The Near Miss Apocalypse: Predictions for Post SVB Collapse

Spencer Rascoff

Spencer Rascoff serves as executive chairman of dot.LA. He is an entrepreneur and company leader who co-founded Zillow, Hotwire, dot.LA, Pacaso and Supernova, and who served as Zillow's CEO for a decade. During Spencer's time as CEO, Zillow won dozens of "best places to work" awards as it grew to over 4,500 employees, $3 billion in revenue, and $10 billion in market capitalization. Prior to Zillow, Spencer co-founded and was VP Corporate Development of Hotwire, which was sold to Expedia for $685 million in 2003. Through his startup studio and venture capital firm, 75 & Sunny, Spencer is an active angel investor in over 100 companies and is incubating several more.

The Near Miss Apocalypse: Predictions for Post SVB Collapse
Evan Xie

The historic Silicon Valley Bank collapse dominated headlines recently, and the tech and financial communities have only just started processing the aftermath. The 48-hour breakdown was both historic and a few inches away from economically catastrophic, and thanks to the swift moves of the FDIC, complete disaster was avoided.

But it’s still been disruptive. SVB was the banking partner for nearly half of U.S. venture-backed technology and healthcare companies that listed on stock markets in 2022, making it one of the biggest lenders for early-stage startups. The aftershocks of SVB’s breakdown spread just as far and fast as the main event: the close of Signature Bank just two days later, major market volatility, other banking crises at Credit Suisse, tech industry troubles, and much more.

In the days since, things have settled slightly, and the world’s fingers are crossed that depositors are comforted enough and confident enough to avoid another bank run. It’s good news, but we aren’t out of the woods yet. Now that we know the second-largest bank failure in U.S. history could be looming around any corner, how does that change the ways startups do business?

Level, Set, Go

Before we get into what could happen, it’s smart to level-set about how we got here. (And for an introductory primer, this short podcast can help.)

  • The government 100% did the right thing by assuring depositors that they will be made whole. The FDIC swooped in, steadied the ship, and made sure people had the money they needed when they needed it.
  • Some have called this a ‘bailout', but it’s not for two reasons. 1) SVB shareholders and creditors will be wiped out and 2) taxpayer money is not being used to do any bailing.
  • Remember: depositors are not creditors. When companies and people put money into their accounts at SVB, they had every reason to expect that it would be there when they needed to withdraw it. They weren’t loaning the money to SVB (as a creditor would), they were depositing money into their own account at SVB for safekeeping.
  • People who say “depositors took a risk by having more than the FDIC insured $250K limit” are, ahem, a bit misguided. (I’m being polite). The truth is that $250K is not that much money for a company, especially of the size and scale of some of SVB's major customers.

Here’s where I think we should go from here.

The Short Term

While SVB’s failure didn’t launch us over the precipice, many people are rightfully feeling very nervous being this close to the edge.

Looking out to the next few weeks, I predict we’ll see venture funding slow way down. It’s been chilly out there recently, but it’s going to be ice cold, piggybacking on the already struggling tech landscape. Writing new checks will take a backseat to checking in on existing investments. VCs will need to assess where their cash is and where their portfolio companies stand, and likewise startups are going to have to start thinking hard about what it means to be lean and extend runway. Hopefully this only lasts a few weeks and the wheels of the machine start turning again before summer.

If there is a positive take on the SVB wreckage, it’s that the Fed will likely slow down the rate of increases. I’d predict a 25, maybe even 0, basis-point increase next week, and I wouldn’t be surprised if there was a rate cut later this year.

Whither venture debt?

Prior to SVB’s failure, it was very common for a startup to have enough cash at SVB for one year of runway, plus a venture debt line for an additional another year. SVB profited from this by charging interest plus warrants and requiring banking exclusivity. It was part and parcel of how they did business, and since they’ve transitioned from success story to cautionary tale, expect to see new regulations prohibiting banks from requiring customer exclusivity in exchange for additional services.

In the immediate term, companies who had venture debt lines with SVB are trying to decide whether to put their cash back in SVB in order to access that venture debt. The whole situation is surreal, since just a few days ago these same companies were scrambling to pull their money out of SVB, and now they are considering returning. There are conflicting reports, but it appears that SVB is allowing these companies to keep a second banking relationship with another bank (so no more exclusivity), but at least half of their cash must be with SVB.

For startups choosing not to access that venture debt line, now trying to figure out how to operate without venture debt (aka less hiring, less spending, less growth), they’re in for challenging times ahead. To fill that funding gap, maybe we’ll see more private lenders step in and provide venture debt as a product. If that is the case, I suspect terms will be tougher and many VCs will recommend against it for their companies.

Another prediction: audit committees of boards will come into play much earlier than they often do now. Given the ever larger seed and Series A/B rounds, it wasn’t uncommon to see startups that had raised $100M+ and had 200+ employees before an audit committee was formed. I suspect these will now be formed upfront and have a much bigger role to play in early stages.

Silver Lining

The good news: the world isn’t ending and won’t in the near future (at least, not because of this). Yes, things will be different and it will take some time to settle into a post-SVB startup environment, but with change comes adaptation. And with adaptation comes innovation, which is what startups are all about.

https://twitter.com/spencerrascoff
https://www.linkedin.com/in/spencerrascoff/
admin@dot.la

Subscribe to our newsletter to catch every headline.

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.

Read moreShow less

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.

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

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.

Read moreShow less
RELATEDEDITOR'S PICKS
LA TECH JOBS
interchangeLA
Trending