Meta is building dozens of massive tents at campuses across the US, sticking billions of dollars of chips inside, and powering them with off-grid turbines.
The AI race has officially entered its Mad Max phase.
Over the last month, I reviewed hundreds of documents and satellite images for Cleanview's latest report on behind-the-meter data centers. Meta's data center strategy, which is very visible from space, was one of the weirder approaches I came across.
Mark Zuckerberg recently ditched the data center designs that Meta had perfected over the last decade and told his team to stick tens of thousands of chips in tents outside their data center in New Albany, Ohio. Each of these chips costs about $60,000. Zuckerberg plans to stick billions of dollars worth of them in the tents.
The strategy has helped cut the time to build compute in half. The first five buildings at Meta’s New Albany, Ohio data center took between two and three years to build. Meta started building five ~125,000 square foot tents between April and June of 2026, according to city permits. Satellite images show the structures have all been built.
To power those "rapid deployment structures", as they are officially named, Meta signed a 10-year deal with Williams to build a pair of 200 MW off-grid power plants. Those power plants began construction about a year ago and are nearly complete.
Meta is using the same strategy to build a data center in Tennessee, bringing the total count of tent data centers to three.
Strategies like this are part of the reason behind-the-meter data center capacity is growing so quickly.
In Cleanview's report, I found that there's currently about 2 GW of BTM capacity online today. By the end of the year, it will likely be 3 GW—equivalent to three nuclear power plants. By the end of 2027, it could be as high as 13 GW—more than the power demand of NYC.
I've been talking to a lot of reporters about this research. When I told one reporter about these tents and other companies powering their data centers with jet engines, he said, "It's like a scene out of the movie Mad Max."
@DeItaone Sure, CIOs around the world are going to be desperate to use the enterprise AI cloud offering of a company in a bunch of child porn lawsuits, sure, $352B EBITDA (adjusted* see notes** see Elon disclaimers***)
Sure, GoogleMaps is cool but not half as cool as ORBIS. The Stanford Geospatial Network Model of the Roman World allows you to check travel times during Roman times. You can choose your mode of travel too! Source: https://t.co/zgVnhUdbKh
@robertgraham Conspiracy theory? Have you actually looked at the data on how much tax billionaires pay as a percentage of their net worth? Why are you stanning for them?
Monthly VC/LP debrief.
What I actually saw in May 2026:
1/ SF is in full gold rush mode again, but history says the current winners won't stay on top forever. Every dominant technology eventually gets surpassed – newspapers, telecom, cable, Google in ads, IBM in computers. In AI the same pattern is already playing out: compute will hit walls, chips get dramatically more efficient, new energy sources emerge, and entirely new model architectures appear. The people feeling left behind today may just be early in a much longer cycle. (h/t @TurnerNovak)
2/ The largest $10B+ funds went from 140–150 collective early-stage deals per year in the SaaS era to 370–400 in the AI era. But the concentration is at the top of the market – top-decile rounds, known founders, proven operators. @kevinhartz calls it "option value": a small check today for the right to lead Series A tomorrow. The average seed round remains territory for EMs.
3/ We might be entering a Zombie VC era. ~85% of 2017–2018 vintage funds still haven't returned 1x DPI after 7–8 years. Median DPI sits at $0.34 on the dollar, while median IRR for the same cohort looks respectable at 11.6%. Paper returns hide the reality. The liquidity window opening over the next two years will be the moment of truth for most of these funds.
4/ @SpaceX IPO might be the single largest DPI event in VC history dropping into the lowest-distribution moment in venture capital history. @foundersfund alone, with an early $20M check in 2008, could return $60B+ (~3000x). When that capital hits LP accounts, it needs to be redeployed and that will circulate a new wave of fundraising for the same funds and fresh allocations from LPs who finally have liquidity to work with.
5/ The @cerebras IPO was the first real data point on crossover returns after two years of everyone writing off the model – both early-stage VCs and late-stage crossover funds made money on the same company, and LP conversations shifted from "do we have any exposure to the winners" to "how do we get into the next one." The same strategy that was declared dead in 2022-2023 got fully rehabilitated by a single exit. (h/t @MeghanKReynolds)
6/ Monte Carlo across 1,391 VC funds: concentrated portfolios (15 companies) and diversified ones (100 companies) produce the same average fund return – 2.44x. But compounded across multiple vintages, diversified wins: 2.25x vs. 1.78x. Concentrated funds carry more variance per fund, and variance drag compounds against you over time. The extreme outcomes (15x+) are almost exclusive to concentrated funds but the probability is tiny either way. (h/t Steve Kim)
7/ EM activity is showing the first real pulse in years. @cartainc logged 78 new US venture funds in the $10M–$100M range in Q1 2026 – a 34% jump from Q1 2025. Still well below the 2022 peak of 147, but the post-winter bottom might finally be in. The managers raising right now are doing it without a favorable macro, without easy LP recycling, and into a market where mega-funds are more active at seed than ever. (h/t @PeterJ_Walker)
8/ 76% of all EM-focused FoFs are American. The entire addressable market for a Fund I or Fund II isn't 132 FoFs – it's roughly 33. The other 100 exist, but Classic and Government-Led FoFs structurally can't anchor an early-stage vehicle: the check size doesn't justify the overhead, and a pension board can't be sold on a first-time manager without a track record. Geography and fund type filter out 75% of the market before the first meeting. (via @murphcapital)
9/ The 10-year fund is structurally mismatched with the assets mega-funds are holding. @SpaceX has been private for 18 years. @stripe for 15. For managers at that scale, @sequoia's move makes sense – open-ended, permanent capital, indefinite horizon. For small funds the logic runs the opposite way: the 10-year horizon enforced as a hard constraint, secondaries at Series C/D as the default exit, actual distributions on schedule. (h/t @credistick)
10/ There are only 3 positions that matter in a startup's cap table story: first investor, most helpful investor, biggest investor. Biggest is reserved for ~10 megafunds. First requires conviction most managers don't have – and LP preferences for concentrated portfolios often push against it structurally. So 90%+ of firms end up competing for "most helpful," which is why every pitch deck has a platform slide and every GP talks about their right to win oversubscribed rounds. (h/t @arian_ghashghai)
Every month I track new fund launches, LP events, market reports, and what's actually moving in VC/LP.
All of it in the @murphcapital newsletter: https://t.co/Wi8pAGQHLB
When we first met Jean and Patricia, @BubbleRobotics did not exist.
Jean was in Milan, Patty was in Zurich. They did not know each other yet, but they were both looking for the same thing: a cofounder to build a deeply technical, ambitious company with.
In October 2024, they joined EF. They met at our kick-off weekend and teamed up immediately.
A few weeks later, after exploring multiple ideas in agriculture and recycling, they landed on the ocean.
That became Bubble Robotics: autonomous robotic systems that can stay at sea, inspect offshore infrastructure, monitor critical assets, and collect underwater data continuously.
From ideation at EF, to San Francisco, to building their first robot in a pool, to raising a $5M pre-seed round, it has been incredible to watch the pace of this team.
Proud to have backed Jean and Patty from the very beginning.
@gurgavin Post earnings sell offs happen to all public companies, extremely frequently. Sometimes it's just pure profit taking. If you're an investor who bothers to look at earnings numbers and projects forwards, it's noise