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Juniper Networks acquires Boston-area AI SD-WAN startup 128 Technology for $450M
Today Juniper Networks announced it was acquiring smart wide area networking startup 128 Technology for $450 million.
This marks the second AI-fueled networking company Juniper has acquired in the last year and a half after purchasing Mist Systems in March 2019 for $405 million. With 128 Technology, the company gets more AI SD-WAN technology. SD-WAN is short for software-defined wide area networks, which means networks that cover a wide geographical area such as satellite offices, rather than a network in a defined space.
Today, instead of having simply software-defined networking, the newer systems use artificial intelligence to help automate session and policy details as needed, rather than dealing with static policies, which might not fit every situation perfectly.
Writing in a company blog post announcing the deal, executive vice president and chief product officer Manoj Leelanivas sees 128 Technology adding great flexibility to the portfolio as it tries to transition from legacy networking approaches to modern ones driven by AI, especially in conjunction with the Mist purchase.
“Combining 128 Technology’s groundbreaking software with Juniper SD-WAN, WAN Assurance and Marvis Virtual Network Assistant (driven by Mist AI) gives customers the clearest and quickest path to full AI-driven WAN operations — from initial configuration to ongoing AIOps, including customizable service levels (down to the individual user), simple policy enforcement, proactive anomaly detection, fault isolation with recommended corrective actions, self-driving network operations and AI-driven support,” Leelanivas wrote in the blog post.
128 Technologies was founded in 2014 and raised over $96 million, according to Crunchbase data. Its most recent round was a $30 million Series D investment in September 2019 led by G20 Ventures and The Perkins Fund.
In addition to the $450 million, Juniper has asked 128 Technology to issue retention stock bonuses to encourage the startup’s employees to stay on during the transition to the new owners. Juniper has promised to honor this stock under the terms of the deal. The deal is expected to close in Juniper’s fiscal fourth quarter, subject to normal regulatory review.
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The OpenStack Foundation becomes the Open Infrastructure Foundation
This has been a long time coming, but the OpenStack Foundation today announced that it is changing its name to “Open Infrastructure Foundation,” starting in 2021.
The announcement, which the foundation made at its virtual developer conference, doesn’t exactly come as a surprise. Over the course of the last few years, the organization started adding new projects that went well beyond the core OpenStack project, and renamed its conference to the “Open Infrastructure Summit.” The organization actually filed for the “Open Infrastructure Foundation” trademark back in April.
Image Credits: OpenStack Foundation
After years of hype, the open-source OpenStack project hit a bit of a wall in 2016, as the market started to consolidate. The project itself, which helps enterprises run their private cloud, found its niche in the telecom space, though, and continues to thrive as one of the world’s most active open-source projects. Indeed, I regularly hear from OpenStack vendors that they are now seeing record sales numbers — despite the lack of hype. With the project being stable, though, the Foundation started casting a wider net and added additional projects like the popular Kata Containers runtime and CI/CD platform Zuul.
“We are officially transitioning and becoming the Open Infrastructure Foundation,” long-term OpenStack Foundation executive president Jonathan Bryce told me. “That is something that I think is an awesome step that’s built on the success that our community has spawned both within projects like OpenStack, but also as a movement […], which is [about] how do you give people choice and control as they build out digital infrastructure? And that is, I think, an awesome mission to have. And that’s what we are recognizing and acknowledging and setting up for another decade of doing that together with our great community.”
In many ways, it’s been more of a surprise that the organization waited as long as it did. As the foundation’s COO Mark Collier told me, the team waited because it wanted to be sure that it did this right.
“We really just wanted to make sure that all the stuff we learned when we were building the OpenStack community and with the community — that started with a simple idea of ‘open source should be part of cloud, for infrastructure.’ That idea has just spawned so much more open source than we could have imagined. Of course, OpenStack itself has gotten bigger and more diverse than we could have imagined,” Collier said.
As part of today’s announcement, the group also announced that its board approved four new members at its Platinum tier, its highest membership level: Ant Group, the Alibaba affiliate behind Alipay, embedded systems specialist Wind River, China’s FiberHome (which was previously a Gold member) and Facebook Connectivity. These companies will join the new foundation in January. To become a Platinum member, companies must contribute $350,000 per year to the foundation and have at least two full-time employees contributing to its projects.
“If you look at those companies that we have as Platinum members, it’s a pretty broad set of organizations,” Bryce noted. “AT&T, the largest carrier in the world. And then you also have a company Ant, who’s the largest payment processor in the world and a massive financial services company overall — over to Ericsson, that does telco, Wind River, that does defense and manufacturing. And I think that speaks to that everybody needs infrastructure. If we build a community — and we successfully structure these communities to write software with a goal of getting all of that software out into production, I think that creates so much value for so many people: for an ecosystem of vendors and for a great group of users and a lot of developers love working in open source because we work with smart people from all over the world.”
The OpenStack Foundation’s existing members are also on board and Bryce and Collier hinted at several new members who will join soon but didn’t quite get everything in place for today’s announcement.
We can probably expect the new foundation to start adding new projects next year, but it’s worth noting that the OpenStack project continues apace. The latest of the project’s bi-annual releases, dubbed “Victoria,” launched last week, with additional Kubernetes integrations, improved support for various accelerators and more. Nothing will really change for the project now that the foundation is changing its name — though it may end up benefitting from a reenergized and more diverse community that will build out projects at its periphery.
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Edge computing startup Edgify secures $6.5M seed from Octopus, Mangrove and semiconductor
Edgify, which builds AI for edge computing, has secured a $6.5 million seed funding round backed by Octopus Ventures, Mangrove Capital Partners and an unnamed semiconductor giant. The name was not released but TechCrunch understands it may be Intel Corp. or Qualcomm Inc.
Edgify’s technology allows “edge devices” (devices at the edge of the internet) to interpret vast amounts of data, train an AI model locally and then share that learning across its network of similar devices. This then trains all the other devices in anything from computer vision, NLP, voice recognition or any other form of AI.
The technology can be applied to anything from MRI machines, connected cars, checkout lanes, mobile devices and anything that has a CPU, GPU or NPU. Edgify’s technology is already being used in supermarkets, for instance.
Ofri Ben-Porat, CEO and co-founder of Edgify, commented in a statement: “Edgify allows companies, from any industry, to train complete deep learning and machine learning models, directly on their own edge devices. This mitigates the need for any data transfer to the Cloud and also grants them close to perfect accuracy every time, and without the need to retrain centrally.”
Mangrove partner Hans-Jürgen Schmitz, who will join Edgify’s Board comments: “We expect a surge in AI adoption across multiple industries with significant long-term potential for Edgify in medical and manufacturing, just to name a few.”
Simon King, partner and Deep Tech Investor at Octopus Ventures added: “As the interconnected world we live in produces more and more data, AI at the edge is becoming increasingly important to process large volumes of information.”
So-called “edge computing” is seen as being one of the forefronts of deep tech right now.
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How Roblox completely transformed its tech stack
Picture yourself in the role of CIO at Roblox in 2017.
At that point, the gaming platform and publishing system that launched in 2005 was growing fast, but its underlying technology was aging, consisting of a single data center in Chicago and a bunch of third-party partners, including AWS, all running bare metal (nonvirtualized) servers. At a time when users have precious little patience for outages, your uptime was just two nines, or less than 99% (five nines is considered optimal).
Unbelievably, Roblox was popular in spite of this, but the company’s leadership knew it couldn’t continue with performance like that, especially as it was rapidly gaining in popularity. The company needed to call in the technology cavalry, which is essentially what it did when it hired Dan Williams in 2017.
Williams has a history of solving these kinds of intractable infrastructure issues, with a background that includes a gig at Facebook between 2007 and 2011, where he worked on the technology to help the young social network scale to millions of users. Later, he worked at Dropbox, where he helped build a new internal network, leading the company’s move away from AWS, a major undertaking involving moving more than 500 petabytes of data.
When Roblox approached him in mid-2017, he jumped at the chance to take on another major infrastructure challenge. While they are still in the midst of the transition to a new modern tech stack today, we sat down with Williams to learn how he put the company on the road to a cloud-native, microservices-focused system with its own network of worldwide edge data centers.
Scoping the problem
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Greycroft, Lerer Hippeau and Audible back audio measurement startup Veritonic
Veritonic is announcing that it has raised $3.2 million in Series A funding led by Greycroft, with participation from Lerer Hippeau and Amazon-owned audiobook service Audible.
CEO Scott Simonelli, who founded the New York startup with COO Andrew Eisner and CTO Kevin Marshall, told me that his goal is to create a new category of “audio intelligence” — namely, measuring and predicting the effectiveness of any piece of audio content or advertising.
The company is focused on marketing initially, with its first product, Creative Measurement, analyzing any audio ad and showing marketers how it scores compared to similar content, as well as identifying which parts of the audio are most effective. And Veritonic is launching a new product, Competitive Intelligence, which helps businesses see how and where their competitors are spending on advertising and provides alerts when those competitors launch a new ad.
Simonelli said that until now, audio measurement has been limited to things like creating audience panels with a few hundred people, which simply doesn’t scale, given the enormous growth in the audio market.
Veritonic, on the other hand, has analyzed thousands of audio files, correlating the content with data about how people responded and using that analysis to predict how people will respond to new audio. Simonelli said the company can add more “fuel” by going out and gathering more human response data, but even without additional data, it can provide an instant prediction on an ad or campaign’s effectiveness.
Image Credits: Veritonic
Simonelli also noted that Veritonic has spent the past five years developing technology that’s specifically attuned to the challenges of measuring audio effectiveness — like the fact that audio is experienced over time and, even more than other media, needs to be memorable.
“We can look at a sonic profile and predict and evaluate how somebody is going to respond,” he said.
The ultimate goal, he added, is to create the “benchmark for audio advertising,” which means working with a variety of players in the industry. For example, he said that when you look at other audio investments in Greycroft’s portfolio (such as podcast network Wondery or podcast analytics company Podsights): “Veritonic makes every one of those audio investments more valuable.”
Veritonic’s made pretty good progress on that goal already, with partners including Pandora, SiriusXM and NPR, and brand clients like Pepsi, Visa and Subway. It was previously backed by Newark Venture Partners (whose founder Don Katz previously founded Audible).
“We are excited to be a part of Veritonic’s continued growth and success,” said Greycroft’s Alan Patricof in a statement. “I’m personally very passionate about the future of voice, and the team at Veritonic deeply understands how to use audio to drive recall, stickiness and brand awareness — which is hugely important in a highly-competitive consumer brand landscape.”
Simonelli added that Veritonic will use the new funding to expand its data science and sales teams. Eventually, he hopes to start analyzing non-advertising content as well — for example, since Audible is an investor, he said, “Analyzing every audiobook on the planet is something we’re ready for and excited to do.”
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Former Apple engineer and autocorrect creator builds his first app, a word game called Up Spell
Former Apple software engineer and designer Ken Kocienda, whose work included the original iPhone and the development of touchscreen autocorrect, has created his first iOS app, Up Spell. The fast-paced, fun word game challenges users to spell all the words you can in two minutes and uses a lexicon of words Kocienda built to allow for the inclusion of proper names. A portion of app revenues are also being donated to a local food bank, so you can help give back while relieving stress through gaming.
Kocienda says he had never before made a standalone iOS app.
When he worked at Apple, all the code he wrote was integrated into a bigger iOS release. So when Kocienda got the idea to develop a game, he looked to obvious sources of inspiration: his past experiences with typing, keyboards and autocorrect.
The game’s lexicon was built first with the New General Service List to serve as its foundation. This was followed by weeks of writing small programs to generate lists of candidate words — like, by adding an “S” to existing words to pluralize them, for example. And hours more were spent scanning lists to choose the words to include.
Kocienda says he also wanted the game to be fun, and personally found it frustrating that other word games wouldn’t allow proper names.
“Many games accept words like PHARAOH and PYRAMID, but not NILE or EGYPT. This doesn’t make sense to me. These are all words!,” he says.
So he built his own list that includes thousands of proper names, then added to it more slang and contractions to expand it even further. That means you can spell a word like S’MORES, which involves an apostrophe, for example.
Image Credits: Up Spell
While support for a variety of words, including proper names, is the key way the gameplay differentiates from rivals, the app’s business model is also one that’s becoming less common these days: it’s a one-time paid download.
The app is a $1.99 download that lets you pay once to play forever. Today, many games in this same space use a freemium model where the app download itself is free, but you’re then nagged with in-app hooks to buy coins or tokens to advance gameplay or unlock certain features.
Kocienda’s decision to forgo this model was intentional, he explains.
“I made Up Spell a two-minute game without much in the way of gameplay gimmicks,” says Kocienda. “You just spell words. 2020 has been a rough year for everyone, and sometimes taking out two minutes to think about nothing but spelling a few words is just the kind of right kind of stress reliever,” he adds. “I hope Up Spell brings people a little unexpected happiness to their 2020.”
Also of note, 25 cents per download is being donated to the San Francisco-Marin Food Bank, which works to get food to vulnerable people in Kocienda’s area.
If all goes well, Up Spell may be followed by other games with a similar model, like a sounds or color-matching games, for instance.
The new game is a one-time paid download on the App Store.
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Kong launches Kong Konnect, its cloud-native connectivity platform
At its (virtual) Kong Summit 2020, API platform Kong today announced the launch of Kong Konnect, its managed end-to-end cloud-native connectivity platform. The idea here is to give businesses a single service that allows them to manage the connectivity between their APIs and microservices and help developers and operators manage their workflows across Kong’s API Gateway, Kubernetes Ingress and Kong Service Mesh runtimes.
“It’s a universal control plane delivery cloud that’s consumption-based, where you can manage and orchestrate API gateway runtime, service mesh runtime, and Kubernetes Ingress controller runtime — and even Insomnia for design — all from one platform,” Kong CEO and co-founder Augusto “Aghi” Marietti told me.
The new service is now in private beta and will become generally available in early 2021.
Image Credits: Kong
At the core of the platform is Kong’s new so-called ServiceHub, which provides that single pane of glass for managing a company’s services across the organization (and make them accessible across teams, too).
As Marietti noted, organizations can choose which runtime they want to use and purchase only those capabilities of the service that they currently need. The platform also includes built-in monitoring tools and supports any cloud, Kubernetes provider or on-premises environment, as long as they are Kubernetes-based.
The idea here, too, is to make all these tools accessible to developers and not just architects and operators. “I think that’s a key advantage, too,” Marietti said. “We are lowering the barrier by making a connectivity technology easier to be used by the 50 million developers — not just by the architects that were doing big grand plans at a large company.”
To do this, Konnect will be available as a self-service platform, reducing the friction of adopting the service.
Image Credits: Kong
This is also part of the company’s grander plan to go beyond its core API management services. Those services aren’t going away, but they are now part of the larger Kong platform. With its open-source Kong API Gateway, the company built the pathway to get to this point, but that’s a stable product now and it’s now clearly expanding beyond that with this cloud connectivity play that takes the company’s existing runtimes and combines them to provide a more comprehensive service.
“We have upgraded the vision of really becoming an end-to-end cloud connectivity company,” Marietti said. “Whether that’s API management or Kubernetes Ingress, […] or Kuma Service Mesh. It’s about connectivity problems. And so the company uplifted that solution to the enterprise.”
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As it closes in on Arm, Nvidia announces UK supercomputer dedicated to medical research
As Nvidia continues to work through its deal to acquire Arm from SoftBank for $40 billion, the computing giant is making another big move to lay out its commitment to investing in U.K. technology. Today the company announced plans to develop Cambridge-1, a new £40 million AI supercomputer that will be used for research in the health industry in the country, the first supercomputer built by Nvidia specifically for external research access, it said.
Nvidia said it is already working with GSK, AstraZeneca, London hospitals Guy’s and St Thomas’ NHS Foundation Trust, King’s College London and Oxford Nanopore to use the Cambridge-1. The supercomputer is due to come online by the end of the year and will be the company’s second supercomputer in the country. The first is already in development at the company’s AI Center of Excellence in Cambridge, and the plan is to add more supercomputers over time.
The growing role of AI has underscored an interesting crossroads in medical research. On one hand, leading researchers all acknowledge the role it will be playing in their work. On the other, none of them (nor their institutions) have the resources to meet that demand on their own. That’s driving them all to get involved much more deeply with big tech companies like Google, Microsoft and, in this case, Nvidia, to carry out work.
Alongside the supercomputer news, Nvidia is making a second announcement in the area of healthcare in the U.K.: it has inked a partnership with GSK, which has established an AI hub in London, to build AI-based computational processes that will be used in drug vaccine and discovery — an especially timely piece of news, given that we are in a global health pandemic and all drug makers and researchers are on the hunt to understand more about, and build vaccines for, COVID-19.
The news is coinciding with Nvidia’s industry event, the GPU Technology Conference.
“Tackling the world’s most pressing challenges in healthcare requires massively powerful computing resources to harness the capabilities of AI,” said Jensen Huang, founder and CEO of Nvidia, in his keynote at the event. “The Cambridge-1 supercomputer will serve as a hub of innovation for the U.K., and further the groundbreaking work being done by the nation’s researchers in critical healthcare and drug discovery.”
The company plans to dedicate Cambridge-1 resources in four areas, it said: industry research, in particular joint research on projects that exceed the resources of any single institution; university granted compute time; health-focused AI startups; and education for future AI practitioners. It’s already building specific applications in areas, like the drug discovery work it’s doing with GSK, that will be run on the machine.
The Cambridge-1 will be built on Nvidia’s DGX SuperPOD system, which can process 400 petaflops of AI performance and 8 petaflops of Linpack performance. Nvidia said this will rank it as the 29th fastest supercomputer in the world.
“Number 29” doesn’t sound very groundbreaking, but there are other reasons why the announcement is significant.
For starters, it underscores how the supercomputing market — while still not a mass-market enterprise — is increasingly developing more focus around specific areas of research and industries. In this case, it underscores how health research has become more complex, and how applications of artificial intelligence have both spurred that complexity but, in the case of building stronger computing power, also provides a better route — some might say one of the only viable routes in the most complex of cases — to medical breakthroughs and discoveries.
It’s also notable that the effort is being forged in the U.K. Nvidia’s deal to buy Arm has seen some resistance in the market — with one group leading a campaign to stop the sale and take Arm independent — but this latest announcement underscores that the company is already involved pretty deeply in the U.K. market, bolstering Nvidia’s case to double down even further. (Yes, chip reference designs and building supercomputers are different enterprises, but the argument for Nvidia is one of commitment and presence.)
“AI and machine learning are like a new microscope that will help scientists to see things that they couldn’t see otherwise,” said Dr. Hal Barron, chief scientific officer and president, R&D, GSK, in a statement. “NVIDIA’s investment in computing, combined with the power of deep learning, will enable solutions to some of the life sciences industry’s greatest challenges and help us continue to deliver transformational medicines and vaccines to patients. Together with GSK’s new AI lab in London, I am delighted that these advanced technologies will now be available to help the U.K.’s outstanding scientists.”
“The use of big data, supercomputing and artificial intelligence have the potential to transform research and development; from target identification through clinical research and all the way to the launch of new medicines,” added James Weatherall, PhD, head of Data Science and AI, AstraZeneca, in his statement.
“Recent advances in AI have seen increasingly powerful models being used for complex tasks such as image recognition and natural language understanding,” said Sebastien Ourselin, head, School of Biomedical Engineering & Imaging Sciences at King’s College London. “These models have achieved previously unimaginable performance by using an unprecedented scale of computational power, amassing millions of GPU hours per model. Through this partnership, for the first time, such a scale of computational power will be available to healthcare research – it will be truly transformational for patient health and treatment pathways.”
Dr. Ian Abbs, chief executive & chief medical director of Guy’s and St Thomas’ NHS Foundation Trust Officer, said: “If AI is to be deployed at scale for patient care, then accuracy, robustness and safety are of paramount importance. We need to ensure AI researchers have access to the largest and most comprehensive datasets that the NHS has to offer, our clinical expertise, and the required computational infrastructure to make sense of the data. This approach is not only necessary, but also the only ethical way to deliver AI in healthcare – more advanced AI means better care for our patients.”
“Compact AI has enabled real-time sequencing in the palm of your hand, and AI supercomputers are enabling new scientific discoveries in large-scale genomic data sets,” added Gordon Sanghera, CEO, Oxford Nanopore Technologies. “These complementary innovations in data analysis support a wealth of impactful science in the U.K., and critically, support our goal of bringing genomic analysis to anyone, anywhere.”
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Pixie Labs raises $9.15M Series A round for its Kubernetes observability platform
Pixie, a startup that provides developers with tools to get observability into their Kubernetes-native applications, today announced that it has raised a $9.15 million Series A round led by Benchmark, with participation from GV. In addition, the company also today said that its service is now available as a public beta.
The company was co-founded by Zain Asgar (CEO), a former Google engineer working on Google AI and adjunct professor at Stanford, and Ishan Mukherjee (CPO), who led Apple’s Siri Knowledge Graph product team and also previously worked on Amazon’s Robotics efforts. Asgar had originally joined Benchmark to work on developer tools for machine learning. Over time, the idea changed to using machine learning to power tools to help developers manage large-scale deployments instead.
“We saw data systems, this move to the edge, and we felt like this old cloud 1.0 model of manually collecting data and shipping it to databases in the cloud seems pretty inefficient,” Mukherjee explained. “And the other part was: I was on call. I got gray hair and all that stuff. We felt like we could build this new generation of developer tools and get to Michael Jordan’s vision of intelligent augmentation, which is giving creatives tools where they can be a lot more productive.”
Image Credits: Pixie
The team argues that most competing monitoring and observability systems focus on operators and IT teams — and often involve a long manual setup process. But Pixie wants to automate most of this manual process and build a tool that developers want to use.
Pixie runs inside a developer’s Kubernetes platform and developers get instant and automatic visibility into their production environments. With Pixie, which the team is making available as a freemium SaaS product, there is no instrumentation to install. Instead, the team uses relatively new Linux kernel techniques like eBPF to collect data right at the source.
“One of the really cool things about this is that we can deploy Pixie in about a minute and you’ll instantly get data,” said Asgar. “Our goal here is that this really helps you when there are cases where you don’t want your business logic to be full of monitoring code, especially if you forget something — when you have an outage.”
Image Credits: Pixie
At the core of the developer experience is what the company calls “Pixie scripts.” Using a Python-like language (PxL), developers can codify their debugging workflows. The company’s system already features a number of scripts written by the team itself and the community at large. But as Asgar noted, not every user will write scripts. “The way scripts work, it’s supposed to capture human knowledge in that problem. We don’t expect the average user — or even the way-above-average developer — ever to touch a script or write one. They’re just going to use it in a specific scenario,” he explained.
Looking ahead, the team plans to make these scripts and the scripting language more robust and usable to allow developers to go from passively monitoring their systems to building scripts that can actively take actions on their clusters based on the monitoring data the system collects.
“Zain and Ishan’s provocative idea was to move software monitoring to the source,” said Eric Vishria, general partner at Benchmark. “Pixie enables engineering teams to fundamentally rethink their monitoring strategy as it presents a vision of the future where we detect anomalous behavior and make operational decisions inside the infrastructure layer itself. This allows companies of all sizes to monitor their digital experiences in a more responsive, cost-effective and scalable manner.”
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Google takes aim at ‘beauty filters’ with design changes coming to Pixel phones
Google is taking aim at photo face filters and other “beautifying” techniques that mental health experts believe can warp a person’s self-confidence, particularly when they’re introduced to younger users. The company says it will now rely on expert guidance when applying design principles for photos filters used by the Android Camera app on Pixel smartphones. In the Pixel 4a, Google has already turned off face retouching by default, it says, and notes the interface will soon be updated to include what Google describes as “value-free” descriptive icons and labels for the app’s face retouching effects.
That means it won’t use language like “beauty filter” or imply, even in more subtle ways, that face retouching tools can make someone look better. These changes will also roll out to the Android Camera app in other Pixel smartphones through updates.
The changes, though perhaps unnoticed by the end user, can make a difference over time.
Google says that more than 70% of photos on Android are shot with the front-facing camera and over 24 billion photos have been labeled as “selfies” in Google Photos.
Image Credits: Google
But the images our smartphones are showing us are driving more people to be dissatisfied with their own appearance. According to the American Academy of Facial Plastic and Reconstructive Surgery, 72% of their members last year said their patients sought them out in order to improve their selfies, a 15% year-over-year increase. In addition, 80% of parents said they’re worried about filters’ impact and two-thirds of teens said they’ve been bullied over how they look in photos.
Google explains it sought the help of child and mental health experts to better understand the impact of filters on people’s well-being. It found that when people weren’t aware a photo filter had been applied, the resulting photos could negatively impact mental well-being as they quietly set a beauty standard that people would then compare themselves against over time.
Image Credits: Google
In addition, filters that use terminology like “beauty,” “beautification,” “enhancement” and “touch up” imply there’s something wrong with someone’s physical appearance that needs to be corrected. It suggests that the way they actually look is bad, Google explains. The same is true for terms like “slimming,” which imply a person’s body needs to be improved.
Google also found that even the icons used could contribute to the problem.
It’s often the case that face retouching filters will use “sparkling” design elements on the icon that switches the feature on. This suggests that using the filter is making your photo better.
To address this problem, Google will update to using value-neutral language for its filters, along with new icons.
Image Credits: Google
For example, instead of labeling a face retouching option as “natural,” it will relabel it to “subtle.” And instead of sparkling icons, it instead shows an icon of the face with an editing pen to indicate which button to push to enable the feature.
Adjustment levels will also follow new guidelines, and use either numbers and symbols or simple terms like “low” and “high,” rather than those that refer to beauty.
Image Credits: Google
Google says the Camera app, too, should also make it obvious when a filter has been enabled — both in the real-time capture and afterwards. For example, an indicator at the top of the screen could inform the user when a filter has been turned on, so users know their image is being edited.
In Pixel smartphones, starting with the Pixel 4a, when you use face retouching effects, you’ll be shown more information about how each setting is being applied and what specific changes it will make to the image. For instance, if you choose the “subtle” effect, it will explain that it adjusts your skin texture, under-eye tone and eye brightness. Being transparent about the effects applied can help to demystify the sometimes subtle tweaks that face retouching filters are making to our photos.
Face retouching will also be shut off in the new Pixel devices announced on Wednesday, including the Pixel 4a 5G and Pixel 5. And the changes to labels and descriptions are coming to Pixel phones through an upcoming update, Google says, which will support Pixel 2 and later devices.
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