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XMeet the New BallerTV CTO Holding Court at Pickup Basketball Games as Sports Seasons Rebound
If you stop by Koreatown's Immanuel Presbyterian Church on Sundays, you might run into Kavodel Ohiomoba pushing a broom across a basketball court hidden on an upper floor of the cavernous historic French Gothic cathedral. It's a favorite movie backdrop for Hollywood films.
On a Bose portable speaker, you also might hear rapper Polo G's mellow-sounding "RAPSTAR" echoing off of the mid-century gymnasium's walls: "Lately, I've been prayin', God, I wonder, can you hear me? Thinkin' 'bout the old me, I swear I miss you dearly."
The six-foot, four-inch tall Ohiomoba, known as "Kav", gets the gym tidied up before the first game starts at 9 a.m. sharp. The "run," or freewheeling run-and-gun basketball game with connections drawn together by Kav, came together this past summer as the pandemic began to subside and vaccines were readily available to all. He got the idea of using pickup basketball as a way to network with the tech community from Jeff Jordan, partner at A16Z, who runs a famous pickup game in Palo Alto.
Kav is chief technology officer of BallerTV, the Pasadena-based streaming sports company that livestreams youth sporting events at scale, and is currently focused on basketball, volleyball, soccer and lacrosse.
Before BallerTV, the Stanford alum put in work at a few tech startups in the Silicon Valley, including MOCAP Analytics, where he was a member of the founding team as a data scientist and software engineer. The MOCAP team leveraged machine learning and computer vision to build a data storytelling engine on top of the player tracking data that was quickly being adopted by NBA teams.
"The opportunities were truly endless," Kav said. "We were building models that told us which players and teams did what, where, how and when."
As advances in computer vision — and later, machine learning and artificial intelligence — introduced new possibilities for sports viewing, Kav sought to bring broadcasting and video to athletes who weren't being streamed on ESPN or major television outlets. Not long after, he co-founded FieldVision, which built hardware and software using artificial intelligence and computer vision to autonomously film any team sport, anywhere.
BallerTV CTO Kavodel Ohiomoba
FieldVision came into the BallerTV fold via acquisition about two years ago, and proved to be a slam-dunk for the company. Since its launch in 2016, BallerTV had relied on an army of 30,000 videographers throughout the United States to film youth athletic games ranging from basketball to volleyball.
Kav spearheaded the effort to take FieldVision's machine learning — fueled by artificial intelligence algorithms — and put it all into an iPhone app. After a few months, the i1 platform was born. The platform uses an iPhone rigged up with a wide-angle lens and its software tracks players on the court, ball movement and shifts in a fast-moving game. The game is then broadcast live to BallerTV's rapidly growing network of subscribers, allowing anyone with an internet connection to watch as if they were sitting courtside at the game.
The i1 platform has been revolutionary for BallerTV, which filmed 350,000 youth sports games in 2021. On a given weekend, BallerTV can film more than 20,000 games. That's 5,000 more games in a weekend than the 15,000 ESPN televises in an entire year.
Kav says there's a bigger purpose behind his basketball runs. The group is diverse and inclusive, with participants coming from all parts of L.A. and a variety of professions. The basketball games serve as a form of connection between people, regardless of their backgrounds.
Some runs have included BallerTV's co-founder and co-CEO Aaron Hawkey, nicknamed "15 and in," mostly because he's money from within 15-feet of the basket; Marcus Boyd, a former professional track and field athlete turned software engineer; John Daniels, founder and CEO of Navtrac, a logistics technology company that utilizes artificial intelligence software to track inventory, and Tommer Schwarz, a doctoral candidate in genetics at UCLA.
"I'm an old man. I did not injure myself last weekend, but I missed several layups in spectacular fashion," said the 40-year-old Paul Haaga, managing director of HW Capital in Santa Monica, of his performance one weekend in October.
Haaga's firm was an early investor in BallerTV, as well as a number of other early-stage companies and real estate deals.
"It's interesting, if you see guys enough on several Sunday mornings in a row, you get to know who they are as people on the basketball court, and that's probably a pretty good indicator of who they are in life. Do they play fair? Do they play hard? Do they compete? It's a good indicator of someone's qualities, and if they have relationships outside of the game, then that's all the better," said Haaga, who makes the 14-mile drive in from his La Cañada residence.
And few reveal who they are quite like Kav, who attends to the runs as he would a group of his close friends.
"There is no job that is below [Kav], whether it's dusting the floor before we get there, or making sure that everybody's hydrated with Gatorade. He's always thinking about your health, right? Everything is sugar-free," observed Ryan Sauter, an entrepreneur in the hospitality industry whose Hybrid One is headquartered in downtown's Arts District.
Sauter's highlight of the week is when he gets the weekly email from Kav asking 60 other like-minded people on the distribution list if they're in or not for the weekly pick up at the church.
"I definitely look forward to that email, which comes Wednesday or Thursday," Sauter said. "It kind of brightens your day a bit because you're like, 'Hey, I can't wait until Sunday to play with everybody."
After breaking a sweat at the church, Kav and the others head over for some chit-chat and a cup of joe at the Starbucks or Blue Bottle Coffee near the K-Town church. Even grabbing a post-run cup of coffee is a welcome respite in a time where people are trying to be connected more than ever.
"We're coming out of COVID, and that's how this evolved," Kav said. "We were itching to meet each other. And of course, I think we were all itching to get back out on the court."
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It took me 48 hours to realize Lensa might have a problem.
“Is that my left arm or my boob?” I asked my boyfriend, which is not what I’d consider a GREAT question to have to ask when using photo editing software.
“Huh,” my boyfriend said. “Well, it has a nipple.”
Well then.
I had already spent an embarrassing amount of money downloading nearly 1,000 high-definition images of myself generated by AI through an app called Lensa as part of its new “Magical Avatar” feature. There are many reasons to cock an eyebrow at the results, some of which have been covered extensively in the last few days in a mounting moral panic as Lensa has shot itself to the #1 slot in the app store.
The way it works is users upload 10-20 photos of themselves from their camera roll. There are a few suggestions for best results: the pictures should show different angles, different outfits, different expressions. They shouldn’t all be from the same day. (“No photoshoots.”) Only one person in the frame, so the system doesn’t confuse you for someone else.
Lensa runs on Stable Diffusion, a deep-learning mathematical method that can generate images based on text or picture prompts, in this case taking your selfies and ‘smoothing’ them into composites that use elements from every photo. That composite can then be used to make the second generation of images, so you get hundreds of variations with no identical pictures that hit somewhere between the Uncanny Valley and one of those magic mirrors Snow White’s stepmother had. The tech has been around since 2019 and can be found on other AI image generators, of which Dall-E is the most famous example. Using its latent diffusion model and a 400 million image dataset called CLIP, Lensa can spit back 200 photos across 10 different art styles.
Though the tech has been around a few years, the rise in its use over the last several days may have you feeling caught off guard for a singularity that suddenly appears to have been bumped up to sometime before Christmas. ChatGPT made headlines this week for its ability to maybe write your term papers, but that’s the least it can do. It can program code, break down complex concepts and equations to explain to a second grader, generate fake news and prevent its dissemination.
It seems insane that when confronted with the Asminovian reality we’ve been waiting for with either excitement, dread or a mixture of both, the first thing we do is use it for selfies and homework. Yet here I was, filling up almost an entire phone’s worth of pictures of me as fairy princesses, anime characters, metallic cyborgs, Lara Croftian figures, and cosmic goddesses.
And in the span of Friday night to Sunday morning, I watched new sets reveal more and more of me. Suddenly the addition of a nipple went from a Cronenbergian anomaly to the standard, with almost every photo showing me with revealing cleavage or completely topless, even though I’d never submitted a topless photo. This was as true for the male-identified photos as the ones where I listed myself as a woman (Lensa also offers an “other” option, which I haven’t tried.)
Drew Grant
When I changed my selected gender from female to male: boom, suddenly, I got to go to space and look like Elon Musk’s Twitter profile, where he’s sort of dressed like Tony Stark. But no matter which photos I entered or how I self-identified, one thing was becoming more evident as the weekend went on: Lensa imagined me without my clothes on. And it was getting better at it.
Was it disconcerting? A little. The arm-boob fusion was more hilarious than anything else, but as someone with a larger chest, it would be weirder if the AI had missed that detail completely. But some of the images had cropped my head off entirely to focus just on my chest, which…why?
According to AI expert Sabri Sansoy, the problem isn’t with Lensa’s tech but most likely with human fallibility.
“I guarantee you a lot of that stuff is mislabeled,” said Sansoy, a robotics and machine learning consultant based out of Albuquerque, New Mexico. Sansoy has worked in AI since 2015 and claims that human error can lead to some wonky results. “Pretty much 80% of any data science project or AI project is all about labeling the data. When you’re talking in the billions (of photos), people get tired, they get bored, they mislabel things and then the machine doesn’t work correctly.”
Sansoy gave the example of a liquor client who wanted software that could automatically identify their brand in a photo; to train the program to do the task, the consultant had first to hire human production assistants to comb through images of bars and draw boxes around all the bottles of whiskey. But eventually, the mind-numbing work led to mistakes as the assistants got tired or distracted, resulting in the AI learning from bad data and mislabeled images. When the program confuses a cat for a bottle of whiskey, it’s not because it was broken. It’s because someone accidentally circled a cat.
So maybe someone forgot to circle the nudes when programming Stable Diffusion’s neural net used by Lensa. That’s a very generous interpretation that would explain a baseline amount of cleavage shots. But it doesn’t explain what I and many others were witnessing, which was an evolution from cute profile pics to Brassier thumbnails.
When I reached out for comment via email, a Lensa spokesperson responded not by directing us to a PR statement but actually took the time to address each point I’d raised. “It would not be entirely accurate to state that this matter is exclusive to female users,” said the Lensa spokesperson, “or that it is on the rise. Sporadic sexualization is observed across all gender categories, although in different ways. Please see attached examples.” Unfortunately, they were not for external use, but I can tell you they were of shirtless men who all had rippling six packs, hubba hubba.
“The stable Diffusion Model was trained on unfiltered Internet content, so it reflects the biases humans incorporate into the images they produce,” continued the response. Creators acknowledge the possibility of societal biases. So do we.” It reiterated the company was working on updating its NSFW filters.
As for my insight about any gender-specific styles, the spokesperson added: “The end results across all gender categories are generated in line with the same artistic principles. The following styles can be applied to all groups, regardless of their identity: Anime and Stylish.”
I found myself wondering if Lensa was also relying on AI to handle their PR, before surprising myself by not caring all that much. If I couldn’t tell, did it even matter? This is either a testament to how quickly our brains adapt and become numb to even the most incredible of circumstances; or the sorry state of hack-flack relationships, where the gold standard of communication is a streamlined transfer of information without things getting too personal.
As for the case of the strange AI-generated girlfriend? “Occasionally, users may encounter blurry silhouettes of figures in their generated images. These are just distorted versions of themselves that were ‘misread’ by the AI and included in the imagery in an awkward way.”
So: gender is a social construct that exists on the Internet; if you don’t like what you see, you can blame society. It’s Frankenstein’s monster, and we’ve created it after our own image.
Or, as the language processing AI model ChatGPT might put it: “Why do AI-generated images always seem so grotesque and unsettling? It's because we humans are monsters and our data reflects that. It's no wonder the AI produces such ghastly images - it's just a reflection of our own monstrous selves.”
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Vinfast, the Vietnamese EV company with headquarters in Los Angeles, shipped its first order of vehicles to U.S. soil from Hai Phong, Vietnam on November 25th. The batch of 999 automobiles is due to arrive here in California on Thursday this week.
The VF8 SUVs on board will have the difficult task of convincing American buyers that an unknown, untested Vietnamese manufacturer can deliver on a new technology. And so far, the company appears to be off to a rocky start.
According to an email sent to reservation holders on November 29th, the VF8s in the initial shipment will be a special “City Edition” and have lower range advertised than the previously announced versions–just 180 miles in total. Over the weekend, Vinfast confirmed to dot.LA via Twitter that all of the vehicles in the first batch are the City Edition, and that the standard edition would be coming Q1 of 2023. Until this email, there had been little, if any mention of this new City Edition. The message to reservation holders offered no rationale as to why the company was choosing to ship this version of the car instead of the 260-292 mile-range VF8 it’s been advertising for months. Despite the lower range, however, the EVs will still carry a price tag of either $55,500 or $62,500, depending on trim–just $3,000 less than the previously-announced versions.
The VF8 Specs page from Vinfast’s site still bears no mention of a “City Edition,” but that’s what’s coming to America this month.
Vinfast is offering reservation holders an additional $3,000 off these City Edition variants (bringing the total to $6,000 less than the previously announced versions). But even at a discount, the vehicle’s $52,000 price tag is far from competitive with more established EV makers and raises questions about the brand’s strategy and value.
For comparison:
- The 2023 Hyundai Ioniq 5 has 220 miles of range and starts at $42,745. Or 303 miles of range for $60,000.
- The base model Kia EV6 costs $49,795 and goes 206 miles on a full charge.
- The Mustang Mach E starts at 46,895 and reaches 224 miles.
And the list goes on. In fact, you’d be hard pressed to find a 2023 EV with a worse cost to range ratio than the VF8. Vinfast, which has been nearly impossible to reach on this matter despite numerous calls and emails, hasn’t explained why they chose to offer such a range-compromised version as their initial foray into the U.S. market, or why the cost remains so high.
The reaction to the news, especially on Reddit, has been largely negative, with users accusing the company of “springing” the City Edition on reservation holders. Others speculated that the company rushed out the first batch so it could drum up good press before its recently announced IPO. Whatever the reason, most redditors didn’t seem to be buying it, and with Vinfast so reluctant to comment, it’s hard to see the announcement in a light that bodes well for the company’s future. First impressions tend to last, and this doesn’t seem like a good one for the EV hopeful.
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