Welcome back to The Hidden Layer. I’m Ian Krietzberg.
I had a blast
talking A.I. bubble chatter early this morning with CBS News’s Errol Barnett, a conversation that feels more timely with each passing day and each additional dollar of debt that enters the A.I. fray.
Today we’re talking outer space—as in, tech companies’ literal moon-shot plans to move A.I. chips off-planet. Plus, I’ve got some exclusive funding news for a small enterprise A.I. startup that’s offering something more interesting than a chatbot, and a look at whether AMD
has an OpenAI problem.
Also discussed in this issue: Ashley Pilipiszyn, Sarah Friar, Hugh Barnaby, Sam Altman, Elon Musk, Bianca Anghelina, Pegah Ebrahimi, Stefano Ermon, Nvidia, Microsoft, OpenAI, and many more…
Let’s get into it…
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Three Things You
Should Know…
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- Exclusive—A.I.
enterprise firm raises $80 million: Aily Labs, an enterprise-focused A.I. startup founded in 2020, has completed an $80 million Series B funding round at an undisclosed valuation. The round was led by FPV Ventures, and included participation from J.P. Morgan and Insight Partners, which led the company’s $21 million Series A in 2023.
Aily’s core offering is an app—loaded with specially trained L.L.M.s and machine learning technology—designed to dramatically boost a company’s ability
to make decisions with their data. Bianca Anghelina, the founder and C.E.O. of Aily Labs, described it to me as something like Waze for corporate strategy. In practice, this might look like real-time inventory optimization to get ahead of seasonal trends, or more accurate revenue forecasting.
The company has spent the past several years scaling slowly, working with just a few customers to prove that its product works. The new funding round, Anghelina told me, will fuel
plans for global expansion—and to eventually evolve from strategic recommendations to fully automated decision-making. “The market is demanding it more than ever as C.E.O.s look for P&L impact,” she said, adding that the R.O.I. is apparent “from the moment we integrate the app.” Now, Anghelina has her sights set on Fortune 500 companies.
Pegah Ebrahimi, the co-founder and managing partner of FPV Ventures, told me that Aily’s global expansion opportunities are enormous.
She said that not only is the company’s offering unique, but its primary impact—significant cost savings—is attractive and straightforward. “One of the C.E.O.s I talked to who’s using it was like, I would pay 3x for this product, if not more,” Ebrahimi said. “It’s actually tying all [the data] together constantly, dynamically, which is why it makes such a measurable impact.” - Microsoft & Nvidia’s latest venture bet: Inception Labs, the company
that pioneered diffusion L.L.M.s, announced a $50 million fundraise today. The round was led by Menlo Ventures, with backing from NVentures and M12—the venture arms of Nvidia and Microsoft, respectively. The startup, which came out of stealth mode earlier this year, was founded by a group of professors with years of experience studying A.I. architectures.
Stefano Ermon, the company’s C.E.O., spent more than a decade researching generative A.I. Back in 2019, his team had
the idea to use diffusion models to generate text content—a breakthrough that later formed the core of Inception Labs. While most L.L.M.s are “autoregressive,” meaning they generate words in a sequence, diffusion models work by adding noise to an image and then removing that noise to learn how to generate the image. When applied to text generation, this produces results significantly faster than traditional L.L.M.s., which means greater G.P.U. efficiency and lower latency. (Basically, it’s
cheaper and faster.)
Back in February, Inception launched Mercury, which it described as the world’s first commercially available diffusion L.L.M. “We see a future where all the language models are going to be diffusion-based,” Ermon told me. “I think it’s going to be an inference game, and the speed and cost will matter. So if you match the quality, or perhaps even surpass the quality, that could have a different kind of ceiling in terms of what’s possible.” - AMD’s got an OpenAI problem: As A.I. earnings rolled in this week, investors seemed at least a little rattled about high valuations. Notably, AMD’s stock actually dropped on Wednesday after the company reported that it beat analysts’ expectations for its data center revenue, presumably due to higher cost. The breakneck push
into A.I. comes with other risks, too. While C.E.O. Lisa Su boasted that a new deal with OpenAI would “significantly accelerate our data center A.I. business, with the potential to generate well over $100 billion in revenue over the next few years,” the company’s recent 10-Q S.E.C.
filing tells another story. “We depend on a small number of customers for a substantial portion of our business and we expect that a small number of customers will continue to account for a significant part of our revenue … in the future,” the filing read.
The risk disclosure went on: “If one of our key customers decides to stop
buying our products” or can’t “pay its liabilities, our business would be materially adversely affected.” Boilerplate language, perhaps, but something that investors may need to take seriously as a growing share of tech stocks becomes dependent on OpenAI’s success. The filing also mentioned potential competition from customers who are working to develop their own A.I. chips. OpenAI seems to check a bunch of those risk-factor boxes.
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Deal of the Week:
Backstops or Misspeaks
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At The Wall Street Journal’s Tech Live event on Wednesday, Sarah Friar, OpenAI’s
C.F.O., said that the company was looking to develop an “ecosystem of banks, private equity, maybe even governmental—the ways governments can come to bear. … Meaning, first of all, the backstop, the guarantee that allows the financing to happen. That can really drop the cost of the financing but also increase the amount of debt that you can take.”
Since that comment slipped out, Friar has moved
quickly to walk it back, clarifying on LinkedIn that “OpenAI is not seeking a government backstop for our infrastructure commitments.” Still, the idea—which comes as OpenAI is looking for a ton of debt financing to meet what Sam Altman recently described as $1.4 trillion in spending commitments—was more than a little attention-grabbing. David
Sacks, the White House’s A.I. czar, eventually weighed in, saying that “there will be no federal bailout for A.I. The U.S. has at least 5 major frontier model companies. If one fails, others will take its place.”
In an uncharacteristically long post, Altman
stepped in to clarify that OpenAI is not seeking loan guarantees from the federal government. He noted that the company is approaching an annualized revenue run rate of $20 billion, and indicated that OpenAI might continue to raise more equity or debt in the future.
And now for the main event…
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As the companies at the heart of the A.I. race search for inventive, cost-efficient ways to
satisfy demand, a number of them are beginning to look to outer space as the next frontier for chip and data center development.
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Caught in the throes of a global race without a clear finish line, perhaps it was inevitable that
the A.I. industry would look to outer space as the next frontier for expansion. This extraterrestrial push has coalesced around two somewhat distinct approaches. One involves moving semiconductor fabrication into orbit. The other involves building data centers in space—where, presumably, the issues of electricity consumption, water usage, and carbon emissions won’t be such a problem.
Besxar, which emerged from stealth mode last week, is among a small handful of companies that
believe they can produce semiconductors in space. Founded in 2023 by Ashley Pilipiszyn, a former OpenAI employee, Besxar aims to address a decidedly terrestrial problem: The newest generation of ultrasmall, ultrapowerful A.I. chips are wildly
expensive to manufacture, largely because they’re highly sensitive to even the slightest contamination during the fabrication process. Interestingly, much of the production expense comes from all the air filters, vacuums, and purifiers required. So Besxar is looking to circumvent these costs by moving manufacturing to the vacuum of
space—the ultimate clean room. “We effectively have broken the capacity for Earth to be the ideal manufacturing place,” Pilipiszyn told me.
Besxar is venture-backed, with support from Bee Partners and Union Labs, along with what Pilipiszyn referred to as “strategic angels” from SpaceX, OpenAI, and Anduril. The company also belongs to the Nvidia Inception program. Pilipiszyn didn’t disclose the amount of money Besxar had raised, its valuation, or its runway. But she did note that moving
the semiconductor manufacturing process off-planet might also clear the runway for other, vital advancements in chip technology.
To wit: Silicon, the primary material used in semiconductors, doesn’t have a very high thermal conductivity. Sam Altman has said that OpenAI’s G.P.U.s literally “melt” when experiencing high demand. Right now, there’s plenty of excitement around so-called
compound semiconductors, which combine multiple materials in one chip, but they’re even trickier to fabricate than silicon chips and require an ultrahigh vacuum (U.H.V.) production environment—not unlike what you’d find in low Earth orbit.
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Of course, the trick will be to bring the chips back to Earth in one piece—a task Pilipiszyn refers to as the
“ultimate egg drop challenge.” Besxar plans to use autonomous, reusable manufacturing pods called “fabships” for this delicate task, and last week, the company signed a deal with SpaceX to launch an initial round of 12 missions beginning this year. Once they’ve established that the chips can return intact, the plan is for SpaceX rockets to enter orbit and the fabship to start production; afterward, it’ll splash down with completed semiconductor wafers. Besxar is already working on a
next-generation version of the fabship, optimized for these longer production flights. “For the most part, it really is designed to be set and forget,” Pilipiszyn said. “Humans are in the loop for oversight monitoring if something goes wrong.”
Pilipiszyn told me that Besxar has already secured a contract with the U.S. Navy, and that there’s “been a lot of interest” from the Department of Defense. Everyone, she said, is on the hunt for more and better wafers—and they don’t really care
where from. Meanwhile, as the number of rocket launches continues to increase, largely thanks to SpaceX, the price of sending stuff to space has dropped to $3,500 per kilogram or less. “For what we’re trying to achieve, we’re looking at less than a billion dollars versus tens of billions of dollars that are doubling every four years,” Pilipiszyn said.
Of course, the fabship plan is not a sure bet, especially given the number of upfront, recurring costs and engineering
challenges. Still, Dr. Hugh Barnaby, a professor of electrical engineering at Arizona State University, told me that the idea is not “completely crazy” and could have major benefits, including a smoother chemical process (which is central to microchip production) and the possibility of fabricating compound semiconductors. “Ultimately, you’ve got to bring things up and down, and then you’ve got to fix things,” Barnaby said. “So I think the short answer is that it could work, but
they’re probably many years out from really making this viable for the real production companies. I’d give it a soft maybe.”
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Then there’s Starcloud, another company from the Nvidia Inception program, which
aims to build fully functioning data centers in space. The idea is to leverage the space vacuum, rather than water, as a means of cooling these systems, while using the sun for “nearly infinite” solar power. Soon, the startup will send a G.P.U.-equipped satellite into orbit—the first step toward achieving its goal of orbital data centers.
Philip Johnston, the
company’s co-founder and C.E.O., has said that within a decade, all new data centers will be put in space. (I’ll believe it when I see it.) And yet, Johnston isn’t alone in making this bet: Elon Musk recently indicated that SpaceX could achieve something similar by upgrading its Starlink satellite constellation.
Starcloud isn’t the only business hoping
to take advantage of solar proximity: Google’s Project Suncatcher aims to get a bunch of solar-powered satellites into orbit, laden with A.I. chips, and use the sun’s power to scale compute in space. “I can see the attraction of solar power and probably some advantages for cooling, but the reality of sending the components into space and
maintaining them is truly daunting,” Dr. Nathaniel Cady, a researcher at the University of Albany, told me. Not to mention “the communication bandwidth challenges for beaming data back and forth to Earth,” he added. “Another major challenge would be radiation hardness, or lack thereof, for the electronics themselves. That is already a challenge for long-term space missions.”
Google acknowledged these challenges—thermal management in space, communications from the
satellites to the ground, and general system reliability—in its qualification of this plan as a moon shot. In any case, by early 2027 (assuming the A.I. investment cycle is still booming then), Google plans to launch a couple of prototype satellites to test the theory.
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That’s all for today. I’ll see you next week. Ian
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