‘Expand Past the Stage’: How These LA-based Ticketing Platforms are Using The Metaverse to Take On Ticketmaster

Andria Moore

Andria is the Social and Engagement Editor for dot.LA. She previously covered internet trends and pop culture for BuzzFeed, and has written for Insider, The Washington Post and the Motion Picture Association. She obtained her bachelor's in journalism from Auburn University and an M.S. in digital audience strategy from Arizona State University. In her free time, Andria can be found roaming LA's incredible food scene or lounging at the beach.

‘Expand Past the Stage’: How These LA-based Ticketing Platforms are Using The Metaverse to Take On Ticketmaster
Evan Xie

When Taylor Swift announced her ‘Eras’ tour back in November, all hell broke loose.

Hundreds of thousands of dedicated Swifties — many of whom were verified for the presale — were disappointed when Ticketmaster failed to secure them tickets, or even allow them to peruse ticketing options.

But the Taylor Swift fiasco is just one of the latest in a long line of complaints against the ticketing behemoth. Ticketmaster has dominated the event and concert space since its merger with Live Nation in 2010 with very few challengers — until now.

Adam Jones, founder and CEO of Token, a fan-first commerce platform for events, said he has the platform and the tech ready to take it on. With Token, Jones is creating a system where there are no queues. In other words, fans know immediately which events are sold out and where.

“We come in very fortunate to have a modern, scalable tech stack that's not going to have all these outages or things being down,” Jones said. “That's step one. The other thing is we’re being aggressively transparent about what we’re doing and how we’re doing it. So with the Taylor Swift thing…you would know in real time if you actually have a chance of getting the tickets.”

Here’s how it works: Users register for Token’s app and then purchase tickets to either an in-person event, or an event in the metaverse through Animal Concerts. The purchased ticket automatically shows up in the form of a mintable NFT, which can then be used toward merchandise purchases, other ticketed events or, Adams’s hope for the future — external rewards like airline travel. The more active a user is on the site, the more valuable their NFT becomes.

Ticketmaster has dominated the music industry for so long because of its association with big name artists. To compete, Token is working on gaining access to their own slew of popular artists. They recently entered into a partnership with Animal Concerts, a live and non-live event experiences platform that houses artists like Alicia Keys, Snoop Dogg and Robin Thicke.

“You'll see they do all the metaverse side of the house,” Jones said. “And we're going to be the [real-life] web3 sides of the house.”

In addition, Token prides itself on working with the artists selling on their platform to set up the best system for their fanbase, devoid of hefty prices and additional fees — something Ticketmaster users have often complained about. Jones believes where Ticketmaster fails, Token thrives. The app incentivizes users to share more data about their interests, venues and artists by operating on a kind of points system in the form of mintable NFTs.

“We can actually take the dataset and say there’s 100 million people in the globe that love Taylor Swift, so imagine she’s going on tour and we ask [the user], ‘Would you go to see her in Detroit?’ And imagine this place has 30,000 seats, but 100,000 people clicked ‘yes,’” he explained. “So you can actually inform the user before anything even happens, right? About what their options are and where to get it.”

Tixr, a Santa-Monica based ticketing app, was founded on the idea that modern ticketing platforms were “living in the legacy of the past.” They plan to attract users by offering them exclusive access to ticketed events that aren’t in Ticketmaster’s registry.

“It melts commerce that's beyond ticketing…to allow fans to experience and purchase things that don't necessarily have to do with tickets,” said Tixr CEO and Founder Robert Davari. “So merchandise, and experiences, and hospitality and stuff like that are all elegantly melded into this one, content driven interface.”

Tixr sells tickets to exclusive concerts like a Tyga performance at a night club in Arizona, general in-person festivals like ComplexCon, and partners with local vendors like The Acura Grand Prix of Long Beach to sell tickets to the races. Plus, Davari said it’s equipped to handle high-demand, so customers aren’t spending hours waiting in digital queues.

Like Token, Tixr has also found success with a rewards program — in the form of fan marketing.

“There's nothing more powerful in the core of any event, brand, any live entertainment, [than] the community behind it,” Davari said. “So we build technology to empower those fans and to reward them for bringing their friends and spreading the word.”

Basically, if a user gets a friend to purchase tickets to an event, then the original user gets rewarded in the form of discounts or upgrades.

Coupled with their platforms’ ability to handle high-demand events, both Jones and Davari believe their platforms have what it takes to take on Ticketmaster. Expansion into the metaverse, they think, will also help even the playing field.

“So imagine you can't go to Taylor Swift,” Jones said. “What if you could purchase an exclusive to actually go to that exact same show over the metaverse? An artist’s whole world can expand past the stage itself.”

With the way ticketing for events works now, obviously not everyone always gets the exact price, venue or date they want. There are “winners and losers.” Jones’s hope is that by expanding beyond in-person events, there can be more winners.

“If there’s 100,000 people who want to go to one show and there's 37,000 seats, 70,000 are out,” he said. “You can't fight that. But what we can do is start to give them other opportunities to do things in a different way and actually still participate.”

Jones and Davari both teased that their platforms have some exciting developments in the works, but for now both Token and Tixr are set on making their own space within the industry.

“We simply want to advance this industry and make it more efficient and more pleasurable for fans to buy,” Davari said. “That's it.”

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Creandum’s Carl Fritjofsson on the Differences Between the Startup Ecosystem in Europe and the U.S.

Decerry Donato

Decerry Donato is a reporter at dot.LA. Prior to that, she was an editorial fellow at the company. Decerry received her bachelor's degree in literary journalism from the University of California, Irvine. She continues to write stories to inform the community about issues or events that take place in the L.A. area. On the weekends, she can be found hiking in the Angeles National forest or sifting through racks at your local thrift store.

Carl Fritjofsson
Carl Fritjofsson

On this episode of the LA Venture podcast, Creandum General Partner Carl Fritjofsson talks about his venture journey, why Generative-AI represents an opportunity to rethink products from the ground up, and why Q4 2023 and Q1 2024 could be "pretty bloody" for startups.

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AI Is Rapidly Advancing, but the Question Is, Can We Keep Up?

Lon Harris
Lon Harris is a contributor to dot.LA. His work has also appeared on ScreenJunkies, RottenTomatoes and Inside Streaming.
AI Is Rapidly Advancing, but the Question Is, Can We Keep Up?
Evan Xie

One way to measure just how white-hot AI development has become: the world is running out of the advanced graphics chips necessary to power AI programs. While Intel central processing units were once the most sought-after industry leaders, advanced graphics chips like Nvidia’s are designed to run multiple computations simultaneously, a baseline necessity for many AI models.

An early version of ChatGPT required around 10,000 graphics chips to run. By some estimates, newer updates require 3-5 times that amount of processing power. As a result of this skyrocketing demand, shares of Nvidia have jumped 165% so far this year.

Building on this momentum, this week, Nvidia revealed a line-up of new AI-related projects including an Israeli supercomputer project and a platform utilizing AI to help video game developers. For smaller companies and startups, however, getting access to the vital underlying technology that powers AI development is already becoming less about meritocracy and more about “who you know.” According to the Wall Street Journal, Elon Musk scooped up a valuable share of server space from Oracle this year before anyone else got a crack at it for his new OpenAI rival, X.AI.

The massive demand for Nvidia-style chips has also created a lucrative secondary market, where smaller companies and startups are often outbid by larger and more established rivals. One startup founder compares the fevered crush of the current chip marketplace to toilet paper in the early days of the pandemic. For those companies that don’t get access to the most powerful chips or enough server space in the cloud, often the only remaining option is to simplify their AI models, so they can run more efficiently.

Beyond just the design of new AI products, we’re also at a key moment for users and consumers, who are still figuring out what sorts of applications are ideal for AI and which ones are less effective, or potentially even unethical or dangerous. There’s now mounting evidence that the hype around some of these AI tools is reaching a lot further than the warnings about its drawbacks.

JP Morgan Chase is training a new AI chatbot to help customers choose financial securities and stocks, known as IndexGPT. For now, they insist that it’s purely supplemental, designed to advise and not replace money managers, but it may just be a matter of time before job losses begin to hit financial planners along with everyone else.

A lawyer in New York just this week was busted by a judge for using ChatGPT as part of his background research. When questioned by the judge, lawyer Peter LoDuco revealed that he’d farmed out some research to a colleague, Steven A. Schwartz, who had consulted with ChatGPT on the case. Schwartz was apparently unaware that the AI chatbot was able to lie – transcripts even show him questioning ChatGPT’s responses and the bot assuring him that these were, in fact, real cases and citations.

New research by Marucie Jakesch, a doctoral student from Cornell University, suggests that even users who are more aware than Schwartz about how AI works and its limitations may still be impacted in subtle and subconscious ways by its output.

Not to mention, according to data from Intelligent.com, high school and college students already – on the whole – prefer utilizing ChatGPT for help with schoolwork over a human tutor. The survey also notes that advanced students tend to report getting more out of using ChatGPT-type programs than beginners, likely because they have more baseline knowledge and can construct better and more informative prompts.

But therein lies the big drawback to using ChatGPT and other AI tools for education. At least so far, they’re reliant on the end user writing good prompts and having some sense about how to organize a lesson plan for themselves. Human tutors, on the other hand, have a lot of personal experience in these kinds of areas. Someone who instructs others in foreign languages professionally probably has a good inherent sense of when you need to focus on expanding your vocabulary vs. drilling certain kinds of verb and tense conjugations. They’ve helped many other students prepare for tests, quizzes, and real-world challenges, while computer software can only guess at what kinds of scenarios its proteges will face.

A recent Forbes editorial by academic Thomas Davenport suggests that, while AI is getting all the hype right now, other forms of computing or machine learning are still going to be more effective for a lot of basic tasks. From a marketing perspective in 2023, it’s helpful for a tech company to throw the “AI” brand around, but it’s not magically going to be the answer for every problem.

Davenport points to a similar (if smaller) whirlwind of excitement around IBM’s “Watson” in the early 2010s, when it was famously able to take out human “Jeopardy!’ champions. It turns out, Watson was a general knowledge engine, really best suited for jobs like playing “Jeopardy.” But after the software gained celebrity status, people tried to use it for all sorts of advanced applications, like designing cancer drugs or providing investment advice. Today, few people turn to Watson for these kinds of solutions. It’s just the wrong tool for the job. In that same way, Davenport suggests that generative AI is in danger of being misapplied.

While the industry and end users both race to solve the AI puzzle in real time, governments are also feeling pressure to step in and potentially regulate the AI industry. This is much easier said than done, though, as politicians face the same kinds of questions and uncertainty as everyone else.

OpenAI CEO Sam Altman has been calling for governments to begin regulating AI, but just this week, he suggested that the company might pull out of the European Union entirely if the regulations were too onerous. Specifically, Altman worries that attempts to narrow what kinds of data can be used to train AI systems – specifically blocking copyrighted material – might well prove impossible. “If we can comply, we will, and if we can’t, we’ll cease operating,” Altman told Time. “We will try, but there are technical limits to what’s possible.” (Altman has already started walking this threat back, suggesting he has no immediate plans to exit the EU.)

In the US, The White House has been working on a “Blueprint for an AI Bill of Rights,” but it’s non-binding, just a collection of largely vague suggestions. It’s one thing to agree “consumers shouldn’t face discrimination from an algorithm” and “everyone should be protected from abusive data practices and have agency over how their data is used.” But enforcement is an entirely different animal. A lot of these issues already exist in tech, and are much larger than AI, and the US government already doesn’t do much about them.

Additionally, it’s possible AI regulations won’t work well at all if they aren’t global. Even if you set some policies and get an entire nation’s government to agree, how to set similar worldwide protocols? What if US and Europe agree but India doesn’t? Everyone around the world accesses roughly the same internet, so without any kind of international standard, it’s going to be much harder for individual nations to enforce specific rules. As with so many other AI developments, there’s inherent danger in patchwork regulations; it could allow some companies, or regions, or players to move forward while others are unfairly or ineffectively stymied or held back.

The same kinds of socio-economic concerns around AI that we have nationally – some sectors of the work force left behind, the wealthiest and most established players coming in to the new market with massive advantages, the rapid spread of misinformation – are all, in actuality, global concerns. Just as the hegemony of Microsoft and Google threaten the ability of new players to enter the AI space, the West’s early dominance of AI tech threatens to push out companies and innovations from emerging markets like Southeast Asia, Subsaharan Africa, and Central America. Left unfettered, AI could potentially deepen social, economic, and digital divisions both within and between all of these societies.

Undaunted, some governments aren’t waiting around for these tools to develop any further before they start attempting to regulate them. New York City has already set up some rules about how AI can be used during the hiring process while will take effect in July. The law requires any company using AI software in hiring to notify candidates that it’s being used, and to have independent auditors check the system annually for bias.

This sort of piecemeal figure-it-out-as-we-go approach is probably what’s going to be necessary, at least short-term, as AI development shows zero signs of slowing down or stopping any time soon. Though there’s some disagreement among experts, most analysts agree with Wharton professor and economist Jeremy Siegel, who told CNBC this week that AI is not yet a bubble. He pointed to the Nvidia earnings as a sign the market remains healthy and not overly frothy. So, at least for now, the feverish excitement around AI is not going to burst like a late ‘90s startup stock. The world needs to prepare as if this technology is going to be with us for a while.

What the Future of Rivian Looks Like According to CEO RJ Scaringe

David Shultz

David Shultz reports on clean technology and electric vehicles, among other industries, for dot.LA. His writing has appeared in The Atlantic, Outside, Nautilus and many other publications.

What the Future of Rivian Looks Like According to CEO RJ Scaringe
Rivian

Rivian CEO RJ Scaringe took to Instagram last weekend to answer questions from the public about his company and its future. Topics covered included new colors, sustainability, production ramp, new products and features. Speaking of which, viewers also got a first look at the company’s much-anticipated R2 platform, albeit made of clay and covered by a sheet, but hey, that’s…something. If you don’t want to watch the whole 33 minute video, which is now also on Youtube, we’ve got the highlights for you.

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