During his tenure as chair from 1987 to 2006, Greenspan was renowned for his cryptic utterances on the economy, leaving rate-watchers befuddled as to whether they presaged a likely cut or hike. His wife, veteran correspondent , famously that their marriage took time because “he claims he proposed three times before I was able to understand. He was so oblique. It was like his testimony.”

In spite of his long history of obfuscation, however, Greenspan is best known for a fairly unambiguous two-word phrase: “irrational exuberance.” He coined it in a 1996 to the  , a conservative-leaning think tank, titled “The Challenge of Central Banking in a Democratic Society.”

One of the speech’s core points was the notion that pricing logic in an industrial economy dominated by durable goods and materials is far simpler than for a modern economy increasingly dominated by software and services.

“What is the price of a unit of software or a legal opinion? How does one evaluate the price change of a cataract operation over a 10-year period when the nature of the procedure and its impact on the patient changes so radically?” he mused, before turning to that most famous insight.

That insight, if I am translating Greenspan-speak correctly, was linked to the question of how one can establish long-term confidence in valuations of assets tied to fast-changing technologies and business models, like software, where prior notions of unit economics no longer applied.

“How do we know when irrational exuberance has unduly escalated asset values, which then become subject to unexpected and prolonged contractions,” he wondered. It’s a conjecture that 30 years later still has no obvious answer.

Notably, Greenspan’s speech actually predated the most heated periods of the dot-com boom, bubble and implosion, which began in the late 1990s and culminated with the hitting its cyclical peak in early 2000. During and shortly after that period, money-losing e-commerce companies like online grocer and pet supply retailer famously went public at then sky-high valuations before abruptly shuttering. Internet infrastructure providers fared even worse, exemplified by networking equipment maker going from Canada’s most valuable company to penny stock in a couple years.

But while losers lost big, winners eventually eclipsed them. Dot-com-era megastars and , for instance, are now worth nearly $8 trillion combined.

That brings us to one of Greenspan’s other well-known analogies: the lottery ticket.

In Congressional testimony in early 1999, pressed for his thoughts on then fast-rising share prices of hot internet companies, the Fed chair the stock-buying frenzy to playing the lottery. He observed that people have long been willing to pay more for a lottery ticket than their chances of winning would justify, simply because they are drawn to the remote chance of a huge win.

”And undoubtedly some of these small companies, which have stock prices going through the roof, will succeed and they very well may justify even higher prices,” he said. ”The vast majority are almost sure to fail. That’s the way the markets work in this regard.”

Fast-forward to today, and one is easily drawn to apply Greenspan’s analogy to the current AI mania. Once again, we’re seeing unprecedented valuations attached to money-losing companies, many in still relatively nascent stages of development.

In other ways, however, this time it’s not a dot-com lottery ticket redo. For one thing, the companies in which a retail investor might be buying said ticket are by no means small. , at its current market cap, is the sixth-most valuable U.S. public company. It’s priced like a winner, not a wanna-be.

Same holds true for recent valuations for and , both of which have confidentially filed for public offerings likely to debut in coming months. Anthropic hit a $965 billion post-money valuation, while OpenAI’s was recently around $852 billion.

One wonders what Greenspan would say about these stratospheric asset price levels. I’d suspect there are better than lottery-ticket odds that it would be something cryptic.

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Photo: Dr. Alan Greenspan, former Chairman of the Board of Governors of the Federal Reserve, speaks at the Per Jacobsson Foundation Lecture, October 21, 2007, in Washington, DC. (Photo by International Monetary Fund Photograph/Stephen Jaffe used under the .)

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The company is a marketing analytics platform that acts as an independent referee of sorts to track which digital ads actually drive mobile app downloads and in-app purchases. It helps companies measure their return on ad spend while claiming to protect user privacy and block ad fraud.

While AppsFlyer CEO and co-founder declined to comment on specific deal details, he did confirm to Axios that , , and each took a minority stake in the San Francisco-based startup.

AppsFlyer’s most recent raise before this was in 2020. With the latest round, the company has now raised $1.3 billion in known funding since its 2011 inception, per .

Previous backers include , 1, , and .

“They believe what we believe: that attribution and measurement must be independent, unbiased and trusted,” Kaniel was quoted as saying of AppsFlyer’s newest investors. “As AI takes over more of how advertising gets bought and optimized, the signals feeding those systems become the most consequential infrastructure in the industry.”

He added that the company is eyeing the public markets, calling the financing “a step on that path.”

So far in 2026, companies in sales, marketing and CRM categories have pulled in around $4.1 billion globally in seed- through growth-stage funding, per 91Ÿ«Æ· . That puts the space on track to come in roughly flat with or a bit up from the prior three years — when annual funding hovering around the $8 billion mark — though still far below boom-era levels, when sales and marketing investment topped $20 billion. Notably, many of the startups funded in recent quarters have been AI-focused, with many of them offering agentic tools and automation in areas such as sales, marketing and customer experience management.

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Globally, robotics startups have so far raised $18.8 billion in 2026, compared to $15 billion in the full year of 2025. The figure also handily surpasses the $14.1 billion raised in the peak venture funding year of 2021, and we still have more than six months of fundraising left.

The impressive rise in funding reflects a marked shift in perception among venture investors about the robotics sector, which was traditionally considered an expensive, asset-heavy hardware gamble. In particular, investors appear to be drawn to startups working on embodied AI, or artificial intelligence with a physical body that interacts with the real world in real time.

Noteworthy recent rounds

The surge in funding is driven by a number of robotics-focused startups raising considerable capital from investors this year. Also, interestingly, two of the five largest raises in 2026 to date have been by Austin-based companies.

Topping the list of largest deals in 2026 so far is Austin-based , a defense tech startup focused on autonomous sea vessels. In March, the 4-year-old company raised $1.75 billion in Series D funding, bringing its total funding to around $2.6 billion. led the round, which set Saronic’s valuation at $9.25 billion — more than double its Series C level in 2025.

Earlier this month, Germany’s , a developer of AI infrastructure for robots to learn, collaborate and operate across real-world environments, said it secured up to $1.4 billion in Series C funding. led that raise.

In January, , a robotics company building an “omni-bodied” brain to operate any robot for any task, announced that it had raised $1.4 billion, tripling its valuation to over $14 billion. That financing came just over seven months after Skild raised at a $4.5 billion valuation. led the startup’s latest round, which included participation from , ’s venture capital arm.

On June 15, Beijing-based , which creates water robots and intelligent unmanned equipment, raised $1 billion in a massive Series A round led by .

And in February, AI-powered robotics company raised $520 million in an extension of its $415 million Series A raise in February 2025, bringing the total round to over $935 million. Existing backers , , and joined new investors, including and manufacturing giant in participating in the extension.

Interestingly, spinout has already raised two rounds in 2026. In March, the Palo Alto, California-based startup closed on a $500 million Series A round, co-led by and . Then in May, it raised another $400 million in a financing led by . The company is developing an AI-enabled industrial robotics platform focused on automating industrial and manufacturing tasks at scale.

Exits

While mergers and acquisitions have been relatively robust with several strategic buyouts, the robotics IPO landscape is a bit quieter, particularly in the U.S.

In China, however, a number of robotics companies have recently gone public. The of , targeting a $3 billion to $7 billion valuation, was considered a milestone for the industry. In March, the company filed for an to list on the , and its IPO was widely expected to spur other startups in the space to pursue their own public-market debuts.

, a startup based in China’s Shandong province that makes lightweight industrial robots, in May listed on the , raising about $86 million. And it did not disappoint. Robotphoenix closed its first full day of trading at HK$53.75 ($6.86 U.S.), up nearly 80%, though shares have dipped to the HK$37 range more recently.

On the M&A front, a number of Big Tech and automotive giants have been aggressively acquiring embodied AI and humanoid talent to anchor their physical automation strategies.

In February, AI-powered supply chain provider acquired , an Austin-based maker of autonomous forklifts and lift trucks.

Skild AI in April that it had picked up the robotics arm of in an effort to deploy its technology to warehouses.

And in May, tech giant entered the humanoid robotics field directly by acquiring San Diego-based . The team was absorbed into Meta’s Superintelligence Labs unit to accelerate training of its foundational physical AI model.

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This is a weekly feature that runs down the week’s top 10 announced funding rounds in the U.S. Check out last week’s biggest funding deal roundup here.

This week was not an exceptionally busy one for large funding deals, though we saw sizable rounds in a lively mix of sectors ranging from AI to fintech to quantum computing and cybersecurity. The biggest raise was for AI world-model developer, which secured a $310 million Series B. Venture investors also put money into AI infrastructure and AI models for biotech.

1. , $310M, artificial intelligence: Menlo Park, California-based Odyssey raised $310 million at a $1.45 billion valuation in a Series B round led by . Other investors included ,,,, and . Odyssey develops AI world models that create multimodal simulations of real-world environments. The startup has now raised $337 million in funding to date, .

2. , $140M, fintech: New York-based Chronograph secured a $140 million private equity round led by . The company provides portfolio monitoring, reporting and diligence software for private capital investors, an increasingly important market as private assets continue to grow. The new raise, which it describes as growth capital, brings its total funding to date to $160 million, according to .

3. (tied) , $100M, AI infrastructure: Boulder, Colorado-based Hydra Host raised a massive $100 million Series A led by . A of other investors joined, including ,, , and . The company operates a bare-metal GPU platform that connects customers to distributed AI computing infrastructure. With the latest investment, it has raised just under $119 million to date.

3. (tied) , $100M, cybersecurity: Startups that promise to protect companies in the AI era are also raising massive sums right out of the gate. This week, Santa Clara, California-based Ent.AI emerged from stealth and said it has raised $100 million in seed funding led by. Other investors included,, 1,, and. The company, founded by former executives and members of the Security Copilot team, offers an AI-powered workspace security platform that it says can analyze user and AI-agent behavior in real time to proactively prevent cyber threats.

3. (tied) , $100M, cybersecurity, defense: Arlington, Virginia-based Twenty Technologies secured a $100 million Series B at a $1 billion valuation. The round was led by, with participation from, and. The company develops AI-enabled cyber warfare systems for the U.S. military and intelligence community, helping automate and accelerate offensive cyber operations at scale. Founded by former cyber operators and defense technologists, Twenty Technologies has now raised $138 million to date,. It’s part of a growing wave of venture-backed startups building software for military and national security purposes.

3. (tied) , $100M, quantum computing: Berkeley, California-based Atom Computing raised a $100 million Series C led by that brings its total private investment to date to just over $191 million, . and also backed its latest round. Along with the venture money, Atom also received a $100 million Letter of Intent from the under the CHIPS and Science Act that gives the startup additional public backing in exchange for a minority government stake. The company develops neutral-atom quantum computers, one of several competing architectures seeking to commercialize quantum computing. It is one of several quantum startups to receive sizable funding deals this year, following a record-breaking venture investment year for the sector in 2025.

7. , $65M, biotechnology: Watertown, Massachusetts-based Triveni Bio raised a $65 million Series C co-led by and. Additional participation came from. The company develops antibody-based therapeutics for immunological and inflammatory diseases. It has now raised $272 million total from investors, .

8. (tied) , $52M, semiconductor infrastructure: Menlo Park, California-based AttoTude secured a $52 million Series C led by. Other investors included ,,,, 2, and. The startup develops high-speed interconnect technology for AI and hyperscale data centers and has raised $142 million to date, according to . It comes amid robust funding for semiconductor startups this year.

8. (tied) , $52M, digital media: Beverly Hills, California-based Richard Roths Media raised a $52 million venture round led by . The company says it delivered AI-driven marketing and advertising services for “high trust” industries such as banking, law and healthcare. The investment appears to be its first outside capital, per 91Ÿ«Æ·.

10. (tied) , $50M, artificial intelligence: San Francisco-based Bland AI raised a $50 million Series C led by . The of other investors includes , , founder , and others. The company develops AI-powered voice agents that automate inbound and outbound phone conversations for enterprises, a category that has seen growing adoption as businesses look to replace traditional call-center workflows. It has raised $106 million to date, according to .

10. (tied) , $50M, fintech: Brooklyn-based Interchecks secured a $50 million Series C led by,, and. The company operates a payments platform that allows businesses to manage deposits and payouts through a single API, reflecting continued investor interest in infrastructure that simplifies financial operations. It has now raised just under $79 million to date.

10. (tied) , $50M, artificial intelligence, biotechnology: Menlo Park, California-based Radical Numerics emerged from stealth and said it has raised a $50 million seed round led by, with participation from , and . The startup is developing AI models designed to simulate and predict biological systems, with the goal of accelerating drug discovery and advancing precision medicine.

Large non-US deals:

• The largest startup deal outside of the U.S. this week was very large indeed, and also very unusual. , the Chinese AI chatbot startup that briefly roiled public AI-related stocks in early 2025, reportedly took its first outside financing, worth roughly $7.4 billion. The Series A deal, however, comes with a lot of atypical caveats, notably that investors in the deal didn’t actually receive a stake in DeepSeek, but rather in an LLC controlled by founder , per . Those investors also reportedly face a five-year lockup and receive no voting rights.

Methodology

We tracked the largest announced rounds in the 91Ÿ«Æ· database that were raised by U.S.-based companies for the period of June 13-18. Although most announced rounds are represented in the database, there could be a small time lag as some rounds are reported late in the week.

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This tracker includes layoffs conducted by U.S.-based companies or those with a strong U.S. presence and is updated at least bi-weekly. We’ve included both startups and publicly traded, tech-heavy companies. We’ve also included companies based elsewhere that have a sizable team in the United States, such as , even when it’s unclear how much of the U.S. workforce has been affected by layoffs.

Layoff and workforce figures are best estimates based on reporting. We source the layoffs from media reports, our own reporting, social media posts and , a crowdsourced database of tech layoffs.

We recently updated our layoffs tracker to reflect the most recent round of layoffs each company has conducted. This allows us to quickly and more accurately track layoff trends, which is why you might notice some changes in our most recent numbers.

If an employee headcount cannot be confirmed to our standards, we note it as “unclear.”

I sold my AI research company while I was qualifying as a lawyer in the U.K. I built with researchers from , , and who believed in the mission enough to trust a 21-year-old law student to lead the ship.

, when acquired us, it was the first time in its 170-year history it bought a company pre-revenue. Thomson Reuters acquired us for the science.

Getting there was painful, though. Our published papers put the model among the best in the world at legal reasoning, and we trained it for a fraction of what the large labs were spending. We had been a quieter version of “the story,” developing very capable models using novel algorithms with huge capital efficiency.

None of that counted for much in the rooms I walked into. Investors always asked about the product and the traction. U.K. investors passed, and I ended up raising most of our funding in the United States.

I back founders now, and the things I weigh have stayed consistent. As a founder, I was told again and again that science meant little until it was bolted onto a product. That test was wrong then and I believe it is fatal now.

Backing founders in the foundational layer

In the first quarter of 2026, foundational AI startups raised around $178 billion. The market is realizing that foundational AI is where the long-term value sits, and this is the year we may see the exits and IPOs that prove the bet right.

However, the capital and the conviction have also pooled around a few names that were already incumbent. , and took roughly 97% of it, and every other foundational AI company in the world shared what was left.

For a deep-tech founder starting out now, that might push them toward a tempting but dangerous read of the market: that the race is over, and that the sensible move would be to build on top of one of these giants.

I’m looking for founders who move the other way.

Most application-layer companies, built on a model they do not own, adapt to the pricing and access decided for them by the firms upstream, and compete in categories that the same firm can absorb whenever it chooses.

The more durable place to build is the layer underneath. The cost, speed, reliability, interpretability and safety of AI systems remain unsolved and genuine scientific challenges, and they decide what everything that sits above them can do.

A real advance in training efficiency, model architecture and inference cost is the work that will still matter in five years, long after most of today’s wrappers have been priced out or absorbed.

Asking the right questions

So the questions I ask AI founders are:

• Is your technical team, scientist-for-scientist, equal to or better than the team at DeepMind?
• Does the problem sit at the level of the model and the system, or is it one more thing stacked on someone else’s?
• Will the “product” get harder to live without over the next five years, or is it looking to reach for early revenue like every other startup?

Some of the companies that ended up mattering most in the AI era are those that survived this line of thought. DeepMind and OpenAI began as research efforts with no obvious product, and both would have looked uncomfortable to a conventional early-stage software investor. Their importance is obvious in hindsight, but the foundational problem-solvers tend to look unfundable right up until it looks inevitable.

Do not build to look fundable this quarter. Build something that the whole stack will depend on in the future. Hire the best team you can find to do it, and solve the hard, foundational problem while it is still unfashionable.

The deep-tech capital market is slow, and it will keep chasing familiar names for a while yet. The work still comes first, and the founders who dare to do it early are the ones the market eventually has to come and find.

The future lies in deep tech, not in the surface wrappers that pass for most products nowadays.

was the founder and CEO of , which was acquired by in 2024. He is an angel investor and senior director at Thomson Reuters Labs.

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The acquisition represents an enormous return on investment for Cursor’s backers. Since its founding just four years ago, parent company raised $3.4 billion from investors including , repeat backer , and and was most recently valued at roughly $30 billion in November, per 91Ÿ«Æ·.

The acquisition gives SpaceX, which raised $75 billion in its IPO last week, a foothold into the enterprise software development market, where AI-assisted coding has taken off and led large companies to significantly pare back their reliance on human engineers. Cursor said in November last year that it had crossed $1 billion in annualized revenue.

Hawthorne, California-based SpaceX has in recent years expanded beyond space exploration to become something of an umbrella company for CEO ’s numerous other interests and ambitions, as the company acquired the social media platform (formerly Twitter) and the AI company . SpaceX shares jumped around 16% on Tuesday following the Cursor announcement.

This year has proven robust for M&A activity involving venture-backed startups, 91Ÿ«Æ· data shows. Through June 16, at least 1,177 such deals altogether valued at $182.7 billion have been announced. That compares with 1,132 deals valued at $106.7 billion in the same period last year.

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So far in 2026, U.S. companies have pulled in nearly 80% of global seed- through growth-stage financing, per 91Ÿ«Æ· data. That’s a sharp divergence from the years leading up to the AI boom, when American companies typically secured less than half of all investment.

Gap for AI is even more pronounced

The U.S. share of artificial intelligence-related investment is even greater.

So far this year, nearly 88% of AI-related startup funding, or $319 billion, went to U.S.-headquartered companies, per 91Ÿ«Æ· data. Of that, most went to just two recipients, and .

Since both Anthropic and OpenAI are on track for public market debuts later this year, it’s possible next year’s comps will be less lopsided, as they won’t be raising any more giant late-stage financings. We’ll see.

Large venture hubs outperform small and mid-sized ones

Although no other country comes close to the U.S. for startup funding, a few of the larger technology investment hubs are seeing year-over-year gains.

Funding to China’s startups, in particular, is on the rise after several sluggish years. So far in 2026, startups have raised over $33 billion, per 91Ÿ«Æ· data, already surpassing the total for all of 2025.

The United Kingdom is also looking up. U.K.-based startups have pulled in $16.5 billion so far this year, compared to $19.5 billion in all of 2025. AI and fintech are the country’s leading sectors for investment.

Other mid-sized venture markets are seeing funding levels this year that are on track to be flat or moderately higher year over year, per 91Ÿ«Æ· data. In Europe, this includes France, Spain and Germany.

In Asia, India, Japan and South Korea are also neither way up nor way down. Canada and Australia, meanwhile, aren’t in a slump but also aren’t seeing any major AI-focused funding raised this year.

Maybe it’s a US bubble?

Now that more than three-fourths of startup funding is going to U.S. companies, it seems timely to note that the country is home to only a little over 4% of the global population.

On the tech startup front, it’s undoubtedly an impressive 4%. The U.S. has an unrivaled track record for building leading technology companies, along with the capital and talent to keep on doing so.

That said, certain trends do warrant some serious bubble consideration. The anomalously high concentration of startup funding into American companies is one of them.

Surely many of the countries in which the remaining 96% of people on Earth dwell possess entrepreneurial talent, infrastructure and economic might that could support more than just a measly 12% share of AI startup funding. If one was a betting type, it’s hard not to argue that the odds for that look pretty good.

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This is a weekly feature that runs down the week’s top 10 announced funding rounds in the U.S. Check out last week’s biggest funding deal roundup here.

Big fundraising deals did not take a pause for summer this week. In the U.S., the largest financings went to enterprise software company and blockchain technology provider . The largest deals of the week, however, were for European companies, with Germany’s pulling in $1.4 billion and Finnish space tech company landing $520 million.

1. , $400M, enterprise software: NinjaOne, provider of an IT operations and endpoint management platform, raised over $400 million in Series C extension funding at a $12.3 billion valuation. The Austin-based company said it grew revenue over 70% in 2025 and posted a profit in the first quarter of this year.

2. , $355M, blockchain technology: Digital Asset, a provider of blockchain technology geared for financial institutions, secured $355 million in a later-stage financing led by ’s crypto fund, . Founded in 2014, the New York-based company has raised at least $847 million in known funding to date, per .

3. , $350M, AI cloud infrastructure: Las Vegas-based TensorWave, an AMD AI cloud technology provider for training and inference workloads, closed on $350 million in Series B funding. and led the financing.

4. , $300M, biotech: Beren Therapeutics, a developer of therapeutics for conditions characterized by defective cholesterol trafficking, raised $300 million in equity and debt funding. The financing for the Thousand Oaks, California-based company includes $165 million in debt funding from as well as $135 million in equity investment.

5. , $200M, robotics: Standard Bots, a manufacturer of AI-native industrial robots, picked up $200 million in Series C funding. and were lead investors in the round, which set a $1 billion valuation for the New York-based company.

6. , $125M, genetic medicines: SonoThera, developer of an ultrasound-mediated genetic medicine platform, secured $125 million in Series B funding. led the financing for the San Francisco-based company.

7. (tied) , $100M, medical devices: Tempe, Arizona-based GT Medical Technologies, developer of a form of radiation therapy called GammaTile that is used at the time of brain tumor removal surgery, picked up $100 million in Series E funding led by .

7. (tied) (aka Genspark), $100M, agentic AI: MainFunc, the company behind Genspark, a developer of agentic AI tools for the workplace, reportedly $100 million in Series B extension funding at a $2.6 billion valuation. Investors reportedly included , and South Korea’s .

9. , $99.5M, biotech: Cambridge, Massachusetts-based City Therapeutics, a developer of RNA interference (RNAi)-based medicines, closed on $99.5 million in Series B funding from backers including new investors and .

10. , $85M, tools for the deaf and hearing-impaired: Rylo, developer of an app for hearing-impaired people, raised $85 million in growth funding from , and existing investors.

Outside the US

, $1.4B, robotics: Germany’s Neura Robotics, a developer of AI infrastructure for robots to learn, collaborate and operate across real-world environments, says it secured up to $1.4 billion in Series C funding.

, $520M, space tech: Helsinki-based Iceye, operator of a satellite constellation for monitoring conditions on Earth, raised $520 million in a Series F funding round led by , at a valuation of over $12 billion.

Methodology

We tracked the largest announced rounds in the 91Ÿ«Æ· database that were raised by U.S.-based companies for the period of June 6-12. Although most announced rounds are represented in the database, there could be a small time lag as some rounds are reported late in the week.

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The IPO caps a remarkable journey for a company that raised nearly $12 billion in private investment since its founding in 2002 to become the world’s most valuable venture-backed startup with a most recent private-market valuation of $1.25 trillion. Along the way, SpaceX helped redefine both the space industry and the late-stage venture market.

Its long-awaited offering raised some $75 billion and served as an enormous liquidity event for Musk, who became the as a result, as well as his close friend and confidant of , who now owns a stake valued at more than $68 billion in SpaceX. It’s also a massive and successful exit for early venture and corporate investors including , , , and .

SpaceX’s offering was unconventional along several fronts. Along with the IPO’s record-breaking nature — more than 10x larger than ’s $104 billion offering in 2012 — the company also by setting a fixed price of $135 per share, rather than the traditional approach whereby investors and bookbuilders determine a range based on demand.

Hawthorne, California-based SpaceX is also wildly unprofitable. The company posted a net loss of $4.28 billion in the first quarter of 2026, up more than 700% from a year ago. Revenue totaled $4.69 billion in Q1, up 15% from a year ago. Its megacap valuation means it’s slated to trade at an aggressive premium of 94x revenue.

The SpaceX offering is the first in a lineup of at least three historic IPOs this year, with generative AI giants and openly racing to make it to the public markets in coming months. Altogether, the three IPOs transfer some $3 trillion in value from the private to public markets.

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