise on Google search. Cc @vijayshekhar

Top of the list is an app they banned today. pic.twitter.com/4USUD92kSc

— Nikhil Pahwa (@nixxin) September 18, 2020

“This is bullshit of a different degree,” Paytm chief executive Vijay Shekhar Sharma said of Google’s objection to Paytm offering cashback in a televised interview Friday. The removal of Paytm app was only on the grounds of Paytm offering cricket-themed cashback, he claimed. “Google is not allowing us to acquire new customers right now. That’s all what this is,” he added.

Google’s payments app, Google Pay, competes with Paytm in India. In fact, Google Pay is the largest payments app for peer-to-peer transaction between users in India and holds the largest market share in UPI.

Without identifying any names, Sharma, the poster child of Indian startup ecosystem, claimed that many founders in India have just accepted that it is Google that has the final say on any matter in India — and not the country’s regulatory agencies.

For Google, which reaches more users than any other company in India and whose Android operating system commands 99% of the local smartphone market, this kind of accusation is exactly what it needs to avoid in the country. The Silicon Valley search and advertising giant has launched a charm offensive in India, including a recently commitment to invest $10 billion — more than any other American or Chinese technology firm.

The timing for Google’s parent company, Alphabet, couldn’t be worse. Google is currently the subject of an antitrust complaint in India over an allegation that it has abused its market position to unfairly promote its mobile payments app in the country; and in the U.S., Congress has intimidated that it may pursue antitrust regulatory action against Alphabet and Apple over app store concerns.

In India, Google’s moves could have a devastating impact on businesses and everyday consumers.

Paytm is not just a payments app. It is also a fully licensed digital bank. And just an eight-hour of absence from the Play Store created a panic among a portion of its users. A source familiar with the matter told TechCrunch that Paytm saw several people withdraw their fixed deposit in Paytm Payments Bank on Friday.

Anecdotally, TechCrunch heard of instances where vendors who previously preferred Paytm for accepting money digitally asked their customers to use a different payments method as they had heard that Paytm was “banned” in India.

Sharma said Google’s monopoly on Indian app ecosystem is of a magnitude unparalleled elsewhere in the world.

“If paying someone and getting a cashback is gambling, then the same rule should be applied to everyone,” said Sharma. “It’s disgraceful that we are standing here at the cusp of an internet revolution in India and we are being sanctioned by companies that are not governed by the law of this country.”

If this sentiment gained traction in India it could create challenges for Google’s future in the world’s second largest internet market.

Meanwhile, the U.S. is forcing a Chinese company to sell stakes to local firms to continue operations in the country. In a recent episode of Dithering podcast, Ben Thompson cautioned that Trump administration’s move — which some have argued is a long due tit for tat against Chinese companies (as China has long prevented U.S. firms from meaningfully operating in the world’s largest  internet market) — might encourage other open markets to do to American firms what it is doing to TikTok.

Several U.S. tech executives share these concerns.

The problem with this TikTok deal is that the US is the largest player in tech globally. You can do this move once or twice, but we have far more to lose long term by setting a precedent like this.

— Aaron Levie (@levie) September 20, 2020

“I’ve said this before, but a US TikTok ban would be quite bad for Instagram, Facebook, and the internet more broadly,” Instagram chief executive Adam Mosseri tweeted earlier this week. “If you’re skeptical keep in mind that most of the people who use Instagram are outside the US, as is most of our potential growth. The long term costs of moods countries making aggressive demands and banning us over the next decade outweigh slowing down one competitor today.”

India, which Google, Facebook, and many other tech giants count as their biggest market by users, has made several proposals in the past three years — including mandates that foreign firms store payments information of users locally in India and companies help local enforcement agencies identify the originator of questionable messages circulating on their platforms — that are widely seen as protectionist moves.

And India is not even that open anymore. New Delhi has also banned more than 200 Chinese apps including TikTok, UC Browser, and PUBG Mobile citing cybersecurity concerns in recent months. India has not made public what those cybersecurity concerns are and in its orders acknowledged that users had expressed concerns.

Enough noise against a foreign firm might just be enough to face an avalanche of serious troubles in India.

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Original Content podcast: ‘Wireless’ shows off Quibi’s Turnstyle technology

“Wireless” is probably the best showcase so far for Quibi’s Turnstyle technology.

That’s the technology that allows the streaming video app to switch seamlessly between landscape and portrait mode depending on the orientation of your phone. With other Quibi shows, you’re essentially getting two views of the same footage — but with “Wireless” (which is executive produced by Steven Soderbergh), you’re switching between traditional cinematic footage (in landscape) and a view of the protagonist’s phone (in portrait).

In this bonus episode of the Original Content podcast, director Zach Wechter told me that he and his co-writer Jack Seidman wrote the initial script — about a college student played by Tye Sheridan who gets trapped in the snow after a car crash, with only his iPhone to save him — before they decided on the phone-centric format. But when they heard about Turnstyle, “It just felt like a match made in heaven that would allow us to facilitate this idea.”

I wondered whether that required going back and adding a bunch of phone interactions to the story, but said Wechter said, “It was quite the opposite. One thing we found in testing was when the phone plot moved really fast, it would be hard, because there are these two perspectives happening at once.”

So that actually meant “reducing some fo the intriacy of the plot happening on the phone” to ensure that viewers didn’t get lost.

And if you’re wondering which mode to focus on as you watch, Wechter has some simple advice: “Go with your gut.” He said he had a “roadmap” for when he was hoping to nudge viewers to turn their phones — like when there’s a notification sound or Sheridan focuses on his phone — “but I think the most important part of the experience is that we’re not indicating when our viewers turn, that it becomes this sort of passive-but-active viewing experience.”

Wechter described making the show — essentially a feature length film divided into episodes of 10 minutes or less — as shooting “two films that had to dance together” in just 19 days. And he made things even more challenging by insisting that all the phone/FaceTime calls and even the text messages be filmed live, rather than just recording both ends separately.

“When I think about directing and my job, really the most fundamental part of it to me is making the actorss comfortable, and I think that having a scene partner is paramount,” he said. “It was a long conversation about why we couldn’t just have them act off of a recording and shoot it separately — because it took a lot of logistical effort and resources to do it — but it really makes the scenes feel very alive and realistic.”

You can listen to the full interview in the player below, subscribe using Apple Podcasts or find us in your podcast player of choice. If you like the show, please let us know by leaving a review on Apple. You can also follow us on Twitter or send us feedback directly. (Or suggest shows and movies for us to review!)

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What Should Beginners Keep in Mind When Playing at An Online Casino

If you are a beginner in the world of digital gambling, then there is a lot that you need to learn. There is a variety of digital games in online casinos for virtual gambling which might seem a bit overwhelming initially, but as one explores different options and set particular interests, it gets into a […]

The post What Should Beginners Keep in Mind When Playing at An Online Casino appeared first on ALL TECH BUZZ.

Voting

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Unity Software has strong opening, gaining 31% after pricing above its raised range

Whoever said you can’t make money playing video games clearly hasn’t taken a look at Unity Software’s stock price.

On its first official day of trading, the company rose more than 31%, opening at $75 per share before closing the day at $68.35. Unity’s share price gains came after last night’s pricing of the company’s stock at $52 per share, well above the range of $44 to $48 which was itself an upward revision of the company’s initial target.

Games like “Pokémon GO” and “Iron Man VR” rely on the company’s software, as do untold numbers of other mobile gaming applications that use the company’s toolkit for support. The company’s customers range from small gaming publishers to large gaming giants like Electronic Arts, Niantic, Ubisoft and Tencent.

Unity’s IPO comes on the heels of other well-received debuts, including Sumo Logic, Snowflake and JFrog.

TechCrunch caught up with Unity’s CFO, Kim Jabal, after-hours today to dig in a bit on the transaction.

According to Jabal, hosting her company’s roadshow over Zoom had some advantages, as her team didn’t have to focus on tackling a single geography per day, allowing Unity to “optimize” its time based on who the company wanted to meet, instead, of say, whomever was free in Boston or Chicago on a particular Tuesday morning.

Unity IPO aims to fuel growth across gaming and beyond

Jabal’s comments aren’t the first that TechCrunch has heard regarding roadshows going well in a digital format instead of as an in-person presentation. If the old-school roadshow survives, we’ll be surprised, though private jet companies will miss the business.

Talking about the transaction itself, Jabal stressed the connection between her company’s employees, value  and their access to that same value. Unity’s IPO was unique in that existing and former employees were able to trade 15% of their vested holdings in the company on day one, excluding “current executive officers and directors,” per SEC filings.

That act does not seemed to have dampened enthusiasm for the company’s shares, and could have helped boost early float, allowing for the two sides of the supply and demand curves to more quickly meet close to the company’s real value, instead of a scarcity-driven, more artificial figure.

Bear and bull cases for Unity’s IPO

Regarding Unity’s IPO pricing, Jabal discussed what she called a “very data-driven process.” The result of that process was an IPO price that came in above its raised range, and still rose during its first day’s trading, but less than 50%. That’s about as good an outcome as you can hope for in an IPO.

One final thing for the SaaS nerds out there. Unity’s “dollar-based net expansion rate” went from very good to outstanding in 2020, or in the words of the S-1/A:

Our dollar-based net expansion rate, which measures expansion in existing customers’ revenue over a trailing 12-month period, grew from 124% as of December 31, 2018 to 133% as of December 31, 2019, and from 129% as of June 30, 2019 to 142% as of June 30, 2020, demonstrating the power of this strategy.

We had to ask. And the answer, per Jabal, was a combination of the company’s platform strength and how customers tend to use more of Unity’s services over time, which she described as growing with their customers. And the second key element was 2020’s unique dynamics that gave Unity a “tailwind” thanks to “increased usage, particularly in gaming.”

Looking at our own gaming levels in 2020 compared to 2019, that checks out.

This post closes the book on this week’s IPO class. Tired yet? Don’t be. Palantir is up next, and then Asana.

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Daily Crunch: Partial US TikTok ban is imminent

The Trump administration moves forwards with plans to ban TikTok and WeChat (although TikTok gets a partial extension), Unity goes public and we announce the winner of this year’s Startup Battlefield. This is your Daily Crunch for September 18, 2020.

The big story: US TikTok ban is imminent

The U.S. Commerce Department has released details about how it will be implementing the Trump administration’s domestic ban of TikTok and WeChat. Both apps will no longer be available (and will not be able to distribute updates) in U.S. app stores starting this Sunday, September 20.

At the same time, TikTok will be able to continue operations in the country until November 12, leaving the door open for a deal with Oracle or another partner.

TikTok, WeChat and their users aren’t the only ones unhappy about this decision. Instagram CEO Adam Mosseri said a TikTok ban would be “bad for US tech companies which have benefited greatly from the ability to operate across borders,” while the ACLU said the order “violates the First Amendment rights of people in the United States.”

The tech giants

Salesforce announces 12,000 new jobs in the next year just weeks after laying off 1,000 — Salesforce CEO and co-founder Marc Benioff announced in a tweet that the company would be hiring 4,000 new employees in the next six months, and 12,000 in the next year.

It’s game on as Unity begins trading — Unity Software, which sells a game development toolkit primarily for mobile phone app developers, raised $1.3 billion in its initial public offering.

Apple will launch its online store in India on September 23 — Apple currently relies on third-party online and offline retailers to sell its products in India.

Startups, funding and venture capital

And the winner of Startup Battlefield at Disrupt 2020 is … Canix — After five days of fierce pitching in a wholly new virtual Startup Battlefield arena, we have a winner.

Amid layoffs and allegations of fraud, the FBI has arrested NS8’s CEO following its $100+ million summer financing — Adam Rogas, the co-founder and former executive at the Las Vegas-based fraud prevention company NS8 was arrested by the Federal Bureau of Investigation.

Outschool, newly profitable, raises a $45 million Series B for virtual small group classes — Outschool’s services, which range from engineering lessons through Lego challenges to Spanish teaching by Taylor Swift songs, are now high in demand.

Advice and analysis from Extra Crunch

Are high churn rates depressing earnings for app developers? — RevenueCat’s Jacob Eiting writes that for all the hype around Apple’s 85/15 split for subscription revenue, very few developers are going to see a meaningful increase.

The stages of traditional fundraising — What you think when you hear “seed funding” and “A rounds” might be different from what investors think.

3 VCs discuss the state of SaaS investing in 2020 — Commentary from Canaan’s Maha Ibrahim, Andreessen Horowitz’s David Ulevitch and Bessemer’s Mary D’Onofrio.

(Reminder: Extra Crunch is our subscription membership program, which aims to democratize information about startups. You can sign up here.)

Everything else

How the NSA is disrupting foreign hackers targeting COVID-19 vaccine research — “The threat landscape has changed,” the NSA’s director of cybersecurity Anne Neuberger said at Disrupt 2020.

NASA to test precision automated landing system designed for the moon and Mars on upcoming Blue Origin mission — The “Safe and Precise Landing – Integrated Capabilities Evolution” (SPLICE) system is made up of a number of lasers, an optical camera and a computer.

The Daily Crunch is TechCrunch’s roundup of our biggest and most important stories. If you’d like to get this delivered to your inbox every day at around 3pm Pacific, you can subscribe here.

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Are high churn rates depressing earnings for app developers?

Jacob Eiting Contributor

Jacob Eiting is CEO of RevenueCat, a platform for managing cross-platform in-app purchases, products and subscribers and analyzing in-app-purchase data.

Ever since Apple opened up subscription monetization to more apps in 2016 — and enticed developers with an 85/15 split on revenue from customers that remain subscribed for more than a year — subscription monetization and retention has felt like the Holy Grail for app developers. So much so that Google quickly followed suit in what appeared to be an example of healthy competition for developers in the mobile OS duopoly.

But how does that split actually work out for most apps? Turns out, the 85/15 split — which Apple is keen to mention anytime developers complain about the App Store rev share — doesn’t have a meaningful impact for most developers. Because churn.

No matter how great an app is, subscribers are going to churn. Sometimes it’s because of a credit card expiring or some other billing issue. And sometimes it’s more of a pause, and the user comes back after a few months. But the majority of churn comes from subscribers who, for whatever reason, decide that the app just isn’t worth paying for anymore. If a subscriber churns before the one-year mark, the developer never sees that 85% split. And even if the user resubscribes, Apple and Google reset the clock if a subscription has lapsed for more than 60 days. Rather convenient… for Apple and Google.

Top mobile apps like Netflix and Spotify report churn rates in the low single digits, but they are the outliers. According to our data, the median churn rate for subscription apps is around 13% for monthly subscriptions and around 50% for annual. Monthly subscription churn is generally a bit higher in the first few months, then it tapers off. But an average churn of 13% leaves just 20% of subscribers crossing that magical 85/15 threshold.

In practice, what this means is that, for all the hype around the 85/15 split, very few developers are going to see a meaningful increase in revenue:

Image Credits: RevenueCat (opens in a new window)

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Improving the Accuracy of Genomic Analysis with DeepVariant 1.0

Posted by Andrew Carroll, Product Lead, and Pi-Chuan Chang, Technical Lead, Google Health

Sequencing genomes involves sampling short pieces of the DNA from the ~6 billion pairs of nucleobases — i.e., adenine (A), thymine (T), guanine (G), and cytosine (C) — we inherit from our parents. Genome sequencing is enabled by two key technologies: DNA sequencers (hardware) that "read" relatively small fragments of DNA, and variant callers (software) that combine the reads to identify where and how an individual's genome differs from a reference genome, like the one assembled in the Human Genome Project. Such variants may be indicators of genetic disorders, such as an elevated risk for breast cancer, pulmonary arterial hypertension, or neurodevelopmental disorders.

In 2017, we released DeepVariant, an open-source tool which identifies genome variants in sequencing data using a convolutional neural network (CNN). The sequencing process begins with a physical sample being sequenced by any of a handful of instruments, depending on the end goal of the sequencing. The raw data, which consists of numerous reads of overlapping fragments of the genome, are then mapped to a reference genome. DeepVariant analyzes these mappings to identify variant locations and distinguish them from sequencing errors.

Soon after it was first published in 2018, DeepVariant underwent a number of updates and improvements, including significant changes to improve accuracy for whole exome sequencing and polymerase chain reaction (PCR) sequencing.

We are now releasing DeepVariant v1.0, which incorporates a large number of improvements for all sequencing types. DeepVariant v1.0 is an improved version of our submission to the PrecisionFDA v2 Truth Challenge, which achieved Best Overall accuracy for 3 of 4 instrument categories. Compared to previous state-of-the-art models, DeepVariant v1.0 significantly reduces the errors for widely-used sequencing data types, including Illumina and Pacific Biosciences. In addition, through a collaboration with the UCSC Genomics Institute, we have also released a model that combines DeepVariant with the UCSC’s PEPPER method, called PEPPER-DeepVariant, which extends coverage to Oxford Nanopore data for the first time.

Sequencing Technologies and DeepVariant
For the last decade, the majority of sequence data were generated using Illumina instruments, which produce short (75-250 bases) and accurate sequences. In recent years, new technologies have become available that can sequence much longer pieces, including Pacific Biosciences, which can produce long and accurate sequences up to ~15,000 bases in length, and Oxford Nanopore, which can produce reads up to 1 million bases long, but with higher error rates. The particular type of sequencing data a researcher might use depends on the ultimate use-case.

Because DeepVariant is a deep learning method, we can quickly re-train it for these new instrument types, ensuring highly accurate sequence identification. Accuracy is important because a missed variant call could mean missing the causal variant for a disorder, while a false positive variant call could lead to identifying an incorrect one. Earlier state-of-the-art methods could reach ~99.1% accuracy (~73,000 errors) on a 35-fold coverage Illumina whole genome, whereas an early version of DeepVariant (v0.10) had ~99.4% accuracy (46,000 errors), corresponding to a 38% error reduction. DeepVariant v1.0 reduces Illumina errors by another ~22% and PacBio errors by another ~52% relative to the last DeepVariant release (v0.10).

DeepVariant Overview
DeepVariant is a convolutional neural network (CNN) that treats the task of identifying genetic variants as an image classification problem. DeepVariant constructs tensors, essentially multi-channel images, where each channel represents an aspect of the sequence, such as the bases in the sequence (called read base), the quality of alignment between different reads (mapping quality), whether a given read supports an alternate allele (read supports variant), etc. It then analyzes these data and outputs three genotype likelihoods, corresponding to how many copies (0, 1, or 2) of a given alternate allele are present.

Example of DeepVariant data. Each row of pixels in each panel corresponds to a single read, i.e., a short genetic sequence. The top, middle, and bottom rows of panels present examples with a different number of variant alleles. Only two of the six data channels are shown: Read base — the pixel value is mapped to each of the four bases, A, C, G, or T; Read supports variant — white means that the read is consistent with a given allele and grey means it is not. Top: Classified by DeepVariant as a "2", which means that both chromosomes match the variant allele. Middle: Classified as a “1”, meaning that one chromosome matches the variant allele. Bottom: Classified as a “0”, implying that the variant allele is missing from both chromosomes.

Technical Improvements in DeepVariant v1.0
Because DeepVariant uses the same codebase for each data type, improvements apply to each of Illumina, PacBio, and Oxford Nanopore. Below, we show the numbers for Illumina and PacBio for two types of small variants: SNPs (single nucleotide polymorphisms, which change a single base without changing sequence length) and INDELs (insertions and deletions).

• Training on an extended truth set

  The Genome in a Bottle consortium from the National Institute of Standards and Technology (NIST) creates gold-standard samples with known variants covering the regions of the genome. These are used as labels to train DeepVariant. Using long-read technologies the Genome in a Bottle expanded the set of confident variants, increasing the regions described by the standard set from 85% of the genome to 92% of it. These more difficult regions were already used in training the PacBio models, and including them in the Illumina models reduced errors by 11%. By relaxing the filter for reads of lower mapping quality, we further reduced errors by 4% for Illumina and 13% for PacBio.

• Haplotype sorting of long reads

  We inherit one copy of DNA from our mother and another from our father. PacBio and Oxford Nanopore sequences are long enough to separate sequences by parental origin, which is called a haplotype. By providing this information to the neural network, DeepVariant improves its identification of random sequence errors and can better determine whether a variant has a copy from one or both parents.

• Re-aligning reads to the alternate (ALT) allele

  DeepVariant uses input sequence fragments that have been aligned to a reference genome. The optimal alignment for variants that include insertions or deletions could be different if the aligner knew they were present. To capture this information, we implemented an additional alignment step relative to the candidate variant. The figure below shows an additional second row where the reads are aligned to the candidate variant, which is a large insertion. You can see sequences that abruptly stop in the first row can now be fully aligned, providing additional information.

  

  Example of DeepVariant data with realignment to ALT allele. DeepVariant is presented the information in both rows of data for the same example. Only two of the six data channels are shown: Read base (channel #1) and Read supports variant (channel #5). Top: Shows the reads aligned to the reference (in DeepVariant v0.10 and earlier this is all DeepVariant sees). Bottom: Shows the reads aligned to the candidate variant, in this case a long insertion of sequence). The red arrow indicates where the inserted sequence begins.

• Use a small network to post-process outputs

  Variants can have multiple alleles, with a different base inherited from each parent. DeepVariant’s classifier only generates a probability for one potential variant at a time. In previous versions, simple hand-written rules converted the probabilities into a composite call, but these rules failed in some edge cases. In addition, it also separated the way a final call was made from the backpropagation to train the network. By adding a small, fully-connected neural network to the post-processing step, we are able to better handle these tricky multi-allelic cases.

• Adding data to train the release model

  The timeframe for the competition was compressed, so we trained only with data similar to the challenge data (PCR-Free NovaSeq) to speed model training. In our production releases, we seek high accuracy for multiple instruments as well as PCR+ preparations. Training with data from these diverse classes helps the model generalize, so our DeepVariant v1.0 release model outperforms the one submitted.

The charts below show the error reduction achieved by each improvement.

Training a Hybrid model
DeepVariant v1.0 also includes a hybrid model for PacBio and Illumina reads. In this case, the model leverages the strengths of both input types, without needing new logic.

Example of DeepVariant merging data from both PacBio and Illumina. Only two of the six data channels are shown: Read base (channel #1) and Read supports variant (channel #5). The longer PacBio reads (at the upper part of the image) span the region being called entirely, while the shorter Illumin reads span only a portion of the region.

We observed no change in SNP errors, suggesting that PacBio reads are strictly superior for SNP calling. We observed a further 49% reduction in Indel errors relative to the PacBio model, suggesting that the Indel error modes of Illumina and PacBio HiFi can be used in a complementary manner.

PEPPER-Deepvariant: A Pipeline for Oxford Nanopore Data Using DeepVariant
Until the PrecisionFDA competition, a DeepVariant model was not available for Oxford Nanopore data, because the higher base error rate created too many candidates for DeepVariant to classify. We partnered with the UC Santa Cruz Genomics Institute, which has extensive expertise with Nanopore data. They had previously trained a deep learning method called PEPPER, which could narrow down the candidates to a more tractable number. The larger neural network of DeepVariant can then accurately characterize the remaining candidates with a reasonable runtime.

The combined PEPPER-DeepVariant pipeline with the Oxford Nanopore model is open-source and available on GitHub. This pipeline was able to achieve a superior SNP calling accuracy to DeepVariant Illumina on the PrecisionFDA challenge, which is the first time anyone has shown Nanopore outperforming Illumina in this way.

Conclusion
DeepVariant v1.0 isn’t the end of development. We look forward to working with the genomics community to further maximize the value of genomic data to patients and researchers.

MIT engineers develop a totally flat fisheye lens that could make wide-angle cameras easier to produce

Engineers at MIT, in partnership with the University of Massachusetts at Lowell, have devised a way to build a camera lens that avoids the typical spherical curve of ultra-wide-angle glass, while still providing true optical fisheye distortion. The fisheye lens is relatively specialist, producing images that can cover as wide an area as 180 degrees or more, but they can be very costly to produce, and are typically heavy, large lenses that aren’t ideal for use on small cameras like those found on smartphones.

This is the first time that a flat lens has been able to product clear, 180-degree images that cover a true panoramic spread. The engineers were able to make it work by patterning a thin wafer of glass on one side with microscopic, three-dimensional structures that are positioned very precisely in order to scatter any inbound light in precisely the same way that a curved piece of glass would.

The version created by the researchers in this case is actually designed to work specifically with the infrared portion of the light spectrum, but they could also adapt the design to work with visible light, they say. Whether IR or visible light, there are a range of potential uses of this technology, since capturing a 180-degree panorama is useful not only in some types of photography, but also for practical applications like medical imaging, and in computer vision applications where range is important to interpreting imaging data.

This design is just one example of what’s called a ‘Metalens’ – lenses that make use of microscopic features to change their optical characteristics in ways that would traditionally have been accomplished through macro design changes – like building a lens with an outward curve, for instance, or stacking multiple pieces of glass with different curvatures to achieve a desired field of view.

What’s unusual here is that the ability to accomplish a clear, detailed and accurate 180-degree panoramic image with a perfectly flat metalens design came as a surprise even to the engineers who worked on the project. It’s definitely an advancement of the science that goes beyond what may assumed was the state of the art.

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