Dogs and Cats - Living Together: The $75B Pet Economy and Why Los Angeles is Headquarters

Rachel Uranga

Rachel Uranga is dot.LA's Managing Editor, News. She is a former Mexico-based market correspondent at Reuters and has worked for several Southern California news outlets, including the Los Angeles Business Journal and the Los Angeles Daily News. She has covered everything from IPOs to immigration. Uranga is a graduate of the Columbia School of Journalism and California State University Northridge. A Los Angeles native, she lives with her husband, son and their felines.

Dogs and Cats - Living Together: The $75B Pet Economy and Why Los Angeles is Headquarters

Snuggling on a chair, hovering over a laptop, stretched out on the floor, the long haired-haired, vaguely Calico-looking Koko with his own Instagram feed is a cat influencer in the making. He is also the face of Basepaws, a feline DNA testing service that's trying to tap into the $75 billion spent on pets in the U.S.

Gingi, a sweet feline that died too young, is the inspiration behind startup PrettyLitter, a mail-order cat litter that monitors feline health. And then there's dozens of dogs that inspired DogVacay, a pet sitting app that was sold last year to Rover. Founder Aaron Hirschhorn launched a new service last fall – stem cell storage banks for pets – motivated by his own experience using the regenerative treatment.

According to Pitchbook, pet tech startups in Los Angeles County have pulled in more than $500 million in investments in the last six years. The largest and most well-known came from Softbank Vision Fund for Wag Labs — once the poster child for app-powered pet services. As Wag struggles to compete with venture capital-backed Rover, a slew of other pet tech companies are making their mark offering premium services.

"When I started DogVacay in 2012, I heard venture doesn't belong in pets. I got lots of 'No, the markets are too small,' said Hirschhorn, who has raised $11 million in funding led by Maveron for his latest venture, Gallant. "Now, the first thing that I hear is that people spend so much on their pets."

DogVacay is a pet sitting app that was sold last year to

Gallant, which launched in the fall, charges a $395 processing fee and $95 a year to store stem cells removed by a veterinarian when pets are spayed or neutered. It aims to make canine life healthier and longer. The company, which has a Federal Drug Administration compliant lab in La Jolla, appeals to veterinarians who can charge a fee for their service and have the promise of pets returning for treatment as they age.

The Pet Economy

Americans love their four-legged friends. More than half of U.S. households own a pet and while ownership rates haven't grown dramatically over the last decade, the amount people willing to spend on their animals has. The American Pet Products Association estimates last year spending topped $75 billion from $45 billion a decade earlier. And the figure is quadruple what it was in 1994.

"We see a ton of interest in the space," said Mike Jones, head of the Santa Monica incubator and investment firm Science Inc. His firm, which invested in DogVacay and Rover, recently backed DogDrop, a flexible canine day care. Jones said they made the calculation that with millennials choosing to have children later in life, animals would play a bigger role. "There's a lot of disposable income that people can spend on pets," he said. "The price point they are willing to spend is way higher."

There's companies like Modern Animal, a Playa Vista-based startup that wants to revamp veterinary clinics for the digital age with telemedicine and other services. It raised $13.5 million in seed funding last fall.

Gallant stores stem cells removed by a veterinarian when pets are spayed or neutered to make canine life healthier and

Scratchpay, a Pasadena-based company that offers financing for veterinary care, scored $65 million in a Series B round in October.

And then there's companies more akin to Gallant like PrettyLitter, a mail-order litter that monitors for health by turning colors when urine shows unusual signs of alkalinity and other factors.

Their growth is part of a larger trend powered by Americans' relationship with their pets, mostly dogs. This humanization, as those in the pet industry like to call it, has driven a push in luxury products and services.

"More and more people are thinking of their pets as parts of their family, as human beings," said Hal Herzog, a professor of psychology at Western Carolina University who has spent decades looking at the relationship between human and animals.

"We spend twice as much on pets per capita as we did 30 years ago."

Where's the money going? On the extravagant side, there's pets spas, canine herbal medicine, Louis Vuitton pet carriers, and diet delivery services. And there's also a booming trend of influencer canines who have their own agents, like Instagram star JiffPom (and his 9.8 million followers).

Pet owners are willing to go to extremes to spoil their dogs and cats -- even wading into unregulated pet technology to keep them healthy.

Unregulated Pet Technology

Founded in 2016 by Anna Skaya, Basepaws promises to tell feline owners with a sample of saliva from their cheek, "the secrets to keeping their health in tip-top shape." The El Segundo-based company presents itself as a health service but operates in a non-regulated zone, along with several other pet companies coming up including PrettyLitter and Gallant.

Skaya, who previously ran Groupon in Russia, originally wanted to name her company 23andMeow. Her proprietary genetic testing provides cat owners with information about their breeds along with hereditary disease. For humans those service are approved by the Federal Drug Administration. Still they aren't intended for diagnostic purposes and there are various levels of evidence to support many of their claims.

PrettyLitter is a mail-order litter that monitors for health by turning colors when urine shows unusual signs of alkalinity and other

And while Skaya and PrettyLitter founder Daniel Rotman say that their services are not diagnostic — merely a tool — they want pet owners looking to improve their animals health to turn to them.

"When you do a DNA test it opens up this world about breeds and diseases," she said. "I always say the cats can't talk but their DNA can." Last year, she clinched $250,000 on Shark Tank and is looking to close a $2.5 million seed round next month.

The service runs $129 and she sees her company, growing to include nutrition products. Hirschhorn, who invested in Basepaws, sees it working for the very same reasons that he believes his own company will take off. "There's this macro trend toward health rather than fighting diseases," Hirschhorn said, adding that it's the same reason humans are taking greater care of themselves.

Skaya has loftier goals: "If we know what diseases they have, we can make sure they are not breeding. We are eradicating genetic diseases."

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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 Undergoing Some Growing Pains at a Pivotal Moment in Its Development

Lon Harris
Lon Harris is a contributor to dot.LA. His work has also appeared on ScreenJunkies, RottenTomatoes and Inside Streaming.
AI Is Undergoing Some Growing Pains at a Pivotal Moment in Its Development
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, 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.

Rivian CEO Teases R2, New Features in Instagram AMA

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.

Rivian CEO Teases R2, New Features in Instagram AMA

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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