ChartHop CEO Ian White breathed a major sigh of relief in late January after his cloud software startup raised a $20 million funding round. He’d started the process six months earlier during a brutal period for tech stocks and a plunge in venture funding.
For ChartHop’s prior round in 2021, it took White less than a month to raise $35 million. The market turned against him in a hurry.
“There was just a complete reversal of the speed at which investors were willing to move,” said White, whose company sells cloud technology used by human resources departments.
Whatever comfort White was feeling in January quickly evaporated last week. On March 9 — a Thursday — ChartHop held its annual revenue kickoff at the DoubleTree by Hilton Hotel in Tempe, Arizona. As White was speaking in front of more than 80 employees, his phone was blowing up with messages.
White stepped off stage to find hundreds of panicked messages from other founders about Silicon Valley Bank, whose stock was down more than 60% after the firm said it was trying to raise billions of dollars in cash to make up for deteriorating deposits and ill-timed investments in mortgage-backed securities.
Startup executives were scrambling to figure out what to do with their money, which was locked up at the 40-year-old firm long known as a linchpin of the tech industry.
“My first thought, I was like, ‘this is not like FTX or something,'” White said of the cryptocurrency exchange that imploded late last year. “SVB is a very well-managed bank.”
But a bank run was on, and by Friday SVB had been seized by regulators in the second-biggest bank failure in U.S. history. ChartHop banks with JPMorgan Chase, so the company didn’t have direct exposure to the collapse. But White said many of his startup’s customers held their deposits at SVB and were now uncertain if they’d be able to pay their bills.
While the deposits were ultimately backstopped last weekend and SVB’s government-appointed CEO tried to reassure clients that the bank was open for business, the future of Silicon Valley Bank is very much uncertain, further hampering an already troubled startup funding environment.
SVB was the leader in so-called venture debt, providing loans to risky early-stage companies in software, drug development and other areas like robotics and climate-tech. Now it’s widely expected that such capital will be less available and more expensive.
White said SVB has shaken the confidence of an industry already grappling with rising interest rates and stubbornly high inflation.
Exit activity for venture-backed startups in the fourth quarter plunged more than 90% from a year earlier to $5.2 billion, the lowest quarterly total in more than a decade, according to data from the PitchBook-NVCA Venture Monitor. The number of deals declined for a fourth consecutive quarter.
In February, funding was down 63% from $48.8 billion a year earlier, according to a Crunchbase funding report. Late-stage funding fell by 73% year-over-year, and early-stage funding was down 52% over that stretch.
‘World was falling apart’
CNBC spoke with more than a dozen founders and venture capitalists, before and after the SVB meltdown, about how they’re navigating the precarious environment.
David Friend, a tech industry veteran and CEO of cloud data storage startup Wasabi Technologies, hit the fundraising market last spring in an attempt to find fresh cash as public market multiples for cloud software were plummeting.
Wasabi had raised its prior round a year earlier, when the market was humming, IPOs and special purpose acquisition companies (SPACs) were booming and investors were drunk on low interest rates, economic stimulus and rocketing revenue growth.
By last May, Friend said, several of his investors had backed out, forcing him to restart the process. Raising money was “very distracting” and took up more than two-thirds of his time over nearly seven months and 100 investor presentations.
“The world was falling apart as we were putting the deal together,” said Friend, who co-founded the Boston-based startup in 2015 and previously started numerous other ventures including data backup vendor Carbonite. “Everybody was scared at the time. Investors were just pulling in their horns, the SPAC market had fallen apart, valuations for tech companies were collapsing.”
Friend said the market always bounces back, but he thinks a lot of startups don’t have the experience or the capital to weather the current storm.
“If I didn’t have a good management team in place to run the company day to day, things would have fallen apart,” Friend said, in an interview before SVB’s collapse. “I think we squeaked through, but if I had to go back to the market right now and raise more money, I think it’d be extremely difficult.”
In January, Tom Loverro, an investor with Institutional Venture Partners, shared a thread on Twitter predicting a “mass extinction event” for early and mid-stage companies. He said it will make the 2008 financial crisis “look quaint.”
Loverro was hearkening back to the period when the market turned, starting in late 2021. The Nasdaq hit its all-time high in November of that year. As inflation started to jump and the Federal Reserve signaled interest rate hikes were on the way, many VCs told their portfolio companies to raise as much cash as they’d need to last 18 to 24 months, because a massive pullback was coming.
In a tweet that was widely shared across the tech world, Loverro wrote that a “flood” of startups will try to raise capital in 2023 and 2024, but that some will not get funded.
Federal Reserve Chair Jerome Powell arrives for testimony before the Senate Banking Committee March 7, 2023 in Washington, DC.
Win Mcnamee | Getty Images News | Getty Images
Next month will mark 18 months since the Nasdaq peak, and there are few signs that investors are ready to hop back into risk. There hasn’t been a notable venture-backed tech IPO since late 2021, and none appear to be on the horizon. Meanwhile, late-stage venture-backed companies like Stripe, Klarna and Instacart have been dramatically reducing their valuations.
In the absence of venture funding, money-losing startups have had to cut their burn rates in order to extend their cash runway. Since the beginning of 2022, roughly 1,500 tech companies have laid off a total of close to 300,000 people, according to the website Layoffs.fyi.
Kruze Consulting provides accounting and other back-end services to hundreds of tech startups. According to the firm’s consolidated client data, which it shared with CNBC, the average startup had 28 months of runway in January 2022. That fell to 23 months in January of this year, which is still historically high. At the beginning of 2019, it sat at under 20 months.
Madison Hawkinson, an investor at Costanoa Ventures, said more companies than normal will go under this year.
“It’s definitely going to be a very heavy, very variable year in terms of just viability of some early-stage startups,” she told CNBC.
Hawkinson specializes in data science and machine learning. It’s one of the few hot spots in startup land, due largely to the hype around OpenAI’s chatbot called ChatGPT, which went viral late last year. Still, being in the right place at the right time is no longer enough for an aspiring entrepreneur.
Founders should anticipate “significant and heavy diligence” from venture capitalists this year instead of “quick decisions and fast movement,” Hawkinson said.
The enthusiasm and hard work remains, she said. Hawkinson hosted a demo event with 40 founders for artificial intelligence companies in New York earlier this month. She said she was “shocked” by their polished presentations and positive energy amid the industrywide darkness.
“The majority of them ended up staying till 11 p.m.,” she said. “The event was supposed to end at 8.”
Founders ‘can’t fall asleep at night’
But in many areas of the startup economy, company leaders are feeling the pressure.
Matt Blumberg, CEO of Bolster, said founders are optimistic by nature. He created Bolster at the height of the pandemic in 2020 to help startups hire executives, board members and advisers, and now works with thousands of companies while also doing venture investing.
Even before the SVB failure, he’d seen how difficult the market had become for startups after consecutive record-shattering years for financing and an extended stretch of VC-subsidized growth.
“I coach and mentor a lot of founders, and that’s the group that’s like, they can’t fall asleep at night,” Blumberg said in an interview. “They’re putting weight on, they’re not going to the gym because they’re stressed out or working all the time.”
VCs are telling their portfolio companies to get used to it.
“In this environment, my advice is pretty simple, which is — that thing we lived through the last three or four years, that was fantasy,” Gurley said. “Assume this is normal.”
Laurel Taylor recently got a crash course in the new normal. Her startup, Candidly, announced a $20.5 million financing round earlier this month, just days before SVB became front-page news. Candidly’s technology helps consumers deal with education-related expenses like student debt.
Taylor said the fundraising process took her around six months and included many conversations with investors about unit economics, business fundamentals, discipline and a path to profitability.
As a female founder, Taylor said she’s always had to deal with more scrutiny than her male counterparts, who for years got to enjoy the growth-at-all-costs mantra of Silicon Valley. More people in her network are now seeing what she’s experienced in the six years since she started Candidly.
“A friend of mine, who is male, by the way, laughed and said, ‘Oh, no, everybody’s getting treated like a female founder,'” she said.
CORRECTION: This article has been updated to show that ChartHop held its annual revenue kickoff at the DoubleTree by Hilton Hotel in Tempe, Arizona, on Thursday, March 9.
Elon Musk announced his new company xAI, which he says has the goal to understand the true nature of the universe.
Jaap Arriens | Nurphoto | Getty Images
XAI, the artificial intelligence startup run by Elon Musk, raised a combined $10 billion in debt and equity, Morgan Stanley said.
Half of that sum was clinched through secured notes and term loans, while a separate $5 billion was secured through strategic equity investment, the bank said on Monday.
The funding gives xAI more firepower to build out infrastructure and develop its Grok AI chatbot as it looks to compete with bitter rival OpenAI, as well as with a swathe of other players including Amazon-backed Anthropic.
In May, Musk told CNBC that xAI has already installed 200,000 graphics processing units (GPUs) at its Colossus facility in Memphis, Tennessee. Colossus is xAI’s supercomputer that trains the firm’s AI. Musk at the time said that his company will continue buying chips from semiconductor giants Nvidia and AMD and that xAI is planning a 1-million-GPU facility outside of Memphis.
Addressing the latest funds raised by the company, Morgan Stanley that “the proceeds will support xAI’s continued development of cutting-edge AI solutions, including one of the world’s largest data center and its flagship Grok platform.”
xAI continues to release updates to Grok and unveiled the Grok 3 AI model in February. Musk has sought to boost the use of Grok by integrating the AI model with the X social media platform, formerly known as Twitter. In March, xAI acquired X in a deal that valued the site at $33 billion and the AI firm at $80 billion. It’s unclear if the new equity raise has changed that valuation.
xAI was not immediately available for comment.
Last year, xAI raised $6 billion at a valuation of $50 billion, CNBC reported.
Morgan Stanley said the latest debt offering was “oversubscribed and included prominent global debt investors.”
Competition among American AI startups is intensifying, with companies raising huge amounts of funding to buy chips and build infrastructure.
Musk has called Grok a “maximally truth-seeking” AI that is also “anti-woke,” in a bid to set it apart from its rivals. But this has not come without its fair share of controversy. Earlier this year, Grok responded to user queries with unrelated comments about the controversial topic of “white genocide” and South Africa.
Musk has also clashed with fellow AI leaders, including OpenAI’s Sam Altman. Most famously, Musk claimed that OpenAI, which he co-founded, has deviated from its original mission of developing AI to benefit humanity as a nonprofit and is instead focused on commercial success. In February, Musk alongside a group of investors, put in a bid of $97.4 billion to buy control of OpenAI. Altman swiftly rejected the offer.
— CNBC’s Lora Kolodny and Jonathan Vanian contributed to this report.
In recent years, the company has transformed from a competent private sector telecommunications firm into a “muscular technology juggernaut straddling the entire AI hardware and software stack,” said Paul Triolo, partner and senior vice president for China at advisory firm DGA-Albright Stonebridge Group.
Ramon Costa | SOPA Images | Lightrocket | Getty Images
Huawei has open-sourced two of its artificial intelligence models — a move tech experts say will help the U.S.-blacklisted firm continue to build its AI ecosystem and expand overseas.
The Chinese tech giant announced on Monday the open-sourcing of the AI models under its Pangu series, as well as some of its model reasoning technology.
Tech experts told CNBC that Huawei’s latest announcements not only highlight how it is solidifying itself as an open-source LLM player, but also how it is strengthening its position across the entire AI value chain as it works to overcome U.S.-led AI chip export restrictions.
In recent years, the company has transformed from a competent private sector telecommunications firm into a “muscular technology juggernaut straddling the entire AI hardware and software stack,” said Paul Triolo, partner and senior vice president for China at advisory firm DGA-Albright Stonebridge Group.
In its announcement Monday, Huawei called the open-source moves another key measure for Huawei’s “Ascend ecosystem strategy” that would help speed up the adoption of AI across “thousands of industries.”
The Ascend ecosystem refers to AI products built around the company’s Ascend AI chip series, which are widely considered to be China’s leading competitor to products from American chip giant Nvidia. Nvidia is restricted from selling its advanced products to China.
A Google-like strategy?
Pangu being available in an open-source manner allows developers and businesses to test the models and customize them for their needs, said Lian Jye Su, chief analyst at Omdia. “The move is expected to incentivize the use of other Huawei products,” he added.
According to experts, the coupling of Huawei’s Pangu models with the company’s AI chips and related products gives the company a unique advantage, allowing it to optimize its AI solutions and applications.
While competitors like Baidu have LLMs with broad capabilities, Huawei has focused on specialized AI models for sectors such as government, finance and manufacturing.
“Huawei is not as strong as companies like DeepSeek and Baidu at the overall software level – but it doesn’t need to be,” said Marc Einstein, research director at Counterpoint Research.
“Its objective is to ultimately use open source products to drive hardware sales, which is a completely different model from others. It also collaborates with DeepSeek, Baidu and others and will continue to do so,” he added.
Ray Wang, principal analyst at Constellation Research, said the chip-to-model strategy is similar to that of Google, a company that is also developing AI chips and AI models like its open-source Gemma models.
Huawei’s announcement on Monday could also help with its international ambitions. Huawei, along with players like Zhipu AI, has been slowly making inroads into new overseas markets.
In its announcement Monday, Huawei invited developers, corporate partners and researchers around the world to download and use its new open-source products in order to gather feedback and improve them.
“Huawei’s open-source strategy will resonate well in developing countries where enterprises are more price-sensitive as is the case with [Huawei’s] other products,” Einstein said.
As part of its global strategy, the company has also been looking to bring its latest AI data center solutions to new countries.
Digital illustration of a glowing world map with “AI” text across multiple continents, representing the global presence and integration of artificial intelligence.
Fotograzia | Moment | Getty Images
As artificial intelligence becomes more democratized, it is important for emerging economies to build their own “sovereign AI,” panelists told CNBC’s East Tech West conference in Bangkok, Thailand, on Friday.
In general, sovereign AI refers to a nation’s ability to control its own AI technologies, data and related infrastructure, ensuring strategic autonomy while meeting its unique priorities and security needs.
However, this sovereignty has been lacking, according to panelist Kasima Tharnpipitchai, head of AI strategy at SCB 10X, the technology investment arm of Thailand-based SCBX Group. He noted that many of the world’s most prominent large language models, operated by companies such as Anthropic and OpenAI, are based on the English language.
“The way you think, the way you interact with the world, the way you are when you speak another language can be very different,” Tharnpipitchai said.
It is, therefore, important for countries to take ownership of their AI systems, developing technology for specific languages, cultures, and countries, rather than just translating over English-based models.
Panelists agreed that the digitally savvy ASEAN region, with a total population of nearly 700 million people, is particularly well positioned to build its sovereign AI. People under the age of 35 make up around 61% of the population, and about 125,000 new users gain access to the internet daily.
Given this context, Jeff Johnson, managing director of ASEAN at Amazon Web Services, said, “I think it’s really important, and we’re really focused on how we can really democratize access to cloud and AI.”
Open-source models
According to panelists, one key way that countries can build up their sovereign AI environments is through the use of open-source AI models.
“There is plenty of amazing talent here in Southeast Asia and in Thailand, especially. To have that captured in a way that isn’t publicly accessible or ecosystem developing would feel like a shame,” said SCB 10X’s Tharnpipitchai.
Doing open-source is a way to create a “collective energy” to help Thailand better compete in AI and push sovereignty in a way that is beneficial for the entire country, he added.
Open-source generally refers to software in which the source code is made freely available, allowing anyone to view, modify and redistribute it. LLM players, such as China’s DeepSeek and Meta’s Llama, advertise their models as open-source, albeit with some restrictions.
The emergence of more open-source models offers companies and governments more options compared to relying on a few closed models, according to Cecily Ng, vice president and general manager of ASEAN & Greater China at software vendor Databricks.
AI experts have previously told CNBC that open-source AI has helped China boost AI adoption, better develop its AI ecosystem and compete with the U.S.
Access to computing
Prem Pavan, vice president and general manager of Southeast Asia and Korea at Red Hat, said that the localization of AI had been focused on language until recently. Having sovereign access to AI models powered by local hardware and computing is more important today, he added.
Panelists said that for emerging countries like Thailand, AI localization can be offered by cloud computing companies with domestic operations. These include global hyperscalers such as AWS, Microsoft Azure and Tencent Cloud, and sovereign players like AIS Cloud and True IDC.
“We’re here in Thailand and across Southeast Asia to support all industries, all businesses of all shapes and sizes, from the smallest startup to the largest enterprise,” said AWS’s Johnson.
He added that the economic model of the company’s cloud services makes it easy to “pay for what you use,” thus lowering the barriers to entry and making it very easy to build models and applications.
In April, the U.N. Trade and Development Agency said in a report that AI was projected to reach $4.8 trillion in market value by 2033. However, it warned that the technology’s benefits remain highly concentrated, with nations at risk of lagging behind.
Among UNCTAD’s recommendations to the international community for driving inclusive growth was shared AI infrastructure, the use of open-source AI models and initiatives to share AI knowledge and resources.