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Veo raises $25M for AI-based cameras that record and analyze football and other team sports

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Sports have been among some of the most popular and lucrative media plays in the world, luring broadcasters, advertisers and consumers to fork out huge sums to secure the chance to watch (and sponsor) their favorite teams and athletes.

That content, unsurprisingly, also typically costs a ton of money to produce, narrowing the production and distribution funnel even more. But today, a startup that’s cracked open that model with an autonomous, AI -based camera that lets any team record, edit and distribute their games, is announcing a round of funding to build out its business targeting the long tail of sporting teams and fixtures.

Veo Technologies, a Copenhagen startup that has designed a video camera and cloud-based subscription service to record and then automatically pick out highlights of games, which it then hosts on a platform for its customers to access and share that video content, has picked up €20 million (around $24.5 million) in a Series B round of funding.

The funding is being led by Danish investor Chr. Augustinus Fabrikker, with participation from US-based Courtside VC, France’s Ventech and Denmark’s SEED Capital. Veo’s CEO and co-founder Henrik Teisbæk said in an interview that the startup is not disclosing its valuation, but a source close to funding tells me that it’s well over $100 million.

Teisbæk said that the plan will be to use to the funds to continue expanding the company’s business on two levels. First, Veo will be digging into expanding its US operations, with an office in Miami.

Second, it plans to continue enhancing the scope of its technology: The company started out optimising its computer vision software to record and track the matches for the most popular team sport in the world, football (soccer to US readers), with customers buying the cameras — which retail for $800 — and the corresponding (mandatory) subscriptions — $1,200 annually — both to record games for spectators, as well as to use the footage for all kinds of practical purposes like training and recruitment videos. The key is that the cameras can be set up and left to run on their own. Once they are in place, they can record using wide-angles the majority of a soccer field (or whatever playing space is being used) and then zoom and edit down based on that.

Veo on grass

Now, Veo is building the computer vision algorithms to expand that proposition into a plethora of other team-based sports including rugby, basketball and hockey, and it is ramping up the kinds of analytics that it can provide around the clips that it generates as well as the wider match itself.

Even with the slowdown in a lot of sporting activity this year due to Covid — in the UK for example, we’re in a lockdown again where team sports below professional leagues, excepting teams for disabled people, have been prohibited — Veo has seen a lot of growth.

The startup currently works with some 5,000 clubs globally ranging from professional sports teams through to amateur clubs for children, and it has recorded and tracked 200,000 games since opening for business in 2018, with a large proportion of that volume in the last year and in the US.

For a point of reference, in 2019, when we covered a $6 million round for Veo, the startup had racked up 1,000 clubs and 25,000 games, pointing to customer growth of 400% in that period.

The Covid-19 pandemic has indeed altered the playing field — literally and figuratively — for sports in the past year. Spectators, athletes, and supporting staff need to be just as mindful as anyone else when it comes to spreading the coronavirus.

That’s not just led to a change in how many games are being played, but also for attendance: witness the huge lengths that the NBA went to last year to create an extensive isolation bubble in Orlando, Florida, to play out the season, with no actual fans in physical seats watching games, but all games and fans virtually streamed into the events as they happened.

That NBA effort, needless to say, came at a huge financial cost, one that any lesser league would never be able to carry, and so that predicament has led to an interesting use case for Veo.

Pre-pandemic, the Danish startup was quietly building its business around catering to the long tail of sporting organizations who — even in the best of times — would be hard pressed to find the funds to buy cameras and/or hire videographers to record games, not just an essential part of how people can enjoy a sporting event, but useful for helping with team development.

“There is a perception that football is already being recorded and broadcast, but in the UK (for example) it’s only the Premier League,” Teisbæk said. “If you go down one or two steps from that, nothing is being recorded.” Before Veo, to record a football game, he added, “you need a guy sitting on a scaffold, and time and money to then cut that down to highlights. It’s just too cumbersome. But video is the best tool there is to develop talent. Kids are visual learners. And it’s a great way to get recruited sending videos to colleges.”

Those use cases then expanded with the pandemic, he said. “Under cornavirus rules, parents cannot go out and watch their kids, and so video becomes a tool to follow those matches.”

‘We’re a Shopify, not an Amazon’

The business model for Veo up to now has largely been around what Teisbæk described as “the long tail theory”, which in the case of sports works out, he said, as “There won’t be many viewers for each match, but there are millions of matches out there.” But if you consider how a lot of high school sports will attract locals beyond those currently attached to a school — you have alumni supporters and fans, as well as local businesses and neighborhoods — even that long tail audience might be bigger than one might imagine.

Veo’s long-tail focus has inevitably meant that its target users are in the wide array of amateur or semi-pro clubs and the people associated with them, but interestingly it has also spilled into big names, too.

Veo’s cameras are being used by professional soccer clubs in the Premier League, Spain’s La Liga, Italy’s Serie A and France’s Ligue 1, as well as several clubs in the MLS such as Inter Miami, Austin FC, Atlanta United and FC Cincinnati. Teisbæk noted that while this might never be for primary coverage, it’s there to supplement for training and also be used in the academies attached to those organizations.

The plan longer term, he said, is not to build its own media empire with trove of content that it has amassed, but to be an enabler for creating that content for its customers, who can in turn use it as they wish. It’s a “Shopify, not an Amazon,” said Teisbæk.

“We are not building the next ESPN, but we are helping the clubs unlock these connections that are already in place by way of our technology,” he said. “We want to help help them capture and stream their matches and their play for the audience that is there today.”

That may be how he views the opportunity, but some investors are already eyeing up the bigger picture.

Vasu Kulkarni, a partner at Courtside VC — a firm that has focused (as its name might imply) on backing a lot of different sports-related businesses, with The Athletic, Beam (acquired by Microsoft), and many others in its portfolio — said that he’d been looking to back a company like Veo, building a smart, tech-enabled way to record and parse sports in a more cost-effective way.

“I spent close to four years trying to find a company trying to do that,” he said.

“I’ve always been a believer in sports content captured at the long tail,” he said. Coincidentally, he himself started a company called Krossover in his dorm room to help somewhat with tracking and recording sports training. Krossover eventually was acquired by Hudl, which Veo sees as a competitor.

“You’ll never have the NBA finals recorded on Veo, there is just too much at stake, but when you start to look at all the areas where there isn’t enough mass media value to hire people, to produce and livestream, you get to the point where computer vision and AI are going to be doing the filming to get rid of the cost.”

He said that the economics are important here: the camera needs to be less than $1,000 (which it is) and produce something demonstrably better than “a parent with a Best Buy camcorder that was picked up for $100.”

Kulkarni thinks that longer term there could definitely be an opportunity to consider how to help clubs bring that content to a wider audience, especially using highlights and focusing on the best of the best in amateur games — which of course are the precursors to some of those players one day being world-famous elite athletes. (Think of how exciting it is to see the footage of Michael Jordan playing as a young student for some context here.) “AI will be able to pull out the best 10-15 plays and stitch them together for highlight reels,” he said, something that could feasibly find a market with sports fans wider than just the parents of the actual players.

All of that then feeds a bigger market for what has started to feel like an insatiable appetite for sports, one that, if anything, has found even more audience at a time when many are spending more time at home and watching video overall. “The more video you get from the sport, the better the sport gets, for players and fans,” Teisbæk said.

Lyron Foster is a Hawaii based African American Musician, Author, Actor, Blogger, Filmmaker, Philanthropist and Multinational Serial Tech Entrepreneur.

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Elon Musk says Tesla Semi is ready for production, but limited by battery cell output

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Tesla CEO Elon Musk said on the company’s 2020 Q4 earnings call that all engineering work is now complete on the Tesla Semi, the freight-hauling semi truck that the company is building with an all-electric powertrain. The company expects to begin deliveries of Tesla Semi this year, the company said in its Q4 earnings release, and Musk said the only thing limiting their ability to produce them now is the availability of battery cells.

“The main reason we have not accelerated new products – like for example Tesla Semi – is that we simply don’t have enough cells for it,” Musk said. “If we were to make the Semi right now, and we could easily go into production with the Semi right now, but we would not have enough cells for it.”

Musk added that the company does expect to have sufficient cell volume to meet its needs once it goes into production on its 4680 battery pack, which is a new custom cell design it created with a so-called ‘tables’ design that allows for greater energy density and therefore range.

“A Semi would use typically five times the number of cells that a car would use, but it would not sell for five times what a car would sell for, so it kind of would not make sense for us to do the Semi right now,” Musk said. “But it will absolutely make sense for us to do it as soon as we can address the cell production constraint.”

That constraint points to the same conclusion for the possibility of Tesla developing a van, Musk added, and the lifting of the constraint will likewise make it possible for Tesla to pursue the development of that category of vehicle, he said.

Tesla has big plans for “exponentially” ramping cell production, with a goal of having production capacity infrastructure in place for a Toal of 200 gigawatt hours per year by 2022, and a target of being able to actually produce around 40% of that by that year (with future process improvements generating additional gigawatt hours of cell capacity  in gradual improvements thereafter).

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Pro-Trump Twitter figure arrested for spreading vote-by-text disinformation in 2016

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The man behind a once-influential pro-Trump account is facing charges of election interference for allegedly disseminating voting disinformation on Twitter in 2016.

Federal prosecutors allege that Douglass Mackey, who used the name “Ricky Vaughn” on Twitter, encouraged people to cast their ballot via text or on social media, effectively tricking others into throwing away those votes.

According to the Justice Department, 4,900 unique phone numbers texted a phone number Mackey promoted in order to “vote by text.” BuzzFeed reported the vote-by-text scam at the time, noting that many of the images were photoshopped to look like official graphics from Hillary Clinton’s presidential campaign.

Some of those images appeared to specifically target Black and Spanish-speaking Clinton supporters, a motive that tracks with the account’s track record of white supremacist and anti-Semitic content. The account was suspended in November 2016.

At the time, the mysterious account quickly gained traction in the political disinformation ecosystem. HuffPost revealed that the account was run by Mackey, the son of a lobbyist, two years later.

“… His talent for blending far-right propaganda with conservative messages on Twitter made him a key disseminator of extremist views to Republican voters and a central figure in the alt-right’ white supremacist movement that attached itself to Trump’s coattails,” HuffPost’s Luke O’Brien reported.

Mackey, a West Palm Beach resident, was taken into custody Wednesday in Florida.

“There is no place in public discourse for lies and misinformation to defraud citizens of their right to vote,” Acting U.S. Attorney for the Eastern District of New York Seth D. DuCharme said.

“With Mackey’s arrest, we serve notice that those who would subvert the democratic process in this manner cannot rely on the cloak of Internet anonymity to evade responsibility for their crimes.”

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Tesla is willing to license Autopilot and has already had “preliminary discussions” about it with other automakers

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Tesla is open to licensing its software, including its Autopilot highly-automated driving technology, and the neural network training it has built to improve its autonomous driving technology. Tesla CEO Elon Musk revealed those considerations on the company’s Q4 earnings call on Wednesday, adding that the company has in fact already “had some preliminary discussions about licensing Autopilot to other OEMs.”

The company began rolling out its beta version of the so-called ‘full self-driving’ or FSD version of Autopilot late last year. The standard Autopilot features available in general release provide advanced driver assistance (ADAS) which provide essentially advanced cruise control capabilities designed primarily for use in highway commutes. Musk said on the call that he expects the company will seek to prove out its FSD capabilities before entering into any licensing agreements, if it does end up pursuing that path.

Musk noted that Tesla’s “philosophy is definitely not to create walled gardens” overall, and pointed out that the company is planning to allow other automakers to use its Supercharger networks, as well as its autonomy software. He characterized Tesla as “more than happy to license” those autonomous technologies to “other car companies,” in fact.

One key technical hurdle required to get to a point where Tesla’s technology is able to demonstrate true reliability far surpassing that of a standard human driver is transition the neural networks operating in the cars and providing them with the analysis that powers their perception engines is to transition those to video. That’s a full-stack transition across the system away from basing it around neural nets trained on single cameras and single frames.

To this end, the company has developed video labelling software that has had “a huge effect on the efficiency of labeling,” with the ultimate aim being enabling automatic labeling. Musk (who isn’t known for modesty around his company’s achievements, it should be said) noted that Tesla believes “it may be the best neural net training computer in the world by possibly an order of magnitude,” adding that it’s also “something we can offer potentially as a service.”

Training huge quantities of video data will help Tesla push the reliability of its software from 100% that of a human driver, to 200% and eventually to “2,000% better than the average human,” Musk said, while again suggesting that it won’t be a technological achievement the company is interested into keeping to themselves.

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