Video
Auto Added by WPeMatico
Auto Added by WPeMatico
VSCO, the popular photo and video editing app, today announced it has acquired AI-powered video editing app Trash, as the company pushes further into the video market. The deal will see Trash’s technology integrated into the VSCO app in the months ahead, with the goal of making it easier for users to creatively edit their videos.
Trash, which was co-founded by Hannah Donovan and Genevieve Patterson, cleverly uses artificial intelligence technology to analyze multiple video clips and identify the most interesting shots. It then stitches your clips together automatically to create a final product. In May, Trash added a feature called Styles that let users pick the type of video they wanted to make — like a recap, a narrative, a music video or something more artsy.
After Trash creates its AI-powered edit, users can opt to further tweak the footage using buttons on the screen that let them change the order of the clips, change filters, adjust the speed or swap the background music.
Image Credits: Trash
With the integration of Trash’s technology, VSCO envisions a way to make video editing even more approachable for newcomers, while still giving advanced users tools to dig in and do more edits, if they choose. As VSCO co-founder and CEO Joel Flory explains, it helps users get from that “point zero of staring at their Camera Roll…to actually putting something together as fast as possible.”
“Trash gets you to the starting point, but then you can dive into it and tweak [your video] to really make it your own,” he says.
The first feature to launch from the acquisition will be support for multi-clip video editing, expected in a few months. Over time, VSCO expects to roll out more of Trash’s technologies to its user base. As users make their video edits, they may also be able to save their collection of tweaks as “recipes,” like VSCO currently supports for photos.
“Trash brings to VSCO a deep level of personalization, machine learning and computer vision capabilities for mobile that we believe can power all aspects of creation on VSCO, both now and for future investments in creativity,” says Flory.
The acquisition is the latest in a series of moves VSCO has made to expand its video capabilities.
At the end of 2019, VSCO picked up video technology startup Rylo. A few months later, it had leveraged the investment to debut Montage, a set of tools that allowed users to tell longer video stories using scenes, where they could also stack and layer videos, photos, colors and shapes to create a collage-like final product. The company also made a change to its app earlier this year to allow users to publish their videos to the main VSCO feed, which had previously only supported photos.
More recently, VSCO has added new video effects, like slowing down, speeding up or reversing clips and new video capture modes.
As with its other video features, the new technology integrations from Trash will be subscriber-only features.
Today, VSCO’s subscription plan costs $19.99 per year, and provides users with access to the app’s video editing capabilities. Currently, more than 2 million of VSCO’s 100 million+ registered users are paid subscribers. And, as a result of the cost-cutting measures and layoffs VSCO announced earlier this year, the company has now turned things around to become EBITDA positive in the second half of 2020. The company says it’s on the path to profitability, and additional video features like those from Trash will help.
Image Credits: Trash
VSCO’s newer focus on video isn’t just about supporting VSCO’s business model, however, it’s also about positioning the company for the future. While the app grew popular during the Instagram era, today’s younger users are more often posting videos to TikTok instead. According to Apple, TikTok was the No. 2 most downloaded free app of the year — ahead of Instagram, Facebook and Snapchat.
Though VSCO doesn’t necessarily envision itself as only a TikTok video prep tool, it does have to consider that growing market. Similar to TikTok, VSCO’s user base consists of a younger, Gen Z demographic; 75% of VSCO’s user base is under 25, for example, and 55% of its subscribers are also under 25. Combined, its user base creates more than 8 million photos and videos per day, VSCO says.
As a result of the acquisition, Trash’s standalone app will shut down on December 18.
Donovan will join VSCO as Director of Product and Patterson as Head of Applied Research. Other Trash team members, including Karina Bernacki, Chihyu Chang and Drew Olbrich, will join as Chief of Staff, Engineering Manager and Sr. Software Engineer for iOS, respectively.
“We both believe in the power of creativity to have a healthy and positive impact on people’s lives,” said Donovan, in Trash’s announcement. “Additionally, we have similar audiences of Gen Z casual creators; and are focused on giving people ways to express themselves and share their version of the world while feeling seen, safe, and supported,” she said.
Trash had raised a total of $3.3 million — a combination of venture capital and $500,000 in grants — from BBG, Betaworks, Precursor and Dream Machine, as well as the National Science Foundation. (Multiple TechCrunch connections here: BBG is backed by our owner Verizon Media, while Dream Machine is the fund created by former TechCrunch editor Alexia Bonatsos.)
“Han and Gen and the Trash team have always paid attention to the needs of creators first and foremost. My hope is that the VSCO and Trash partnership will turn all of us into creators, and turn the gigabytes of latent videos on our phones from trash to treasures,” said Bonatsos, in a statement about the deal.
Flory declined to speak to the deal price, but characterized the acquisition as a “win-win for both the Trash team and for VSCO.”
Updated 12/3/20, 11:27 AM ET: VSCO alerted us that Patterson’s title is being updated to “Head of Applied Research.” We’ve updated the article accordingly.
Powered by WPeMatico
Video has worked the same way for a long, long time. And because of its unique qualities, video has been largely immune to the machine learning explosion upending industry after industry. WaveOne hopes to change that by taking the decades-old paradigm of video codecs and making them AI-powered — while somehow avoiding the pitfalls that would-be codec revolutionizers and “AI-powered” startups often fall into.
The startup has until recently limited itself to showing its results in papers and presentations, but with a recently raised $6.5M seed round, they are ready to move towards testing and deploying their actual product. It’s no niche: video compression may seem a bit in the weeds to some, but there’s no doubt it’s become one of the most important processes of the modern internet.
Here’s how it’s worked pretty much since the old days when digital video first became possible. Developers create a standard algorithm for compressing and decompressing video, a codec, which can easily be distributed and run on common computing platforms. This is stuff like MPEG-2, H.264, and that sort of thing. The hard work of compressing a video can be done by content providers and servers, while the comparatively lighter work of decompressing is done on the end user’s machines.
This approach is quite effective, and improvements to codecs (which allow more efficient compression) have led to the possibility of sites like YouTube. If videos were 10 times bigger, YouTube would never have been able to launch when it did. The other major change was beginning to rely on hardware acceleration of said codecs — your computer or GPU might have an actual chip in it with the codec baked in, ready to perform decompression tasks with far greater speed than an ordinary general-purpose CPU in a phone. Just one problem: when you get a new codec, you need new hardware.
But consider this: many new phones ship with a chip designed for running machine learning models, which like codecs can be accelerated, but unlike them the hardware is not bespoke for the model. So why aren’t we using this ML-optimized chip for video? Well, that’s exactly what WaveOne intends to do.
I should say that I initially spoke with WaveOne’s cofounders, CEO Lubomir Bourdev and CTO Oren Rippel, from a position of significant skepticism despite their impressive backgrounds. We’ve seen codec companies come and go, but the tech industry has coalesced around a handful of formats and standards that are revised in a painfully slow fashion. H.265, for instance, was introduced in 2013, but years afterwards its predecessor, H.264, was only beginning to achieve ubiquity. It’s more like the 3G, 4G, 5G system than version 7, version 7.1, etc. So smaller options, even superior ones that are free and open source, tend to get ground beneath the wheels of the industry-spanning standards.
This track record for codecs, plus the fact that startups like to describe practically everything is “AI-powered,” had me expecting something at best misguided, at worst scammy. But I was more than pleasantly surprised: In fact WaveOne is the kind of thing that seems obvious in retrospect and appears to have a first-mover advantage.
The first thing Rippel and Bourdev made clear was that AI actually has a role to play here. While codecs like H.265 aren’t dumb — they’re very advanced in many ways — they aren’t exactly smart, either. They can tell where to put more bits into encoding color or detail in a general sense, but they can’t, for instance, tell where there’s a face in the shot that should be getting extra love, or a sign or trees that can be done in a special way to save time.
But face and scene detection are practically solved problems in computer vision. Why shouldn’t a video codec understand that there is a face, then dedicate a proportionate amount of resources to it? It’s a perfectly good question. The answer is that the codecs aren’t flexible enough. They don’t take that kind of input. Maybe they will in H.266, whenever that comes out, and a couple years later it’ll be supported on high-end devices.
So how would you do it now? Well, by writing a video compression and decompression algorithm that runs on AI accelerators many phones and computers have or will have very soon, and integrating scene and object detection in it from the get-go. Like Krisp.ai understanding what a voice is and isolating it without hyper-complex spectrum analysis, AI can make determinations like that with visual data incredibly fast and pass that on to the actual video compression part.
Variable and intelligent allocation of data means the compression process can be very efficient without sacrificing image quality. WaveOne claims to reduce the size of files by as much as half, with better gains in more complex scenes. When you’re serving videos hundreds of millions of times (or to a million people at once), even fractions of a percent add up, let alone gains of this size. Bandwidth doesn’t cost as much as it used to, but it still isn’t free.
Understanding the image (or being told) also lets the codec see what kind of content it is; a video call should prioritize faces if possible, of course, but a game streamer may want to prioritize small details, while animation requires yet another approach to minimize artifacts in its large single-color regions. This can all be done on the fly with an AI-powered compression scheme.
There are implications beyond consumer tech as well: A self-driving car, sending video between components or to a central server, could save time and improve video quality by focusing on what the autonomous system designates important — vehicles, pedestrians, animals — and not wasting time and bits on a featureless sky, trees in the distance, and so on.
Content-aware encoding and decoding is probably the most versatile and easy to grasp advantage WaveOne claims to offer, but Bourdev also noted that the method is much more resistant to disruption from bandwidth issues. It’s one of the other failings of traditional video codecs that missing a few bits can throw off the whole operation — that’s why you get frozen frames and glitches. But ML-based decoding can easily make a “best guess” based on whatever bits it has, so when your bandwidth is suddenly restricted you don’t freeze, just get a bit less detailed for the duration.
These benefits sound great, but as before the question is not “can we improve on the status quo?” (obviously we can) but “can we scale those improvements?”
“The road is littered with failed attempts to create cool new codecs,” admitted Bourdev. “Part of the reason for that is hardware acceleration; even if you came up with the best codec in the world, good luck if you don’t have a hardware accelerator that runs it. You don’t just need better algorithms, you need to be able to run them in a scalable way across a large variety of devices, on the edge and in the cloud.”
That’s why the special AI cores on the latest generation of devices is so important. This is hardware acceleration that can be adapted in milliseconds to a new purpose. And WaveOne happens to have been working for years on video-focused machine learning that will run on those cores, doing the work that H.26X accelerators have been doing for years, but faster and with far more flexibility.
Of course, there’s still the question of “standards.” Is it very likely that anyone is going to sign on to a single company’s proprietary video compression methods? Well, someone’s got to do it! After all, standards don’t come etched on stone tablets. And as Bourdev and Rippel explained, they actually are using standards — just not the way we’ve come to think of them.
Before, a “standard” in video meant adhering to a rigidly defined software method so that your app or device could work with standards-compatible video efficiently and correctly. But that’s not the only kind of standard. Instead of being a soup-to-nuts method, WaveOne is an implementation that adheres to standards on the ML and deployment side.
They’re building the platform to be compatible with all the major ML distribution and development publishers like TensorFlow, ONNX, Apple’s CoreML, and others. Meanwhile the models actually developed for encoding and decoding video will run just like any other accelerated software on edge or cloud devices: deploy it on AWS or Azure, run it locally with ARM or Intel compute modules, and so on.
It feels like WaveOne may be onto something that ticks all the boxes of a major b2b event: it invisibly improves things for customers, runs on existing or upcoming hardware without modification, saves costs immediately (potentially, anyhow) but can be invested in to add value.
Perhaps that’s why they managed to attract such a large seed round: $6.5 million, led by Khosla Ventures, with $1M each from Vela Partners and Incubate Fund, plus $650K from Omega Venture Partners and $350K from Blue Ivy.
Right now WaveOne is sort of in a pre-alpha stage, having demonstrated the technology satisfactorily but not built a full-scale product. The seed round, Rippel said, was to de-risk the technology, and while there’s still lots of R&D yet to be done, they’ve proven that the core offering works — building the infrastructure and API layers comes next and amounts to a totally different phase for the company. Even so, he said, they hope to get testing done and line up a few customers before they raise more money.
The future of the video industry may not look a lot like the last couple decades, and that could be a very good thing. No doubt we’ll be hearing more from WaveOne as it migrates from lab to product.
Powered by WPeMatico
When Zoom announced Zapps last month — the name has since been wisely changed to Zoom Apps — VC Twitter immediately began speculating that Zoom could make the leap from successful video conferencing service to becoming a launching pad for startup innovation. It certainly caught the attention of former TechCrunch writer and current investor at Signal Fire Josh Constine, who tweeted that “Zoom’s new ‘Zapps’ app platform will crush or king-make lots of startups.”
As Zoom usage exploded during the pandemic and it became a key tool for business and education, the idea of using a video conferencing platform to build a set of adjacent tooling makes a lot of sense. While the pandemic will come to an end, we have learned enough about remote work that the need for tools like Zoom will remain long after we get the all-clear to return to schools and offices.
We are already seeing promising startups like Mmhmm, Docket and ClassEdu built with Zoom in mind, and these companies are garnering investor attention. In fact, some investors believe Zoom could be the next great startup ecosystem.
Salesforce paved the way for Zoom more than a decade ago when it opened up its platform to developers and later launched the AppExchange as a distribution channel. Both were revolutionary ideas at the time. Today we are seeing Zoom building on that.
Jim Scheinman, founding managing partner at Maven Ventures and an early Zoom investor (who is credited with naming the company) says he always saw the service as potentially a platform play. “I’ve been saying publicly, before anyone realized it, that Zoom is the next great open platform on which to build billion-dollar businesses,” Scheinman told me.
He says he talked with Zoom leadership about opening up the platform to external developers several years ago before the IPO. It wasn’t really a priority at that point, but COVID-19 pushed the idea to the forefront. “Post-IPO and COVID, with the massive growth of Zoom on both the enterprise and consumer side, it became very clear that an app marketplace is now a critical growth area for Zoom, which creates a huge opportunity for nascent startups to scale,” he said.
Jason Green, founder and managing director at Emergence Capital (another early investor in Zoom and Salesforce) agreed: “Zoom believes that adding capabilities to the core Zoom platform to make it more functional for specific use cases is an opportunity to build an ecosystem of partners similar to what Salesforce did with AppExchange in the past.”
Before a platform can succeed with developers, it requires a critical mass of users, a bar that Zoom has clearly passed. It also needs a set of developer tools to connect to the various services on the platform. Then the substantial user base acts as a ready market for the startup. Finally, it requires a way to distribute those creations in a marketplace.
Zoom has been working on the developer components and brought in industry veteran Ross Mayfield, who has been part of two collaboration startups in his career, to run the developer program. He says that the Zoom Apps development toolset has been designed with flexibility to allow developers to build applications the way that they want.
For starters, Zoom has created WebViews, a way to embed functionality into an application like Zoom. To build WebViews in Zoom, the company created a JS Kit, which in combination with existing Zoom APIs enables developers to build functionality inside the Zoom experience. “So we’re giving developers a lot of flexibility in what experience they create with WebViews plus using our very rich set of API’s that are part of the existing platform and creating some new API’s to create the experience,” he said.
Powered by WPeMatico
There’s no shortage of TikTok coverage in the news today as the app’s fate in the U.S. hangs in the air.
What the press doesn’t always address is how TikTok gets here — how did a Chinese startup seize the lucrative short-video market in the West before Google and Facebook? What did it do differently from its Chinese predecessors who tried global expansion to little avail? Matthew Brennan’s new book “Attention Factory” set out to answer these questions by tracing ByteDance’s trajectory from an underdog despised by Chinese tech workers and investors to the envy of Silicon Valley and the target of the White House.
Matthew has spent years working closely with China’s tech firms, not only analyzing them but also using their products as a curious local, experiences that informed his meticulously researched and entertaining book. Interwoven with captivating anecdotes of TikTok, rare photos of ByteDance’s original team, incisive analysis and telling infographics, “Attention Factory” is an essential read for those looking to understand how ideas in the American and Chinese internet worlds collided, coincided and converged throughout the 2010s.
TikTok is a rare example of a Chinese internet service that has gained worldwide success. Before expanding overseas, ByteDance had already proven the short-video model in China through Douyin, the homegrown version of TikTok.
The excerpt below follows a high-growth period of Douyin, detailing how it gained around 200 million daily active users within a year: a loyal creator community, viral memes, algorithmic recommendation and aggressive ad spending.
Before long, the Chinese startup would replicate that growth playbook in the rest of the world, tweaking it here and there to make it work.
Hundreds of fashionably dressed young people were arriving at 751 D.PARK, an expanse of industrial plants redeveloped into a hip culture venue in northeast Beijing. They were clad in baseball caps, brightly colored dresses, loose-fitting hip-hop style streetwear and limited-edition sneakers. The site had been transformed into something akin to the stage of the talent competition “American Idol,” spanning two floors filled with strobe lighting, high-volume music and trendy backdrops. This was an exclusive party — three hundred top Douyin creators coming together to celebrate the app’s one-year anniversary.
The online stars, billed as the “new generation of internet celebrities,” weren’t there to just socialize and enjoy themselves. Every influencer was aware of the unspoken competition to derive the best content from that night. They were all fighting to achieve a higher level of superstardom and the medium of battle was short video.
The influencers who knew each other gathered in small groups as their assistants tirelessly captured fifteen-second videos of their carefully crafted skits. Loners roamed around the dance floor, absorbed in finding the ideal lighting for their lip-syncing selfie videos. Lesser-known influencers nervously approached more famous ones, proposing to record a dance together to potentially tap into their peers’ following. Loud hip-hop music kept playing in the background as creators hurried to touch up the videos they had just shot. Once the editing was done, they uploaded their works and anxiously waited for the app’s algorithms to judge who would grab more eyeballs.
Dance teams took to the stage to display their skills. The crowd bopped their heads back and forth as rappers attempted to impress with clever lyrics. Later as the hosts were midway through giving out awards, a wave of noise erupted from the back of the crowd interrupting the proceedings.
It was Yiming. Dressed in a black baseball cap and gray T-shirt and accompanied by Lidong. The audience went wild — the CEO had decided to drop in unannounced! Immediately he was bombarded with requests to take pictures and videos. As those around him whooped and cried out wildly, the entrepreneur simply smiled and kept his hands calmly by his side, an awkward 34-year-old engineer type among the hyper fashionable, mostly teenage hip-hop crowd.
Yiming and Lidong appear at a Douyin promotional event marking the app’s first anniversary in Sept 2017.
He already knew from looking at the data, but this was confirmation in the flesh — Douyin had built a robust community, with powerful momentum and was on the verge of doing something special.
October 1st marks the beginning of “Golden Week,” a seven-day-long official Chinese national holiday. Periods like these are big opportunities for China’s internet industry. People’s behaviors change for a week; many find more time for entertainment and to try new things.
Over October, Douyin’s daily users doubled from seven to 14 million; two months later, they reached 30 million. Over those three months, the 30-day retention rates jumped from eight to over 20%, the average time spent in the app soared from 20 to 40 minutes. It was as if some magic rocket fuel had suddenly been added, boosting every key metric. What had changed?
The answer was Zhu Wenjia. Zhu Wenjia, hired from Baidu in 2015, was widely considered to be one of the top-three best people in the entire company when it came to algorithm technology. He ran one of ByteDance’s most capable engineering teams and had recently been assigned to work on Douyin. The team’s work harnessing the full power of ByteDance’s content recommendation back end led directly to the astounding October results.
The better the metrics, the more resources ByteDance placed behind the app as it now had good retention and was fast-tracked into becoming a strategically important product. Suddenly support was coming in from all over the company — people, money, user traffic, celebrity endorsements, brand collaborations, and most importantly, full integration and optimization of ByteDance’s powerful recommendation engine. Chinese stars with massive fan bases such as Yang Mi, Lu Han, Kris Wu, and Angelababy opened accounts, joining in publicity campaigns, and a nationwide “Douyin Party” event roadshow was planned. Douyin had become the hottest upcoming app in China.
ByteDance ramped up the investment in all three short-video products, including Douyin. People, resources and advertising budget were all raised, leading an industry insider to comment later: “The sudden rise of Douyin wasn’t without good cause. Yiming threw more money at this than anyone and dared to hunt down and grab the best people.”
Commercialization began with the first three brand ad campaigns paid for by Airbnb, Harbin Beer and Chevrolet. Douyin’s advertising business would soon make rapid progress. ByteDance already had hundreds of sales and marketing staff who would shortly be able to add Douyin’s advertisement inventory to their sales targets.
Yiming revealed in a later interview that the company had made it compulsory for everyone on the management team to make their own Douyin videos with goals to gain a certain number of likes or suffer forfeits such as doing push-ups. It wasn’t good enough to just look at charts and data; management needed to understand short videos from a creator’s perspective also. Yiming had watched Douyin videos for a long time but creating his own was “a big step for me,” he admitted.
Yiming’s personal Douyin account (3277469). Seventeen videos at the time of writing, including clips from his global travels.
The video opened to a young woman yawning, dressed in pajamas with messy morning hair. Wearing glasses and with no signs of makeup, she casually lip-syncs the line, “Oh well … karma’s a bitch” and throws a silk scarf into the air. Suddenly loud background music explosively begins. In an instant, she transforms into a glamorous fashion model, almost unrecognizable from a second before. A new meme had taken hold of Douyin.
“Karma’s a bitch” was a new version of the original “Don’t judge me” challenge that had propelled Musical.ly to top the U.S. app store three years earlier. The meme was another breakthrough for Douyin; People loved watching the shocking transformations. Compilations of the meme’s videos started popping up online. In particular, the makeup skills of some women left many men in disbelief. “Karma’s a bitch” left an impact on mainstream culture and gained widespread recognition and publicity, even making waves out into English language global media.
Douyin was also increasingly hypercharging the popularity of catchy pop songs with strong hooks. In late 2017, a track known as the “Ci-li-ci-li song” exploded on Douyin. The song’s catchy energy was undeniably infectious. Yet, it was the novel set of dance moves that had become associated with the track’s hook that turned the music into a meme and dramatically amplified its success.
The track had actually been released back in 2013 by Romanian reggae and dancehall artist Matteo, under the name “Panama.” Four years after its debut, the song’s unexpected and explosive spike in popularity led the singer to hastily organize an Asia tour to capitalize on his track’s sudden fame. A YouTube video shows him meeting Chinese fans at the Hangzhou airport who demonstrate their moves to him in the arrivals hall. With the dance having been created entirely in China, the bewildered artist finds himself in the awkward situation of not knowing how to follow the moves to the song for which he is famous.
Perhaps the most reliable indicator of the platform’s increasing influence on society was how the name, Douyin, had started to enter everyday colloquial vernacular, becoming synonymous with short video. The meaning of “Let’s shoot a Douyin!” needed no explanation.
ByteDance knew they now had a winning formula. Retention was good, word of mouth was excellent, a large, vibrant community of video creators had been fostered. The recommendation engine was doing its job of surfacing the best content. Douyin’s fire was already burning bright; now, it was time to pour gasoline on things and spend, spend, spend.
The holiday week of Chinese New Year is another unique annual opportunity for app promotions. Hundreds of millions travel home to be reunited with their families and find themselves with free time to relax. An entertainment app like Douyin was the perfect way to pass the time; word of mouth spread naturally between family members.
To step up its efforts further, Douyin directly gave out money to users by running a Chinese New Year “lucky money” campaign. Users could collect small cash amounts in special videos by tapping on the “red packet” icons — a digital manifestation of cash-filled envelopes people give to each other during the holiday. ByteDance also went all out, spending wildly, buying adverts and promotions across major online channels to acquire users, spending about 4 million yuan a day (over half a million dollars). The combination of all these effects sent Douyin to the top of the Chinese app store charts. Various reports stated Douyin’s daily users jumped from around 40 to 70 million over the February to March period covering Chinese New Year, with some of the top accounts seeing their follower numbers quadruple.
A chart mapping the progress of Douyin, from zero to 200 million daily active users, during the first two years of operation.
This article is an excerpt from “Attention Factory: The Story of TikTok and China’s ByteDance,” which was written by Matthew Brennan and edited by TechCrunch reporter Rita Liao, who wrote the introduction to this post.
Powered by WPeMatico
Netflix already borrowed the concept of short-form video “Stories” from social apps like Snapchat and Instagram for its Previews feature back in 2018. Now, the company is looking to the full-screen vertical video feed, popularized by TikTok, for further inspiration. With its latest experiment, Fast Laughs, Netflix is offering a new feed of short-form comedy clips drawn from its full catalog.
The feed includes clips from both originals and licensed programming, Netflix says. It also includes video clips from the existing Netflix social channel, “Netflix Is A Joke,” which today runs clips, longer videos and other social content across YouTube, Twitter, Facebook and Instagram.
Fast Laughs resembles TikTok in the sense that it’s swiped through vertically, offers full-screen videos and places its engagement buttons on the right side. But it’s not trying to become a place to waste time while being entertained.
Like many of Netflix’s experiments, the goal with the Fast Laughs feed is to help users discover something new to watch.
Instead of liking and commenting on videos, as you would in a social video app, the feed is designed to encourage users to add shows to their Netflix watch list for later viewing. In this sense, it’s serving a similar purpose to Netflix’s “Previews” feature, which helps users discover shows by watching clips and trailers from popular and newly released programming.
As users scroll through the new Fast Laughs feed, they’ll encounter a wide range of comedy clips — like a clip from a Kevin Hart stand-up special or a funny bit from “The Office,” for example. The clips will also range in length anywhere from 15 to 45 seconds.
In addition to adding clips to Netflix’s “My List” feature, users can also react to clips with a laughing emoji button, share the clip with friends across social media, or tap a “More” button to see other titles related to the clip you’re viewing.
The feature was first spotted by social media consultant Matt Navarra, based in the U.K. In his app, Fast Laughs appeared in front of the row of Previews, where it was introduced with text that said “New!”
Netflix confirmed to TechCrunch the experiment had been tested with a small number of users earlier this year, but has recently started rolling out to a wider group this month — including users in the U.K., the U.S. and other select markets.
It’s currently available to a subset of Netflix users with adult profiles or other profiles without parental controls on iOS devices only. However, users don’t need to be opted in to experiments nor do they need to be on a beta version of the Netflix app to see the feature. It’s more of a standard A/B test, Netflix says.
And because it’s a test, users may see slightly different versions of the same feature. The product may also evolve over time, in response to user feedback.
Netflix is hardly the first to “borrow” the TikTok format for its own app. Social media platforms, like Instagram and Snapchat, have also launched their own TikTok rivals in recent months.
But Netflix isn’t a direct competitor with TikTok — except to the extent that any mobile app competes for users’ time and attention, as there are only so many hours in a day.
Instead, the new feed is more of an acknowledgment that the TikTok format of a full-screen vertical video feed with quick engagement buttons on the side is becoming a default style of sorts for presenting entertaining content.
“We’re always looking for new ways to improve the Netflix experience,” a Netflix spokesperson said, confirming the experiment. “A lot of our members love comedy so we thought this would be an exciting new way to help them discover new shows and enjoy classic scenes. We experiment with these types of tests in different countries and for different periods of time — and only make them broadly available if people find them useful,” they added.
Powered by WPeMatico
Instagram is adapting to the way creators have been using its service during the coronavirus pandemic. With individuals and businesses now limited from hosting in-person events — like concerts, classes, meetups, and more — users have turned to Instagram to live stream instead. Today, the company says it’s significantly expanding the time limit for these streams, from 1 hour to now 4 hours for all users worldwide.
The change, the company explains, is meant to help those who’ve had to pivot to virtual events, like yoga and fitness instructors, teachers, musicians, artists and activists, among others. During the height of government lockdowns in the U.S., Instagram Live became a place for people to gather as DJ’s hosted live sets, artists played their music for fans, celebs hosted live talk shows, workout enthusiasts joined live classes, and more. Live usage had then jumped 70% over pre-coronavirus numbers in the U.S. as people connected online.
Many of these Instagram Live creators had wanted to extend their sessions beyond the 60 minute time limit without an interruption.
The change puts Instagram on par with the time limits offered by Facebook for live streams from mobile devices, which is also 4 hours. (If live streaming from a desktop computer or via an API, the Facebook time limit expands to 8 hours.)
While the longer time limit is opening up to all creators worldwide starting today, Instagram says the creator’s account has to be “good standing” in order to take advantage. That means the account can’t have a history of either intellectual property or policy violations.
Related to this change, Instagram will also update the “Live Now” section in IGTV and at the end of live streams to help direct users to more live content.
Instagram also today pre-announced another feature which has yet to arrive.
It says that it will “soon” add an option that will allow creators to archive their live streams for up to 30 days.
Image Credits: Instagram
Before, users could archive their Feed posts or their Stories to a private archive, but the only way to save a live stream was to publish it to IGTV immediately after the stream, through a feature introduced in May.
The company says the new option to archive live broadcasts will mirror the existing archive experience for Stories and Feed Posts.
The difference is that archived live videos will be permanently deleted after 30 days.
But up until that time, the creator has the option to return to the video to save it or download it. This would allow the creator to publish the video on other social platforms, like Facebook or YouTube, or even trim out key parts for short-form video platforms, like TikTok. The Archive feature also means if a creator’s Live stream crashes for some reason — or if the creator forgot to download it in the moment — it can still be downloaded later on.
The news follows another recent Instagram update which introduced a new way for creators to monetize their Live streams.
The company earlier this month began rolling out badges in Instagram Live to an initial group of over 50,000 creators who will test the feature by selling badges at price points of $0.99, $1.99, or $4.99. These badges help fans’ comments stand out in busy streams, allow fans to support a favorite creator, and places the fan’s name on the creator’s list of badge holders.
Powered by WPeMatico
Virtual meetings are a fundamental part of how we interact with each other these days, but even when (if!?) we find better ways to mitigate the effects of COVID-19, many think that they will be here to stay. That means there is an opportunity out there to improve how they work — because let’s face it, Zoom Fatigue is real and I for one am not super excited anymore to be a part of your Team.
Mmhmm, the video presentation startup from former Evernote CEO Phil Libin with ambitions to change the conversation (literally and figuratively) about what we can do with the medium — its first efforts have included things like the ability to manipulate presentation material around your video in real time to mimic newscasts — is today announcing an acquisition as it continues to home in on a wider launch of its product, currently in a closed beta.
It has acquired Memix, an outfit out of San Francisco that has built a series of filters you can apply to videos — either pre-recorded or streaming — to change the lighting, details in the background, or across the whole of the screen, and an app that works across various video platforms to apply those filters.
Like mmhmm, Memix is today focused on building tools that you use on existing video platforms — not building a video player itself. Memix today comes in the form of a virtual camera, accessible via Windows apps for Zoom, WebEx and Microsoft Teams; or web apps like Facebook Messenger, Houseparty and others that run on Chrome, Edge and Firefox.
Libin said in an interview that the plan will be to keep that virtual camera operating as is while it works on integrating the filters and Memix’s technology into mmhmm, while also laying the groundwork for building more on top of the platform.
Libin’s view is that while there are already a lot of video products and users in the market today, we are just at the start of it all, with technology and our expectations changing rapidly. We are shifting, he said, from wanting to reproduce existing experiences (like meetings) to creating completely new ones that might actually be better.
“There is a profound change in the world that we are just at the beginning of,” he said in an interview. “The main thing is that everything is hybrid. If you imagine all the experiences we can have, from in-person to online, or recorded to live, up to now almost everything in life fit neatly into one of those quadrants. The boundaries were fixed. Now all these boundaries have melted away we can rebuild every experience to be natively hybrid. This is a monumental change.”
That is a concept that the Memix founders have not just been thinking about, but also building the software to make it a reality.
“There is a lot to do,” said Pol Jeremias-Vila, one of the co-founders. “One of our ideas was to try to provide people who do streaming professionally an alternative to the really complicated set-ups you currently use,” which can involve expensive cameras, lights, microphones, stands and more. “Can we bring that to a user just with a couple of clicks? What can be done to put the same kind of tech you get with all that hardware into the hands of a massive audience?”
Memix’s team of two — co-founders Inigo Quilez and Pol Jeremias-Vila, Spaniards who met not in Spain but the Bay Area — are not coming on board full-time, but they will be helping with the transition and integration of the tech.
Libin said that he first became aware of Quilez from a YouTube video he’d posted on “The principles of painting with maths”, but that doesn’t give a lot away about the two co-founders. They are in reality graphic engineering whizzes, with Jeremias-Vila currently the lead graphics software engineer at Pixar, and Quilez until last year a product manager and lead engineer at Facebook, where he created, among other things, the Quill VR animation and production tool for Oculus.
Because working the kind of hours that people put in at tech companies wasn’t quite enough time to work on graphics applications, the pair started another effort called Beauty Pi (not to be confused with Beauty Pie), which has become a home for various collaborations between the two that had nothing to do with their day jobs. Memix had been bootstrapped by the pair as a project built out of that. Other efforts have included Shadertoy, a community and platform for creating Shaders (a computer program created to shade in 3D scenes).
That background of Memix points to an interesting opportunity in the world of video right now. In part because of all the focus (sorry not sorry!) on video right now as a medium because of our current pandemic circumstances, but also because of the advances in broadband, devices, apps and video technology, we’re seeing a huge proliferation of startups building interesting variations and improvements on the basic concept of video streaming.
Just in the area of videoconferencing alone, some of the hopefuls have included Headroom, which launched the other week with a really interesting AI-based approach to helping its users get more meaningful notes from meetings, and using computer vision to help presenters “read the room” better by detecting if people are getting bored, annoyed and more.
Vowel is also bringing a new set of tools not just to annotate meetings and their corresponding transcriptions in a better way, but to then be able to search across all your sessions to follow up items and dig into what people said over multiple events.
And Descript, which originally built a tool to edit audio tracks, earlier this week launched a video component, letting users edit visuals and what you say in those moving pictures, by cutting, pasting and rewriting a word-based document transcribing the sound from that video. All of these have obvious B2B angles, like mmhmm, and they are just the tip of the iceberg.
Indeed, the huge amount of IP out there is interesting in itself. Yet the jury is still out on where all of it would best live and thrive as the space continues to evolve, with more defined business models (and leading companies) only now emerging.
That presents an interesting opportunity not just for the biggies like Zoom, Google and Microsoft, but also players who are building entirely new platforms from the ground up.
Mmhmm is a notable company in that context. Not only does it have the reputation and inspiration of Libin behind it — a force powerful enough that even his foray into the ill-fated world of chatbots got headlines — but it’s also backed by the likes of Sequoia, which led a $31 million round earlier this month.
Libin said he doesn’t like to think of his startup as a consolidator, or the industry in a consolidation play, as that implies a degree of maturity in an area that he still feels is just getting started.
“We’re looking at this not so much as consolidation, which to me means market share,” he said. “Our main criteria is that we wanted to work with teams that we are in love with.”
Powered by WPeMatico
YouTube has long allowed its users to test new features and products before they go live to a wider audience. But in a recent change, YouTube’s latest series of experiments are being limited to those who subscribe to the Premium tier of YouTube’s service. Currently, paid subscribers are the only ones able to test several new product features, including one that allows iOS users to watch YouTube videos directly on the home screen.
This is not the same thing as the Picture-in-Picture option that’s become available to app developers with iOS 14, to be clear. Instead, YouTube says this feature allows users who are scrolling on their YouTube home page to watch videos with the sound on while they scroll through their feed.
Two other experiments are related to search. One lets you filter topics you search for by additional languages, including Spanish, French or Portuguese. The other lets you use voice search to pull up videos when using the Chrome web browser.
Image Credits: YouTube, screenshot via TechCrunch
None of these tests will be very lengthy, however. Two of the three new experiments wrap up on October 20, 2020 for example. The other wraps on October 27. And they’ve only been live for a few weeks.
In years past, YouTube had allowed all users to try out new features in development from a dedicated site dubbed “TestTube.” In more recent years, however, it began to use the website YouTube.com/new to direct interested users to upcoming features before they rolled out publicly. For example, when YouTube introduced its redesign in 2017, users could visit that same website to opt-in to the preview ahead of its launch.
Now, the site is being used to promote other limited-time tests.
YouTube says the option to test the features was highlighted to Premium subscribers a few weeks ago within the YouTube app. It’s also the first time that YouTube has run an experimentation program tied to the Premium service, we’re told.
The company didn’t make a formal public announcement, but the addition was just spotted by several blogs, including XDA Developers and Android Central, for example.
Contrary to some reports, however, it does not appear that YouTube’s intention is to close off all its experiments to anyone except its paid subscribers. The company’s own help documentation, in fact, notes this limitation will only apply to “some” of its tests.
YouTube also clarified to TechCrunch that the tests featured on the site represent only a “small minority” of those being run across YouTube. And they are not at all inclusive of the broader set of product experiments the company runs, according to the company.
In addition, non-Premium users can opt to sign up to be notified of additional opportunities to participate in other YouTube research studies, if they choose. This option appears at the bottom of the YouTube.com/new page.
YouTube says the goal with the new experiments is two-fold. It allows product teams to receive feedback on different features and it allows Premium subscribers to act as early testers, if they want to.
Premium users who choose to participate can opt into and out of the new features individually, but can only try one experiment at a time.
This could serve to draw more YouTube users to the Premium subscription, as there’s a certain amount of clout involved with being able to try out features and products ahead of the general public. Consider it another membership perk then — something extra on top of the baseline Premium tier features like ad-free videos, downloads, background play and more.
YouTube, which today sees more than 2 billion monthly users, said earlier this year it has converted at least 20 million users to a paid subscription service. (YouTube Premium / YouTube Music). As of Q3 2020, YouTube was the No. 3 largest app by consumer spend worldwide across iOS and Android, per App Annie data.
Powered by WPeMatico
While the coronavirus has accelerated the dealmaking pace for many early-stage startups, activity has not come without adaptation.
Remote investment struggles for investors were clear from the get go: it’s challenging to invest millions in someone you have never met, and there’s not a lot to learn from “off-the-cuff” conversations that are calendared days in advance. Some investors said the pandemic was forcing them to stick with people they know in categories where they have experience, limiting the network that one can push money into.
Over six months into a global pandemic, though, new techniques are emerging to address some of these woes. The very art of a deal, from due diligence to sourcing, is changing from a cultural and technological standpoint.
One of the new places that recreates informal bonding and camaraderie is Matchbox.VC, formerly Fortnite.VC.
The service connects founders and investors over video games to network and source deals in a low-stress environment. Matchbox.VC was inspired from a tweet by Founders Fund principal Delian Asparouhov and has garnered interest from investors like Arjun Sethi from Tribe Capital, Ryan Shea, the ex-founder of Blockstack, Jake Chapman from AlphafundVC and Peter Rojas from Betaworks. Its last game night was backed by Yac, Tribe Capital and Shrug Capital.
We’ve invested $14m total in the company and it’s off to the races, and is counter cyclical in a covid world so yeah
pretty pleased with my Fortnite sourcing thus far
— delian (@zebulgar) April 24, 2020
The pitch is simple: founders and investors sign up on the website, answer basic questions about their focus, company and stage before picking three game choices from eight options that include Fortnite, COD: Warzone and Valorant.
Powered by WPeMatico
For many investors, the coronavirus has effectively taken geography out of the equation when it comes to vetting new opportunities.
While this dynamic opens up startups to more investment opportunities, venture capital firms that focus on a specific region are in a thornier spot. The competitive advantage they once had when raising — the notion that they’re focused on an area no one else is — is potentially threatened.
Natasha Mascarenhas, Danny Crichton and Alex Wilhelm of the TechCrunch Equity crew discussed the future of geographic-focused funds given the uptick of remote investing:
Since 2014, Steve Case and his team have made an annual bus trip across the country to meet startups in emerging startup hubs. Five days, five cities and at least $500,000 of investment dollars given to startups. Case would even offer to fly out promising and hard-to-reach startups to have them join the trip.
The Rise of the Rest fund, with more than $300 million in assets under management, has invested in over 130 startups across 70 cities, including Austin, Chicago, Detroit, Los Angeles, New Orleans and Washington, D.C.
Powered by WPeMatico