Writer-Actor Shantell Yasmine Abeydeera on How Niche Streamers Create Community

Sam Blake

Sam primarily covers entertainment and media for dot.LA. Previously he was Marjorie Deane Fellow at The Economist, where he wrote for the business and finance sections of the print edition. He has also worked at the XPRIZE Foundation, U.S. Government Accountability Office, KCRW, and MLB Advanced Media (now Disney Streaming Services). He holds an MBA from UCLA Anderson, an MPP from UCLA Luskin and a BA in History from University of Michigan. Email him at samblake@dot.LA and find him on Twitter @hisamblake

Writer-Actor Shantell Yasmine Abeydeera on How Niche Streamers Create Community

Shantell Yasmine Abeydeera is an L.A.-based writer, performer and content creator. Her latest series, "Dating In Place," will be available on Revry, an L.A.-based, ad-supported, niche streaming service focused on the LGBTQ community.

Revry is one of many niche streaming services competing in an increasingly crowded market, where audience loyalty and good relationships with artists are key to success, as we probed in an earlier piece on what it takes for a niche streaming service to survive.

Revry is free and accessible to more than 250 million households and devices in over 130 countries. Its offerings are divided into several channels, such as "Revry News" and "Revry Live TV." "Dating In Place" will air on the channel " OML on Revry," which debuted earlier this month to focus on queer female programming.


It is a collaboration with OML, a boutique media company formerly called One More Lesbian, of which Abeydeera is also the director of content and partnerships.

dot.LA recently caught up with her about her new show, her thoughts on the value of queer spaces in the streaming world and how niche services can help build community around content.

OML on. Revry - Official Teaser

dot.LA: Do you consider yourself a queer-oriented artist?

Abeydeera: I consider myself to be a storyteller, first and foremost. But being queer is a very important part of of my storytelling journey, mainly because of the lack of representation that was available to me when I was younger. I wasn't seeing stories where I was represented on screen. And that's because of the fact that I am so unique, in being multi-ethnic, queer, very feminine-presenting, a lot of things that we just don't really on screen.

I was always really, really thirsty to see that kind of representation. I started creating queer storylines, and once it started being received by the queer community, I saw that there was such a need for it.

How does a platform like Revry allow you to get those kinds of representative stories out there?

I think it's huge, but there is definitely a struggle. Platforms like Revry obviously don't have the money behind them, the way that the mainstream streamers like your Hulus and your Amazons do. So it's harder for them to produce shows that are the kinds that bring in the audiences that become loyal.

What's really smart is that these guys are focusing a lot on short-form content, which is far more attainable for content-creators as well as for the platform. So, say for example, "Dating In Place": 10-minute episodes, 10 episodes of the series – that is far more affordable than 10 episodes of a half-hour series where you go from the show costing $20,000 to costing $150,000. It's easier for queer content-creators to fund short-form content.

In that sense, do you see Revry as a stepping stone to working with a different, perhaps larger distributor?

I would like to see the development of platforms like Revry. My hope is that these platforms develop and form the viewership they deserve, so that then they're able to become partners in creating more content. I'm not necessarily thirsty to go and work with a big machine, but I'm not totally against it either.

Are you worried about potentially pigeonholing your career by focusing on queer content or working with a queer-oriented distributor?

No, I don't really worry about pigeonholing my career, mainly because I think there are many different incarnations of queer stories that can be told. For a long time, queer people weren't able to tell their stories. I think we're going to start to see an expansion. So I'm looking forward to telling stories that just merely have queer characters in them. And where we're not necessarily calling it queer.

How do you see "Dating In Place" playing a role in that trajectory of telling broader queer stories?

One of the interesting things in "Dating In Place" is that we don't actually ever refer to any of the characters as being queer. We never talk about it. I think that's a big step. And there's never any reference to there being any issues with parents or families when it comes to these characters' sexual identity.

The issue was just that these two girls met, they were going to go on a date, and then the pandemic hit, and now they're in completely separate countries, and they're dating online and falling in love but they've never seen each other or touched each other.

If not for OML on Revry, what do you think would have happened with "Dating In Place"?

A lot of what happens to short-form content is it goes to festivals and then it goes to YouTube. And especially for queer content, that's kind of the death for the content creator, because queer content on YouTube is quite famously de-monetized. So the money that you're making on the clicks of queer content is, like, minus cents in comparison to other content that can maybe make like a dollar, or whatever. So I think without a platform like OML on Revry, a show like "Dating in Place" would have just gone on YouTube or Vimeo.

How else would you say having your show on OML on Revry is beneficial to you as a creator?

The thing that I will say about the queer community, especially – consumers of queer content – is that they're very loyal. Once they become interested in your content, they are then interested in you and invested in you. As an artist and as a creator, that's really all you can ask for: people that are going to be there to view the content that you've made, and people that are going to be there when you make more.

I'm really excited for this platform to exist for this audience. Before, a lot of this audience, the fandom audience, kind of would just be scrolling through YouTube, clicking on tiny thumbnails trying to figure out, is this a queer-inclusive show? And now, hopefully, they will migrate over to a platform where they know that all of the content is queer-inclusive and queer-positive, and has been made for them. Hopefully, now this audience will find a home.

This interview has been edited and condensed for clarity.

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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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