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.

AI once again dominated venture funding this week, claiming five of the 10 largest announced rounds, including a pair of billion-dollar financings for AI infrastructure and cybersecurity that led the pack. Investors also continued to back quantum computing, geothermal energy, crypto infrastructure and aerospace startups with large checks. Let’s take a look.

1. (tied) , $1B, cybersecurity: Keyfactor raised a $1 billion private equity round led by. Other investors in the private equity round for the Independence, Ohio-based company included and . Keyfactor provides digital identity and machine identity management software that helps enterprises secure certificates, encryption keys and connected devices. It has now raised $1.21 billion to date, .

1. (tied) , $1B, AI infrastructure: Palo Alto, California-based SambaNova officially announced a long-awaited $1 billion Series F deal at an $11 billion post-money valuation led by. A of other investors joined the round, including ,,,,, and. SambaNova develops AI chips and enterprise AI infrastructure for training and inference workloads. The company has raised nearly $2.5 billion to date, .

3. , $300M, quantum computing: , and co-led a sizable $300 million Series A for South Pasadena, California-based quantum startup Oratomic. A of 16  investors participated in the round, including , , , co-founder , and computer scientist . Oratomic is developing neutral-atom quantum hardware and fault-tolerant architectures designed to accelerate the commercialization of quantum computing, an area that has seen robust venture investment in recent years.

4. , $134M, clean energy: Houston-based Quaise Energy raised a $134 million Series B led by . Additional investors included , and. Quaise is developing millimeter-wave drilling technology to unlock deep geothermal energy, an emerging source of carbon-free power. To date, the company has raised $225 million.

5. , $130M, artificial intelligence: San Francisco-based Prime Intellect raised a $130 million Series A led by . A of investors — many of them prominent Silicon Valley figures — joined, including CEO , �䷡���� , co-founder , CEO and co-CEO . Corporate investors , and also backed the round. Prime is building an open platform for training and deploying AI models across distributed compute networks. It has now raised $200.4 million total, .

6. , $125M, crypto infrastructure: New York-based Gauntlet raised a $125 million Series B, with Japan’s as the sole investor. The company develops simulation, risk management and optimization software for decentralized finance protocols.

7. , $120M, artificial intelligence: New York-based Norm AI secured a $120 million Series C led by at a reported $1.2 billion valuation to expand its AI-powered regulatory compliance platform. The company develops AI systems that translate complex laws and regulations into software to help enterprises automate their compliance workflows. The latest funding included a long list of other venture, corporate and individual backers including , , , and , the chairman of and former president of , which also participated in Norm AI’s deal. The startup has now raised just over $256 million, .

8. , $91M, aerospace and defense: Aerospace continues to draw substantial investor attention, as was the case this week with Houston-based Venus Aerospace’s $91 million Series B. backed the round, which will be used to advance development of Venus’ hypersonic propulsion technology. The company is building engines and aircraft designed to dramatically reduce long-distance flight times while supporting future defense applications. It has now raised $197 million total. An of investors joined in its Series B, including , , , and .

9. , $76M, fintech: Digital asset exchange EDX Markets raised $76 million as institutional interest in crypto trading infrastructure continues to grow. The deal was backed by sole investor , marking the second large crypto funding deal for the Japanese firm this week, along with Gauntlet’s aforementioned round. EDX operates a marketplace designed specifically for institutional investors. It’s not clear how much it raised in previous rounds.

10. , $67.4M, biotechnology: Philadelphia-based Fore Biotherapeutics (previously known as NovellusDx) raised $67.4 million in Series D funding to advance its precision oncology therapies targeting rare cancer mutations. The company is developing targeted treatments for patients whose tumors are driven by specific genetic alterations. led the latest round, which brings its total to date to just over $274 million. , , , and other investors also joined.

Large non-US deals:

Several startups based outside the U.S. also raised notable fundings this week. They include:

• , €411M, fusion energy: Munich-based Proxima Fusion raised a €411 million (about $468 million) Series B funding round to develop what’s poised to become Europe’s first commercial fusion energy power plant. Lead investors in the round include , , and .
• , €200M, workplace tech: led the €200 million ($229 million) private-equity round for Paris-based Skello, which makes HR software for employers to handle tasks such as payroll, scheduling, compliance and employee communications.

Methodology

We tracked the largest announced rounds in the ������Ƶ database that were raised by U.S.-based companies for the period of July 4-10. 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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Our inboxes overflowed with interesting deals in the past month, but we managed to sift through them all to find the five most intriguing ones.

They include a startup that’s simultaneously developing AI models for biology and trying to prevent the threats that stem from those types of advances, a company that says it wants to prevent modern day private markets from the kind of paperwork crisis that shut down Wall Street in the ’60s, and AI agents that can dispatch plumbers and electricians to your door.

$50M for ‘general biological intelligence’

AI has conquered text, images and code. Now one startup wants to do the same for DNA.

San Francisco-based last month emerged from stealth with a hefty $50 million seed round led by , with participation from , , and . The startup said it also received pre-seed backing from co-founder .

Radical Numerics was founded by the team behind , one of the first AI models capable of reading and generating DNA sequences at scale. The startup’s mission is even more ambitious: building what it calls “general biological intelligence,” or multimodal AI models that can reason across DNA, RNA, proteins and other biological data to accelerate drug discovery, cancer diagnostics and biosecurity.

Alongside the funding, the company previewed Omnii, its next-generation genome language model.

The company’s dual focus on human health and biodefense reflects a growing theme in frontier AI investing. ������Ƶ data shows that as models become increasingly capable of designing biological systems, investors have poured tens of millions of dollars into startups that promise not only to accelerate scientific discovery, but also help detect and defend against AI-generated biological threats.

“Evo showed that AI can generate DNA and whole genomes, the next generation of models will go further with the ability to control function, and eventually, create entirely new forms of life,” Radical Numerics CEO said in a statement. “Our multimodal models are already far more capable, and we understand the responsibility that comes with that. The same models that can help cure disease may also lower the barrier to designing harmful biology. These forces are inseparable. Biology will be the most consequential application of AI.”

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$40M for AI that dispatches the plumber

The AI gold rush has reached an unlikely destination: your local plumber and HVAC company. New York-based said last month that it has raised $40 million in new funding: a $34 million Series A led by and a $6 million seed round led by , with Sequoia also participating in the Series A.

The startup is building what it calls an AI operating system for home service businesses, from plumbers and electricians to HVAC contractors. Rather than adding yet another AI chatbot or voice agent, Probook says it aims to replace the patchwork of software many contractors use with a single platform centered on dispatch, arguably the most critical function in the business.

Its software ties together customer intake, scheduling, messaging and outbound communications so technicians spend less time waiting for jobs and office staff spend less time coordinating them.

“I started Probook to solve a problem in my own business,” Probook CEO and co-founder said in a statement. “I grew up pressure washing in upstate New York with my dad. Six summers in the truck. I spent two to three hours of my day driving between jobs. I’d be up on a ladder washing a house and miss calls because I couldn’t hear my phone ringing.”

The company is tapping into a growing trend of vertical AI startups targeting industries that have historically lagged in software adoption, and they’re seeing keen enthusiasm from investors betting that trades such as plumbing, electrical and HVAC represent a massive opportunity to automate workflows and potentially boost profit margins for businesses that still run much of their operations by phone, clipboard and spreadsheet.

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$25M for subterranean warfare

Defense investors have poured billions into startups developing drones and missiles for the sky, tanks and other vehicles for land warfare, and autonomous military vessels for the water.

But a newly funded startup, , is betting the next battlefield is below the ground. The Austin-based startup emerged from stealth last month with a $25 million seed round led by , with participation from a long list of other investors including , , , and , and strategic angels including and founders from and .

Traysar calls itself the world’s first “subterra” defense tech company. Rather than building systems for the skies or seas, it’s developing autonomous platforms that can tunnel underground, map subterranean networks, breach hardened infrastructure and deliver payloads beneath the Earth’s surface. It’s there that it says modern warfare is increasingly being conducted in places like Iran, with its underground nuclear bunkers; Gaza, which has a vast Hamas-built subterranean tunnel network; and Ukraine, which has moved more of its military infrastructure beneath the surface to protect it from aerial drone threats.

The startup, whose founding team includes former engineers from and , is developing two autonomous underground systems. The first is an excavator-type robot designed to navigate, map and breach tunnels from within, giving military operators a way to explore or disable underground networks without sending in troops.

The second is a high-speed burrowing platform that drills new underground access points and can carry payloads — from explosives to sensing equipment — beneath the surface, bringing tunnel-boring technology to the battlefield.

Through the first half of 2026, defense-tech startups globally raised nearly $15.8 billion, by far the largest funding half-year for the sector on record, per ������Ƶ data. Of course, the vast majority of that has gone toward above-ground or marine technologies.

“The global defense industry has a vertical bias: hundreds of billions flow skyward into missiles, missile defense, drones, and counter-drone systems, while adversaries dig in building deeply buried facilities the U.S. cannot reliably strike, and cannot affordably keep disabled,” Traysar in its funding announcement.

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$23.7M for AI growth tools for small businesses

Most AI startups chase large enterprise customers. is betting the neighborhood coffee shop and corner restaurant are the bigger opportunity.

The New York-based startup last month emerged from stealth with $23.7 million in funding, including a $19.5 million Series A led by . , ‘s , , , , and also participated.

Pie says it’s creating an AI-powered growth platform that helps local merchants get discovered  across AI search platforms like ChatGPT and Claude where customers increasingly begin their searches, as well as more traditional marketing channels like Maps, and .

The company also unveiled Front Desk, an AI agent that it says can answer calls around the clock, book appointments and handle customer inquiries when business owners can’t get to the phone.

Founded by former and executives, Pie says it has already reached thousands of businesses through partnerships with industry software providers while operating in stealth.

“Pie is bringing AI to Main Street by starting with one of the biggest pain points for small business owners: finding new customers,” , partner at Lightspeed, said in a statement. “Customer acquisition is a powerful entry point, but the broader vision is to build an AI platform that can support small businesses across more of their daily operations over time.”

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$2M to tackle the private market paperwork crisis

Wall Street once got so buried in paperwork that the shut down every Wednesday . Six decades later, Berlin-based thinks private markets are headed toward a similar reckoning and just raised $2 million to stop it.

The company’s pre-seed round was led by , with participation from and individuals from firms including and .

Founded by two early employees of fund administration startup , Nomerra is building AI agents for the operational work that keeps private capital markets running behind the scenes.

While public markets rely on standardized infrastructure, private markets still depend heavily on emails, PDFs, spreadsheets and disconnected software, the company said. Its software plugs into existing ERP systems, banking platforms and document repositories, then uses AI agents to read documents, reconcile information across systems and complete workflows such as fund accounting, treasury operations and transfer agency work.

At the same time, private markets are expected to swell from roughly $13 trillion today to more than $30 trillion over the coming years, according to Nomerra, even as the industry faces a shortage of qualified accounting and operations professionals.

Rather than replacing existing software, the company says it aims to automate the manual tasks that have traditionally required growing back-office teams.

“Think of how telephone operators used to connect one caller to another by plugging cables into a switchboard,” , Nomerra co-founder and CEO, said in a statement. “Today, the idea that humans once routed every phone call manually seems absurd. Private market operations are at the same turning point. In a few years, people will look back and wonder how any of this was ever done by hand.”

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• 5 Interesting Startup Deals You May Have Missed: A Law Firm Operating System, Building Defense Tech Near The Battlefield, And Cell-Based Milk
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Within the region, U.K. startups gained significant share in Q2, raising more than $10 billion. That marked the third-largest funding quarter for the U.K. on record, and came in at less than $500 million below its peak quarter in 2021.

������Ƶ startup M&A activity also picked up in Q1 and continued that momentum in Q2, even as public-market exits stayed subdued.

Table of contents

• Large rounds drive gains
• H1 2026 up 50%
• UK momentum builds
• By stage
• Looking ahead
• Methodology
• Glossary of funding terms

Large rounds drive gains

Four companies raised venture fundings of a billion dollars or more last quarter, accounting for 25% of all startup investment in the region in Q2, ������Ƶ data shows.

Those billion-dollar-plus rounds were raised by an AI-centric group: -owned AI drug developer , which was spun out of ; green steel production manufacturer ; , which is developing robots for home and industrial applications; and , an AI lab founded by former DeepMind researchers.

However, most of the growth in funding year over year and quarter over quarter was driven by rounds of $100 million and over. The majority of funding — 65% — went to a group of 42 companies that raised rounds of $100 million-plus. Sectors that stood out for these companies include  biotech, quantum, financial services, AI labs, aerospace, semiconductor, robotics and energy.

H1 2026 up 50%

Funding to Europe-based startups in H1 was up 50% year over year to total $42 billion, ������Ƶ data shows. Still, the region’s startup investment for the first half of the year remained well below the 2021 H1 peak, when VC funding in Europe totaled $60 billion.

It’s also drastically lower than the $392 billion raised in North America’s record-setting H1, with that region’s funding up 158% year over year.

Europe’s funding deal count subsided last quarter, but mostly at the seed stage. Late-stage rounds were up a bit, while early-stage deals dipped slightly year over year. (It’s worth noting, seed stage rounds are often added to the ������Ƶ data set after the close of the quarter, so those numbers will increase over time.)

UK momentum builds

The United Kingdom widened its venture-funding lead last quarter, as startups based in the country raised $10.4 billion — not far from the peak in 2021 at $10.8 billion.

The region’s No. 2 startup market, Germany, trailed with $3.2 billion raised by its startups in Q2, and France followed in third place with $2.4 billion. Sweden was Europe’s fourth-largest startup market last quarter, with its companies raising $2 billion.

������Ƶ data shows funding to Europe’s AI-focused companies reached more than $10 billion in Q2 — the largest quarterly amount so far — but slightly below the Q1 percentage, when those companies raised more than half of the region’s startup investment.

By stage

Europe’s late-stage funding totaled $12.1 billion in Q2, up 90% year over year. Large Series C and D rounds were raised by Germany-based robotics developer Neura Robotics; Netherlands-based , which makes inspection tools for semiconductor manufacturing; U.K.-based quantum computing startup ; and Germany-based satellite launcher .

Early-stage funding reached $8.6 billion across 250-plus Europe-based startups last quarter, ������Ƶ data shows. Large Series A and Series B rounds were raised by London-based Isomorphic Labs, London-based AI self-learning lab , Germany-based fusion energy company , London-based semiconductor developer , and London-based quantum processor provider .

������Ƶ seed funding totaled $3.2 billion last quarter, with a billion dollars of that raised by just one company: Ineffable Intelligence.

Other large seed rounds were raised by , a London-based AI lab for science; Italy-based autonomous driving technology producer ; and Stockholm-based defense tech company .

M&A increase

While IPO activity for ������Ƶ startups was muted, M&A showed strong momentum following increased activity in Q1. A total of 154 Europe-based, venture-backed companies were acquired for a cumulative $11.5 billion or more in Q2, ������Ƶ data shows. That includes three companies acquired for more than $1 billion each in biotech, industrial AI and micromobility.

Looking ahead

������Ƶ startup investment has now steadily increased since the fourth quarter of 2024, with increased momentum in the just-ended quarter, driven by larger rounds of $100 million and over. The region’s startup ecosystem shows particular strength in deep tech and financial services as well as the formation of new AI labs, and M&A activity has fueled liquidity for the next batch of startups.

Now the question remains: Will it be enough to keep Europe competitive with the frontrunners, the U.S. and China?

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Related reading:

• ������Ƶ Data: Global Startup Investment Hit Record $510B In H1 2026 As AI Boom Accelerates Funding And Exits
• North American Startup Funding Shattered Records In First Half Of 2026, Driven By AI

Methodology

The data contained in this report comes directly from ������Ƶ, and is based on reported data. Data is as of July 6, 2026.

Note that data lags are most pronounced at the earliest stages of venture activity, with seed funding amounts increasing significantly after the end of a quarter/year.

Please note that all funding values are given in U.S. dollars unless otherwise noted. ������Ƶ converts foreign currencies to U.S. dollars at the prevailing spot rate from the date funding rounds, acquisitions, IPOs and other financial events are reported. Even if those events were added to ������Ƶ long after the event was announced, foreign currency transactions are converted at the historic spot price.

Glossary of funding terms

Seed and angel consists of seed, pre-seed and angel rounds. ������Ƶ also includes venture rounds of unknown series, equity crowdfunding and convertible notes at $3 million (USD or as-converted USD equivalent) or less.

Early-stage consists of Series A and Series B rounds, as well as other round types. ������Ƶ includes venture rounds of unknown series, corporate venture and other rounds above $3 million, and those less than or equal to $15 million.

Late-stage consists of Series C, Series D, Series E and later-lettered venture rounds following the “Series [Letter]” naming convention. Also included are venture rounds of unknown series, corporate venture and other rounds above $15 million. Corporate rounds are only included if a company has raised an equity funding at seed through a venture series funding round.

Technology growth is a private-equity round raised by a company that has previously raised a “venture” round. (So basically, any round from the previously defined stages.)

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.

U.S. startups announced sizable funding rounds at a steady clip during a truncated holiday week, with energy and AI leading the way.

Houston-based energy startup secured the biggest round, a $1.75 billion strategic financing, followed by , a developer of infrastructure for companies running open source AI models, and , a provider of compliance tools for enterprises.

Other big rounds were for companies focused on therapeutics, homebuilding, and even lacrosse.

1. , $1.75B, energy: Houston-based Joulent, a provider of energy infrastructure focused on the demands of artificial intelligence and other compute-intensive industries, raised $1.75 billion in a strategic investment backed by through its arm.

2. , $800M, AI infrastructure: Together AI, developer of an infrastructure layer for companies running open source AI models, secured $800 million in Series C financing. led the round, which set an $8.3 billion post-money valuation for the San Francisco-based startup.

3. , $180M, compliance: LeapXpert, a provider of tools for tracking enterprise communications for compliance needs, closed on $180 million in growth financing. led the financing for the New York-based company.

4. , $135M, AI software development: Redwood City, California-based 8090 Solutions, developer of a platform for building enterprise software with coordinated AI agents under human-led oversight,  picked up $135 million in a round led by 1. The company, founded in 2024, counts prominent startup investor as co-founder and CEO.

5. , $126M, biotech: Boston-based Beeline Medicines, a startup focused on precision therapies for autoimmune and inflammatory diseases, secured $126 million in Series A extension funding backed by , and . The financing follows a previously disclosed $300 million Series A.

6. (tied) , $100 million, professional sports: The Premier Lacrosse League, a men’s professional lacrosse league in North America, closed a $100 million Series E financing round led by and . New York-based PLL said the deal represents the largest capital raise in the history of professional lacrosse.

6. (tied) , $100M, video-based AI: Twelve Labs, a San Francisco-based startup developing AI systems trained on video archives, raised $100 million in a Series B round co-led by and .

8. , $95M, AI for homebuilding: Higharc, a developer of AI-enabled tools for designing homes and managing workflows around homebuilding, picked up $95 million in Series C funding. led the financing for the Durham, North Carolina-based company.

9. , $85M, biotech: Cambridge, Massachusetts-based Flare Therapeutics, a startup targeting transcription factors to develop treatments for cancer and other ailments, raised $85 million in Series C funding led by and .

10. , $65M, AI privacy: Venice, developer of a platform enabling private, surveillance-free access to a wide array of AI models, secured $65 million in Series A funding led by . The round set a $1 billion valuation for the 2-year-old Sheridan, Wyoming-based startup.

Methodology

We tracked the largest announced rounds in the ������Ƶ database that were raised by U.S.-based companies for the period of June 27-July 2. 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.

Illustration:

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, most of the largest U.S. startup funding rounds centered around the sector one would suspect: artificial intelligence. This was true for the week’s largest venture financing, a $1.5 billion Series F for AI inference technology provider , as well as a majority of rounds in the Top 10. Beyond that, the next-biggest area for startup funding was biotech.

1. , $1.5B, AI inference technology: Baseten, a provider of systems software to run AI applications workloads, raised $1.5 billion in Series F funding, its fourth fundraise in 18 months. , , , and co-led the round, which set a $13 billion valuation for the San Francisco-based company.

2. , $1B, digital marketing: AppsFlyer, a San Francisco-based provider of data analytics with digital marketing as a core use case, reportedly secured more than $1 billion in a Series E funding round at a post-money valuation of $2.7 billion. Backers reportedly include , , and .

3. , $650M, AI inference technology: San Francisco-based Groq closed on $650 million in new funding led by and that it says will be used to scale its AI inference cloud technology and infrastructure. The investment comes just over six months after an acquihire-type transaction in which hired away its founder and key team members and licensed its technology.

4. , $330M, ophthalmic therapies: Ollin Biosciences, a developer of therapies for vision-threatening diseases, picked up $330 million in Series B funding. and led the financing for the Austin-based company.

5. , $320M, foundational AI: General Intuition, developer of a foundational AI model based on gameplay, secured $320 million in Series A funding at a $2.3 billion valuation. led the financing for the New York-based company, while backers including and participated.

6. , $250M, government software: Peregrine Technologies, provider of a platform used by public safety agencies and other government entities, secured $250 million in Series D financing. , , , , and led the financing, which set a $6.8 billion valuation for the San Francisco-based company.

7. (tied) , $200M, risk intelligence: Palo Alto, California-based Quantifind, developer of a risk intelligence platform for financial crime detection and national security operations, closed on $200 million in growth financing led by .

7. (tied) , $200M, foundational AI: San Francisco-based Mirendil, a frontier lab building systems that excel at AI R&D, says it raised a seed round of $200 million led by and . The startup also counts as a backer.

9. (tied) , $190M, AI infrastructure: AI networking infrastructure startup Upscale AI raised $190 million in Series A extension funding, bringing total financing to $500 million. led the round, which set a $2 billion valuation for the Santa Clara, California-based company.

9. (tied) , $190M, biotech: San Francisco-based Osanni Bio, a therapeutics platform focused on ophthalmic therapies and other treatments, secured $190 million in Series B funding led by .

Large non-US deals:

The week also brought some large ������Ƶ rounds:

, $569M, defense tech: Berlin-based defense tech startup Stark reportedly raised $569 million in a financing led by and .

, $546M, insurance: Paris-based health insurance startup Alan secured $460 million in new investment in primary and secondary equity led by .

Methodology

We tracked the largest announced rounds in the ������Ƶ database that were raised by U.S.-based companies for the period of June 18-26. 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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Those were the unsurprising findings of a ������Ƶ analysis of U.S. startup acquisition outlays in 2026. So far this year, acquirers have spent at least $119.8 billion buying private, venture-backed companies, on pace to exceed 2025’s record-setting tally.

For 2026, however, about half of total M&A spending on U.S. startups comes from a single deal: ’s $60 billion of AI coding tool Cursor and its parent company . SpaceX first announced an option to the company in April and consummated the deal after its IPO this month.

The Cursor purchase represents the largest startup acquisition of all time, nearly double the size of the prior frontrunner, ’s purchase of for $32 billion. After that, the next-biggest startup M&A deal was ’s $19 billion acquisition of in 2014.

Other big M&A deals

While other 2026 startup purchases weren’t setting records, many of them were still on the historically large size.

To illustrate, we used ������Ƶ data to put together a list of the 10 largest disclosed-price U.S. startup acquisitions this year. 1 The bottom nine range from $2 billion to $7 billion.

Biotech was a standout

Biotech was especially big. This is due in large part to , which announced in April that it was acquiring , a developer of gene therapies with a particular focus on cancer treatment, in a deal valued at up to $7 billion in cash. Per ������Ƶ data, the high end of the purchase price represents the largest acquisition of a venture-backed biotech company in years.

Lilly was also the acquirer in two other deals in our Top 10 ranking. The pharma giant bought , a developer of RNA therapeutics, for up to $2.4 billion, and , a developer of blood cancer therapies, for up to $2.3 billion.

Overall, half of the 10 largest deals this quarter were biotech transactions. However, in most cases the number represents the maximum potential acquisition price, which will require the acquired company to meet pre-determined milestones, typically around clinical results and commercialization.

Brex, Modular and more

Outside of biotech and, of course, Cursor, the next-largest acquisition was ’s purchase of business credit card and account provider for $5.15 billion. It’s followed by ‘s acquisition, announced yesterday, of AI chip startup for $4 billion.

Further down the list is ’s 2 acquisition this month of , a provider of AI-enabled customer experience tools, and ’s purchase of , an industrial AI platform, each at $3.6 billion.

With the second quarter winding to a close, we wouldn’t rule out the likelihood of another big deal making headlines in coming days. Even if that doesn’t happen, however, it’s already clear that 2026 is shaping up as a big spending year for startup M&A.

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led the financing, which included participation from , and existing backers. The raise brings the company’s total funding to more than $76 million since its 2018 inception and values it at $127 million post-money. That’s more than double the valuation of its previous funding round — a $25 million Series A that closed in December 2023.

“Healthcare has spent decades generating enormous amounts of patient data without a reliable way to make that information usable,” said xCures CEO in an exclusive interview with ������Ƶ News. “We’re changing that.”

Venture investment in healthcare and biotech companies that have an AI bent has been on an upward trajectory in recent years. As of June 22, investors have put an estimated $8.5 billion into seed- to growth-stage funding for companies in AI-powered health tech categories, according to ������Ƶ data. In 2025, funding to the sector across all stages $15.8 billion. This year’s total is already nearly as much as the $8.6 billion raised in the category in all of 2024.

Pivoting to solve a problem

Founded in 2018 as a spinout from by , xCures initially launched to provide decision-support tools for patients with advanced cancer. At its inception, the company focused on patients with Stage 3 or Stage 4 recalcitrant cancer diagnoses, where standard care options were exhausted.

While working with thousands of patients across the country in a direct-to-consumer setting to build its initial model, the company encountered a systemic bottleneck.

“What we learned in the process was that the decision-making was hard,” Newton said. “These are complicated things, but doable. But the even harder thing was to get our hands on the data and information about the patient that we needed in order to give them the advice in the first place.”

At the time, patient records were arriving at the company in boxes and over fax machines. This logistical hurdle prompted xCures to pivot to build the underlying infrastructure needed to connect directly to national healthcare interoperability networks. Today, xCures hooks into these electronic exchanges on behalf of its customers, shifting its primary focus to structuring what Newton described as the industry’s “dirty data.”

“The data in those medical records is incredibly dirty, so it’s duplicative. There are pictures of things, scans of things. There are errors that are caused because it’s all human entry,” Newton explained. “There’s lots of narrative information, and we turn it all into something that basically is clinical intelligence or the clinical clarity an organization needs to make its next decisions.”

Creating a ‘clinical clarity engine’

Patient information remains scattered across thousands of labs, hospitals, imaging centers and electronic medical records, often arriving as unstructured documents that are difficult to use in clinical workflows. This is where xCure can provide a differentiated experience, according to Newton.

“They’re [competitors] really in the transport business … moving data from Point A to Point B,” he noted. “We think of our product as the executor’s clinical clarity engine. We’re in the business of taking that transported data and making it into something that’s actually instantly useful, versus just moving it from one space to another.”

The xCures Clinical Clarity Engine, he said, solves this by integrating capabilities to generate decision-ready checklists from automated patient histories, backed by evidence-grade data. Newton estimates that the engine is three to five years ahead of anyone else in the market. To date, xCures has processed more than 300 million medical records sourced from more than 550,000 healthcare locations nationwide, supporting clinical decisions for millions of patients across the U.S., per the company.

To manage this volume without incurring the extreme processing costs associated with running massive, unstructured files through generic models, xCures utilizes a variety of AI, combining its own home-built machine learning models with commercial frontier models from existing vendors. The company manages these tools through a proprietary governance framework.

“We really see it as the harness for … the process for applying AI, and how we make sure that the tasks that we’re asking the AI to do are appropriate and well-governed, and that the rules of engagement are really clearly defined,” Newton said.

High growth and enterprise adoption

This technological approach has driven impressive traction. Operating on a usage-based SaaS model with committed caps, xCures grew from roughly $3 million to $10 million in annualized recurring revenue in 2025, according to Newton, and it’s on track to break $20 million in 2026.

While xCures achieved cash-flow breakeven last year, the company has intentionally entered a capital-burn phase to build its team for its 2027 business pipeline, he added.

The startup’s enterprise customer base consists of 25 clients, including lab diagnostic companies such as , and . Large hospital networks use the tool to “instantly” generate patient histories for operating room scheduling, screen for comorbidities and estimate operative times ahead of surgeries. The engine is also used by telehealth providers lacking robust Electronic Health Record architectures, as well as by Medicare Advantage plans seeking to automate population risk stratification, prior authorizations, medical-necessity documentation and administrative appeals.

Solving healthcare’s most expensive grunt work

Ultimately, Newton believes that reducing the immense administrative drag built into the American healthcare system is crucial.

“Companies like xCures really reduce the administrative burden and represent the fastest path to realizing value in healthcare for everybody who’s involved in it,” Newton said. “This idea that we can use AI not to do things that doctors should do, but just to make it all better, easier, faster, cheaper and better for everybody involved … there’s just a lot of, like, grunt work that you should do that’s really expensive, and so that’s probably the most immediate opportunity.”

, partner at Innovius, wrote via email that his firm backed xCures because it was impressed with its ability to “locate, extract, and normalize messy data across thousands of incompatible sources.” By applying real clinical context to surface exactly what matters, the investor noted that Mika Newton and his team are successfully “building the foundational AI data layer that will power the entire healthcare industry.”

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The Menlo Park, California-based firm highlighted its early investment in , which last month overtook rival as the top-valued frontier lab in the world with a staggering $965 billion valuation. While Menlo Ventures’ investment in Anthropic’s was not its first bet on artificial intelligence, the firm described it as its “flag-planting moment.”

“We made our first investment in Anthropic in 2023, when the company was pre-product, pre-revenue. By then, ChatGPT was a household name, and many believed the LLM race was already decided. We saw it differently,” the firm wrote in published Tuesday. “In and his founding team — arguably the most accomplished researchers in the field — we saw the rare mix of technical depth and clarity of purpose that defines a category leader. We were convinced there was room for another independent foundation model company, that Anthropic was the team to build it, and that an investment in Anthropic could anchor our broader AI strategy.”

The firm went on to lead Anthropic’s the following year.

“That early relationship gave us a rare vantage point on the model layer and on the infrastructure, workflows, and application opportunities forming around it,” the firm said this week.

Two new funds

The firm’s new capital is across two funds: , earmarked for seed and Series A startups, and , a growth fund for Series B and later startups that are “already pulling away from the pack and on their way to becoming the breakout names of the AI era.”

Along with Anthropic, other notable Menlo Ventures investments over the years include , , , and . Anthropic, which has filed plans for a 2026 IPO, would be the largest exit to date for one of its portfolio companies by far, with an expected IPO target of $1 trillion or more.

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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 ������Ƶ.

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 ������Ƶ 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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“Silicon Valley has done very well with software, but while software was eating the world, they forgot about silicon,” Barrett told ������Ƶ News in an interview.

The firm recently closed a $475 million fund focused on investing in deep-tech startups at seed and Series A. In the decade-plus since its founding, it has built its investment thesis around the idea that breakthroughs in science and engineering — not just software — would create the next generation of valuable companies.

With demand surging for compute, semiconductors and energy, Barrett argues the rest of the industry is now catching up. “We’ve been at it for more than a decade,” he said. “In recent years, as AI is eating software, people are scrambling back to recognize that the energy, semiconductors and infrastructure they operate on all need capital too. We’ve been operating in that regime for a very long time.”

Barrett is originally from Australia and came to Silicon Valley in the 1980s. He’s been coding for 50 years, he said, after developing an early and deep respect for science and engineering as the child of two engineers. His childhood was steeped in punch cards, draftsmen and drawings of control systems and machinery, he said.

“Science lets you follow breadcrumbs from prehistoric plumage to semiconductors. One principle can be applied somewhere orthogonal and create extraordinary value,” Barrett said in a lengthy interview with ������Ƶ News.

Barrett went on to found video game developer , joined to build the entertainment browser acquired by , and was subsequently CTO at prior to co-founding Playground Global in 2015.

Playground Global operates a lab in the former Palo Alto Research Building in Palo Alto, California. The location hosts 350 people, including those working at its portfolio companies and others with adjacencies working from the lab.

On a recent visit to the warehouse, I saw various models of robots, materials for aerospace construction, and a model of building powerful lasers to increase the speed of semiconductor manufacturing. The quantum computing startup , a Playground portfolio company, moved in when it had three employees and moved out when it reached 90.

The firm has four general partners. Along with Barrett, they are , the former CEO of and who architected CPUs at Intel that helped computing take off at scale, and who joined the Playground team last year as a general partner specializing in semiconductors; , who has made many investments in biotech, including ; and co-founder , who led the investment in .

What follows are highlights from a wide-ranging interview with Barrett that covered topics including sovereign technology, the need to invest in companies that operate on the physical plane, and why he believes putting data centers in space is stupid.

This interview has been lightly edited for clarity.

Gené Teare: What is the thesis for Playground Global?

Peter Barrett: It is about reducing new results in science and engineering into commercial and societal value. That means operating at the boundary between computation and the physical world. We are very interested in new capabilities of computation driving civilization forward, and that inevitably means operating in the same physical plane that we live in.

We’re seeing in our data a huge amount of funding going into space, semiconductors and robotics. It seems as if the whole venture industry has pivoted to this much broader array of companies. Do you see that as a good thing?

Barrett: We lost a lot when people weren’t investing in things that strike us as important. It is good that there is capital chasing the things we care about and that have real consequence.

You can’t spin up a deep-tech practice overnight. You still need domain expertise. You still need to understand why investing in nuclear reactors is good, and why data centers in space are preposterous.

Silicon Valley hasn’t been very efficient with much of the capital it’s deployed over the past decade or so. But I do think it’s good that people recognize that software may be eating the world, but you can’t eat software. We have to operate in the physical layer.

Do you think Silicon Valley gets more efficient?

Barrett: We need to do the work. You develop the instincts and the platform to deploy capital efficiently into these places.

It’s important that people recognize there’s this unprecedented funnel of technical change. AI is an early indicator of it, but we have technologies like quantum. We know how to produce computation using things beyond transistors and semiconductors.

We’re scratching the surface in terms of AI models. We’re right at the beginning of an explosion and renaissance in materials science driven by things like quantum computing.

Now would be the time — and candidly, I feel the imperative — that anywhere there is science and capital, it needs to be turned into value, especially in liberal democracies, because the despots are doing a pretty good job of it. It’s incumbent on us to stay ahead.

We’re in the DOS age of AI. We’re scratching the surface, both in terms of the models we make and the hardware we run them on.

Now would be the time for people to write checks into things that are sensible and valuable. We spent a lot of time on NFTs. How are we doing with cancer? How are we doing with our most difficult challenges in terms of healing and feeding the world?

There are lots of new degrees of freedom that could take capital and turn it into value.

Do you think deep tech fits the venture thesis, despite the long time horizons and the amount of capital it requires?

Barrett: The long time horizons certainly exist. If you’re building PsiQuantum, we’re building million-qubit quantum machines. That takes billions of dollars and a decadal effort.

The corollary is that we’ve had hardware exits in two years. The timelines for hardware aren’t necessarily that different from software.

Therapeutics naturally take a longer time, because of clinical trials. But we’ve also seen exits there. One of our companies tested half a million drugs in a single animal and created a new corpus of AI input for building models to create therapeutics. That’s not a decadal effort — that’s a handful of years before exit.

We try to craft a portfolio that’s a mix of tactical and strategic. Some of these companies get to hundreds of millions in revenue within a few years. Others, like PsiQuantum or , may take a decade to reach full entitlement. That’s part of portfolio construction.

The biology company you mentioned — what’s its name?

Barrett: . It did the largest pharma deal of its kind last year with . The deal could be worth $2 billion on the back end.

It’s a unique mechanism to create giant AI training sets by using physical systems — using animals and in vivo testing to create that dataset. It affords the ChatGPT and biology moment, where you can have large enough training sets to build big models.

You describe the firm as investing somewhere between improbable and impossible. Are there companies that really fit that thesis when you first met them?

Barrett: When we first met PsiQuantum, they were talking about building a machine which was 10,000x the state of the art. Using then-current technologies, it would have been the size of the Sierra Nevadas.

They required exponential improvements in both hardware and software, and they’ve achieved both. It’s the size of a warehouse, not a laptop.

The work we’re doing in biology, materials, quantum algorithms and superconducting logic — which will replace transistors and semiconductors — all of these things sound like science fiction, but they’re much closer to improbable. In many cases they’re entirely practical before we invest; they just seem improbable to those unfamiliar with the domain.

There are things that are not impossible but are still really dumb — data centers in space, small modular reactors (SMRs), or fusion. The physics may work, but the economics don’t, or the timelines don’t align.

I’m disappointed we haven’t invested in anything that turned out to be more impossible than we thought. None of our portfolio companies failed because the technology didn’t work.

We’ve had capitalization failures. We flew hydrogen planes. We’ve built things that were thought to be virtually impossible that turned out to be straightforward. They may have missed their market or may have been unable to raise the capital to continue.

I want to do something where the technology doesn’t work, and we’ve yet to do one of those.

Is there a company you missed out on where it looked impossible and you wish you’d invested?

Barrett: I wish I hadn’t taken ‘s word for it when was a non-profit.

We haven’t missed many. As the roadmap developed, we wish we had been earlier in a couple of categories that are really interesting. But overall, we haven’t missed too many.

In which sectors or companies have you invested where the time horizons have shortened due to AI?

Barrett: Adding Pat Gelsinger to the team reflects an interest in scaling semiconductors along various dimensions, including energy efficiency and how power is delivered.

We do everything from nuclear reactors all the way through to transmission, energy conversion outside the data center, inside the data center, under the chip, what kinds of chips you’re running, what models run on top of those chips, what architectures those chips are made from, and what materials those chips are made from.

At every layer of the infrastructure — optical interconnects, memory systems — we have a best-in-class company at every point. We built the first AI accelerator a decade ago, and we’ve broadened that to encompass the entire ecosystem, from the creation of electrons to how they expend themselves doing useful software work.

There are bubbly aspects of the current AI moment, but the bubble is being modulated to some degree by the unavailability of energy.

We’re in the DOS age of AI. LLMs are embarrassingly incompetent compared to what comes next, but we believe in the durability and growth of AI, and are making investments in model architectures and the ways AIs are trained. We see demand for compute, energy and infrastructure continuing to grow.

We have technologies that can reduce general-purpose compute workloads by 100x to 1,000x over state of the art. We believe we know how to make the energy and deliver it. We know how to connect these systems.

So quixotic pursuits like putting data centers in space are unnecessary.

Talking privately to hyperscalers and Fortune 50 companies, they all say there is way more demand for AI in its future incarnation than exists today. It’s incumbent on us to figure out how to do it 100x, 1,000x or 10,000x more efficiently, because that demand turns into GDP growth and better solutions to our hardest problems.

What are the companies in energy and semiconductors that you are betting on?

Barrett: One example is the wild superconducting logic company . We can make things that are post-semiconductor and post-transistor, with devices that switch five orders of magnitude more efficiently than transistors.

They operate at cryogenic temperatures, but quantum computers do that, and our extreme ultraviolet lithography system does that. The future of computation is cryogenic. Even after you pay to make it cold, you’re still 100x to 1,000x more energy-efficient on compute.

This technology has been around since last century, but it’s mainly been used for secure signals intelligence and radar applications. We’re generalizing it for compute.

Another example is . People talk about SMRs, which are a physics solution to a financial problem, or fusion, which is still decades away. Alva instead uprates the existing nuclear fleet to get hundreds of megawatts out of each unit by replacing 1970s steam generators with a 2020 steam generator.

We can deliver power in a handful of years. No new fuel, no new regulatory path, and a business model that makes sense for operators. We can put gigawatts onto the grid without moving a fence line of an existing reactor and without upgrades to the electricity grid.

We know how to make AI training wildly more efficient. We know how to train different kinds of AI models that we’ve been unable to train.

The last supercomputer at uses something unlike a CPU or GPU to run existing software. We’ve been running software the same way for 70 years, but there are other ways, with dataflow architectures. We have a company doing that — [].

The degrees of freedom from materials, systems, code and models have never been greater. We’re exploring all of them. But most require rolling your sleeves up in the physical world.

LLMs feel like brute-forcing something — like a drunk looking for keys under the streetlight. We’re pushing more and more into that, and I think that’s a dead end. We know other ways of moving forward.

Are you seeing new model companies, separate from LLMs, that are going to solve things?

Barrett: Our brains are not LLMs. They’re not transformers. Transformers are effective, but they are one of a long line of soon-to-be-extinct models that get replaced by something that works better.

That millionfold gap between our brains and GPUs is an architectural gap. Meat is much worse at computation than hardware can be, so biology shouldn’t be better.

Physics allows a million times a million more efficiency, and we should start chipping away at that.

Intelligence is useful and can be pressed into service against basic things like photosynthesis. Plants were invented by accident of evolution 3 billion years ago. They’re pretty, but not efficient. They shouldn’t be green; they should be black. We know how to make photosynthesis twice as efficient, and probably 5x more efficient.

We’re not stuck with the physical constraints of our technology or of nature. Nature is beautiful, but cobbled together by a process that we can have agency over.

All the materials that operate our civilization are discovered, not designed, because we can’t design things we can’t simulate. Our best computers cannot simulate the quantum nature of nature. That’s about to change.

We’re stumbling around in the dark, relying on serendipity and the occasional magical material. Whereas we can construct any number of materials with magical properties that are currently hidden from us by our inability to simulate the quantum mechanical processes that animate chemistry.

We are right on that threshold of unlocking all of these dimensions. And at the same time, we’re putting money into NFTs, the metaverse and other things that will come and go, without anybody ever caring.

Are you talking about the mix of quantum with biology and model-focused companies?

Barrett: Quantum allows us to directly design materials, directly explore the method of action of drugs, and directly design drugs.

AI has a role to play in biology and understanding structures we can measure. We think there are quantum wet labs where we can measure the performance of small-molecule drugs against models of nature and then verify in nature.

We don’t know how many things that animate our industry actually work. We don’t know how Tylenol works. We don’t know how the Type II superconductors we’re building fusion reactors out of work. We know that if you take iron and nitrogen and arrange them in a certain way, they produce magnets stronger than rare earth magnets, but we don’t know why.

There are mysterious things we’ve stumbled across that hint at an Aladdin’s cave locked behind a wall of computation. That wall is coming down.

Which sectors do you think are going to take a lot longer to come to fruition?

Barrett: Civilization will operate on fusion eventually, but right now the only reactor that works using gravimetric confinement is the sun. I think that’s a long way off.

Data centers in space are stupid. You can’t operate a gigawatt data center in a thermos. We have terrestrial answers to those questions that we should pursue.

I’ve always been a detractor of self-driving cars, which are starting to work. Now we need an economic model that makes them sensible and doesn’t drown our cities. The problem with transportation in cities is not the degree of autonomy. If we cared about traffic deaths, we’d worry about roundabouts.

There’s also nonsense with NFTs and the metaverse which have sopped up enormous amounts of capital. Small amounts of capital using these tools against our most difficult diseases would yield results. Small modular reactors are an unwarranted innovation.

There are lots of things that, at first blush, seem good and valuable, but there are far better solutions that are simpler and more imminent. We need to be practical about where the money goes.

There was a company that just joined the ������Ƶ, valued over $1 billion this past month, doing orbital data centers. Are you saying this whole category doesn’t make sense?

Barrett: To his credit, will show you a picture of what a 100-kilowatt data center looks like, and it’s bigger than Starship. A 100-kilowatt is a small rack from that is human-sized.

The arguments are that there are a lot of renewables in space. But there are a lot of renewables on the ground too. North Western Australia has solar and wind that are 70% naturally firm, and on the ground, so you can build things on it.

Put a data center in North Western Australia, which we are doing. We have a renewable site 35x the size of Manhattan.

Energy generation and compute in space is a nonstarter because space is not cold. You’re building things in a thermos and need to get rid of heat. A single human-sized rack is 100 kilowatts, which is about the size of the International Space Station’s radiators and solar panels.

Starship has yet to actually put anything in orbit. It’s made some fireworks, which are pretty, and it’s a beautiful thing. is an amazing company because of Falcon 9 and Starlink. But data centers and power generation in space makes no sense.

We know how to build arbitrary amounts of energy generation on the ground with very safe, very large nuclear reactors. We’ve been doing it for decades.

For all the talent and genius rattling around the Valley, we do spend money on silly things.

Do you think now is the most exciting time to be investing, or have some of those investments already been made and are going to come to fruition?

Barrett: We’ve already made investments in things on a really steep trajectory.

Snowcap will take a decade before we’re building GPUs with that technology, but we’ll have commercial product from them next year. We’re getting better at early, undeniable signals.

PsiQuantum is a long journey, but some things just take that amount of time.

X-Lite seems like a ridiculously long journey, although we’re building the prototype facility now, and it received the first money from the new CHIPS Act.

Some hardware companies making silicon or systems are getting significant revenue in a handful of years.

There’s a sleeper in Fund I. Its first trick was to make MRI machines 100,000x more sensitive, and they’re shipping those. In the background they’ve also been developing that core physics to build a new quantum computing modality. So we actually have two quantum computing companies in Fund I.

Even though that’s a 10-year-old company, there are about to be two companies, one of which will be a unicorn virtually overnight.

There are wild things bubbling under the surface that people are going to wonder where they came from.

Companies like — the only co-packaged optics on TSMC — we’ve been working on that for a long time. Now people are waking up to silicon photonics and co-packaged optics.

There are also stealth companies that are indistinguishable from magic. Some of those will come out of stealth this summer.

Is there anything we haven’t chatted about that you think is worth noting?

Barrett: It’s a sobering note, but globally there is a need and desire for sovereign capability in tech — in Western Europe, Australia, Canada and elsewhere.

There are extraordinary pools of capital, pension funds and Australia’s superannuation fund. Given the things we can invest in, globally the West needs to do a better job translating that capital into societal and economic value.

The safety and durability of liberal democracies depends on creating wealth and staying ahead.

We see a resurgent desire to do that in Europe and Australia. Around those pools of capital, there’s ambition. We need to drive that ecosystem globally, not just in the U.S.

The pace of innovation in Ukraine, driven by need, is indicative of changes that can be made in parts of the world less friendly to the tenets we hold dear in liberal democracies.

We can’t operate under the assumption that everybody clever lives in Palo Alto or that we can only invest in things we can drive to. We need to deploy capital globally, and we do. We’re going to do more of that.

Do you feel encouraged by the amount of infrastructure build-out that’s going to happen over the next few years? It feels like it will create a boom in all sorts of technologies because the drive for efficiency will become much stronger.

Barrett: LLMs are not the end. We’ll run LLMs on these data centers initially, but we’ll run their descendants and other more useful things on these machines and on quantum machines.

It’s going to be hard to overbuild because computation is incredibly useful. There’s no upper bound. We’re not in a Malthusian zero-sum game for resources.

We know how to make everything more productive. We know how to grow GDP arbitrarily large. But we need food, energy and medicine there, and we need to normalize the distribution of wealth.

There is unbounded abundance we can unlock if we spend capital on the right things. We know how to do much more of that than people suspect.

The fact that sensible people are considering data centers in space indicates they’re not paying attention to the things we already have in hand that can move the needle.

We do need compute in space. We need AIs in space, sensing in space, and Starlink is great. But we need to use technologies that make sense, not try to make skyscrapers out of toothpicks.

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