TheChek News Flow

Lapsa said on the podcast that he thought those companies would succeed. But, he added, “I don’t think they’re sufficient for what the commercial space economy needs and the government use case as well,” he said. “Any healthy economy needs multiple players.”

Investors have sunk billions of dollars into space-related startups, despite the setbacks or failures of some. Richard Branson’s Virgin Orbit filed for bankruptcy two years ago after the failure of a rocket launch. Privately held Sierra Space, which raised $1.4 billion from investors such as General Atlantic and Coatue Management in 2021, has faced leadership turnover and delays for its cargo-carrying space plane. And Relativity Space, backed by Fidelity Management and Mark Cuban, faced trouble raising money last year, Bloomberg reported, after its rocket failed to reach orbit after a test launch. Former Google CEO Eric Schmidt then took a controlling stake and became Relativity’s CEO and chair.

Maybe! Maybe not!

Are the big trading firms that now seem to dominate markets (and whose interns earn more than the Fed chair) about to see a shift in fortunes? That’s the controversial suggestion of Alphacution’s Paul Rowady, a longtime industry analyst.

Rowady last week published an interesting report titled “Approaching Peak Proprietary”, which argued that the two primary drivers of the remarkable run enjoyed by the large trading firms will soon fade away.

The first driver has been expansion into more markets and asset classes. The big trading firms are now all active in almost every major asset class and every region, and have managed to push banks out of several of them. Here’s a killer Alphacution chart that shows the trend in US equity options (zoomable version):

For the curious, the top six banks here are (given alphabetically, rather than in order of size) Bank of America, Barclays, Credit Suisse (RIP), Goldman Sachs, JPMorgan and UBS. Alphacution doesn’t say which firms are included in “top market makers” bucket, but we can probably guess most of them.

Here’s a slightly more obtuse chart showing how dominant the big prop trading firms in particular are in cash equity trading, using positions disclosed in 13F filings as a proxy (zoomable version):

Alphacution’s report doesn’t give out the names, only anonymous ranks, but a different report from last month listed the top five as Jane Street, Susquehanna International Group, Citadel Securities, Hudson River Trading and Jump Trading, in that order.

Obviously, 13F filings only capture a moment in time, and will make some firms that typically carry more financial inventory for longer look bigger than the more pure speed merchants. For example, we’re pretty sure CitSec is still a bigger player in US equities than Jane Street, even though Jane’s disclosed holdings are more than twice as big in dollar terms.

But it’s a decent proxy for who matters, and as you can see, if you’re not top five then you’re almost inconsequential.

Things are a little bit more equal when it comes to US equity options — with the same caveat that open interest is also only a rough guide to overall trading volume shares — but not by much (zoomable version):

Rowady argues that there’s a limit to how much more market share the big prop trading firms can now profitably seize. After all, they’re now mostly competing among themselves, rather than against big old lumbering banks.

Another big driver of prop trading firm profits is that the pie itself has become bigger, even as they have increasingly eaten more of it than banks. For example, option trading volumes have exploded ever since 2020-ish, and periodic bouts of volume-boosting turmoil — eg “Liberation Day” — have been a boon to every trading desk.

But Rowady is sceptical that the growth in the velocity of trading we’ve seen lately can be sustained. The level might stay high, but it cannot grow increasingly frenzied forever.

At the same time, he notes that the prop trading industry itself is giving several oblique hints that it is near the peak:

We know that the most dominant players are near — or, at — strategy capacity for many reasons. When prop firms become active in venture capital, it’s a sign of surplus capital relative to core capacity. Another is when the smaller players consistently die off and new players are not replacing them.

The bottom line therefore is:

We don’t know when the top proprietary trading firms will hit their collective peak. They have definitely been making hay in the recent years of sunshine. Certainly, this is tied to the axes of the global listed cash and derivative product universe (or, at least, the electronically traded universe) and transaction volume. Meanwhile, the headwind to this is the concentration in just a few products — where ~40% of the US equity market has become a leveraged bet on no more than 10 stocks.

We’re inclined to agree, but only up to a point. Making markets/providing liquidity/prop trading in US equity and equity-linked markets are probably now close to zero-sum games — especially at the very fastest speeds — but they’re not quite there yet.

Moreover, the magic happens in arbitrages between all the individual stocks, equity indices and the derivatives and ETFs linked to them all. At a time of Bonk Income ETFs, it seems brave to say that equity markets are so efficient that there’s relatively less money to be made for smart traders.

We’re also sceptical about the idea that there are few inroads left to make in new asset classes and regions. Sure, there’s been lots of expansion by the big firms into areas like Asia and credit markets, but we suspect there is still plenty more potential in these areas, not least fixed income.

So, while the kind of trading revenue growth the likes of Citadel Securities, XTX and Jane Street have put up lately might not be repeated, calling the peak seems very premature.

The previously undisclosed Oracle figures aren’t comparable to what other AI cloud server rivals such as publicly traded CoreWeave and privately traded Lambda report to investors. Each company appears to calculate its margins differently.

All cloud firms face the same financial challenge: the high price of Nvidia’s chips. The cost of powering Nvidia server chips far exceeds that of using traditional servers, which were the backbone of the cloud computing industry before the rise of ChatGPT. AI computing also requires other specialized hardware, such as networking equipment to connect the servers.

And to win big deals with AI customers, Oracle and other cloud providers have offered hefty discounts on GPU rental prices, compared to prices they list for regular customers, according to several people with knowledge of these deals. That further diminishes the profitability of those contracts.

Several big cloud providers have said their spending on such chips has hurt their margins in recent quarters.

Building AI-focused data centers has “put pressure on Azure gross margins,” Microsoft Chief Financial Officer Amy Hood said at a Morgan Stanley event in March, in reference to the company’s cloud server rental business. But she said that pressure would lessen as Microsoft made improvements to run the servers more efficiently.

“I feel better about margins [this year] than I felt when we started in June” last year, Hood said.

Pricing ‘Aggressively’

Bigger cloud providers have been able to offset the margin hit from renting out Nvidia GPUs to some extent because most of their businesses don’t rely on that expensive hardware. Amazon Web Services reported a 33% net operating profit margin and Google Cloud reported a 17% net operating margin in the quarter that ended in June, for instance. (Neither company discloses a gross profit margin or breaks out financials for its GPU server rentals.)

Oracle is taking a more direct hit to its margins by renting out GPUs. Oracle reported around $10 billion in sales from renting out cloud servers in the fiscal year that ended in May, with around 20% of that revenue coming from GPU servers, according to the internal documents. In the most recent quarter, the percentage of GPU cloud server sales rose to 27%.

Oracle’s public disclosures imply its GPU cloud business could equal the company’s noncloud revenue as soon as 2028.

Aside from whether Oracle can build enough data centers to generate the revenue it has promised investors, another challenge is how reliant its GPU cloud business could become on a single customer.

“Oracle said, ‘OK, would you rather us not sign these deals and keep the margins higher, or would you rather us sign these deals and [see] the margins go down, but we have incremental profit?’” said Guggenheim Partners’ John DiFucci.

Oracle could still generate healthy free cash flow in the long run, even on the relatively low-margin business of renting out GPUs, if it can sustain rapid revenue growth. One way to do that could be through raising prices, something Luria reckons Oracle may attempt.

“[T]hey are pricing their offering very aggressively” right now, Luria said.

‘Not Our Specialty’

Cloud industry financial analysts largely believe AI computing is the lowest-margin business in the field, given the high cost of Nvidia GPUs. Still, Oracle’s margin on the business in recent quarters is lower than what analysts such as DiFucci and KeyBanc Capital Markets’ Jackson Ader had previously estimated.

Oracle’s margins suffer whenever it installs Nvidia’s latest GPUs in its data centers. In recent months, for instance, the GPU cloud gross margin dipped to the low teens from more than 20% due to the rollout of new Nvidia chips in facilities in Abilene, Texas, that Oracle rents out to OpenAI, the internal documents show.

Oracle could be taking an outsize hit to its margins because it doesn’t own the data centers its customers use, unlike AWS and Google Cloud, which own the majority of theirs. Instead, Oracle primarily leases its data centers from third parties, such as Crusoe.

Owning properties is “not really our specialty,” Oracle Executive Vice Chair Safra Catz said on the company’s earnings conference call last month.

Aside from whether Oracle can build enough data centers to generate the revenue it has promised investors, another challenge is how reliant its GPU cloud business could become on a single customer. Virtually all of the $317 billion worth of cloud deals it signed in the three months that ended in August came from OpenAI.

Blackwell Bleeding

Already, Oracle’s top five AI cloud customers make up roughly 80% of that business: ByteDance, Meta, xAI, OpenAI and Nvidia itself, which uses cloud-based GPUs for its own research and development. Other GPU cloud providers, including CoreWeave, Nebius Group and Lambda, face a similar risk of concentrating most of their cloud revenue in a small number of customers.

One silver lining in Oracle’s GPU business is the amount of revenue it is generating from older generations of Nvidia chips, such as the Ampere chips that came out in 2020. Those chips appear to be helping Oracle’s margins, while newer versions of Nvidia chips strain them.

That dynamic seems to contradict Nvidia CEO Jensen Huang’s recent comment that the release of newer chips essentially wipes out demand for older ones.

Oracle’s margins are also affected by how many of its servers customers are actually using—and paying for. Utilization of Oracle’s GPU cloud servers ranges between 60% and 90%, depending on the type of Nvidia chip that powers them, according to internal documents.

In the three months that ended in August, Oracle lost nearly $100 million from rentals of Nvidia’s Blackwell chips, which arrived this year. That’s partly because there is a period between when Oracle gets its data centers ready for customers and when customers start using and paying for them, the documents show. It’s not clear what causes the gap or how Oracle plans to shorten it.

Cut 2025 Targets

Tesla’s ambitions for Optimus production waned through the year. The company started 2025 with a goal of producing thousands of robots this year, two people with direct knowledge said, up from several dozen in 2024, one of the people said.

In March, Musk said at an all-hands meeting that the company would build at least 5,000 robots in 2025. But Tesla staffers dedicated to Optimus repeatedly told Musk the timelines and goals he set out to scale up production of the robot were overambitious, according to the two people with direct knowledge of the discussions.

Tesla slashed its production goal to 2,000 a few months later, one of the people said. Then, during the summer, staffers told Musk Tesla could meet the 2,000 target, but the robots wouldn’t be very useful due to issues with their hands, the most technically challenging part of their engineering, the person said. As a result, Tesla abandoned plans to produce thousands of bots this year and instead decided to further improve the robot with better hands and other design changes, the person said.

It couldn’t be learned whether Tesla has made meaningful progress since the summer, although Musk acknowledged last month on the “All-In” podcast in September that Tesla was “struggling with the final design of the hardware” and that “the hands inclusive of the forearm are a majority of the engineering difficulty of the entire robot.”

Tesla has not publicly shown the new version of the robot, which Musk has taken to calling V3. “We haven’t shown Optimus V3 yet. It is sublime,” Musk wrote on X in September.

The Optimus delays and redesign coincided with the departure of Milan Kovac, who was head of engineering for the bot until he left the company in June. Now, Konstantinos Laskaris leads Optimus hardware design, Ashok Elluswamy leads software and Lars Moravy leads manufacturing, according to one of the people with direct knowledge. While Laskaris exclusively works on Optimus, Elluswamy and Moravy also work on Tesla vehicles. All three report to Musk.

Musk said on “All-In” that he probably spends “more mental cycles” on Optimus than on any other single project. He has been intensely involved with the program, including meeting with the Optimus group at least once every week or two over the past year in Palo Alto, Calif., where he receives detailed briefings on the design and manufacturing process, two of the people with direct knowledge of the program said.

Some robotics staff at Tesla have questioned whether building a robot in humanoid form makes sense, given the complexity of designing hands—a debate that’s playing out across the industry.

A big reason Tesla is pursuing a humanoid design is that there are billions of videos of humans performing every conceivable task across the internet, which Tesla hopes to eventually use to train Optimus for every task a human can do, a person with direct knowledge said. That plan will only work if Optimus is as close to the size and shape of the average human as possible, so Tesla has designed the bot to be approximately the height of an average person, the person said.

Still, there are huge technical hurdles involved in making random videos of humans useful for training Optimus, and Tesla has so far trained the robots using videos of its own employees doing things like walking around and performing household chores.

Tesla did not respond to a request for comment.

Robot Scientists

In the near term, Tesla’s goal is to deploy as many Optimus robots as possible to perform repetitive industrial tasks inside its own factories. Optimus robots are currently doing basic tasks like sorting batteries in Tesla’s Fremont, Calif., factory, according to videos the company has shared publicly. The bots are also walking around inside the plant on security patrols, according to one of the people with direct knowledge.

Beyond the plan to send Optimus on SpaceX’s first Mars mission—which Musk wants to begin next year, though he has cautioned there may be delays—staff have also discussed other futuristic ways to use the robot through integration with another one of his companies, xAI.

Optimus can already use the Grok chatbot made by Musk’s xAI to speak, a feature Musk has touted on X. Eventually, Tesla envisions using more-advanced versions of Grok and Optimus to replace white-collar workers at the company, including scientists, according to a person with direct knowledge. Tesla staff have discussed having Optimus one day perform hands-on experiments in laboratories using a more advanced and specialized version of Grok as its brain, the person said.

In the meantime, Tesla is facing mounting competition from other companies including Meta Platforms and Amazon, both of which are pushing into humanoid robotics. There are also several other startups, including Figure AI and 1X, that are raising billions of dollars to build humanoids for home and industrial uses.

At The Information’s AI Agenda Live summit in New York last week, 1X CEO Bernt Børnich was asked what advantage his company has over rivals like Tesla and Meta Platforms. “The simple answer is a working product,” he said.

Private equity bets big on utilities

Why private equity is betting big on utilities

As US utilities navigate rising power demand and the need for fresh capital to modernise the grid, private equity firms have taken notice and swooped in to make acquisitions and invest in the sector.

Once considered a sleepy industry, utilities have become popular with Wall Street as investors seek to profit from rising energy demand, especially from technology companies in desperate need of electricity for AI data centres.

Power demand had been flat for nearly two decades but US electricity prices have increased faster than the rate of inflation since 2022, according to the US Energy Information Administration. It expects prices to continue increasing through 2026, with the average US electricity price rising 13 per cent from 2022 to 2025.

“[Utilities are] a growth business these days. Everybody wants power,” said Gregory Brown, a professor specialising in private equity and other alternative assets at the University of North Carolina’s Kenan-Flagler Business School.

Blackstone Infrastructure in May made a deal to acquire local utility TXNM Energy for $11.5bn. Last week, the FT reported that BlackRock-owned Global Infrastructure Partners was nearing a $38bn deal to take over utility group AES, which would be the largest infrastructure takeover of all time. But that is not the first deal GIP has made in the sector. The group last year moved to acquire Allete, the parent of utility Minnesota Power, with Canada Pension Plan Investment Board, for $6.2bn.

Although the deal faced community pushback over concerns about higher electricity prices, the Minnesota Public Utilities Commission approved it unanimously on Friday. As Blackstone awaits approval from regulators in Texas and New Mexico, where TXNM Energy operates, the Allete deal may be a bellwether for further acquisitions in the sector.

Infrastructure has been a target of private equity firms for years and data centre growth has only strengthened demand for energy-related infrastructure. Utilities are also attractive to investors because they are considered a stable investment that tend to operate as regulated monopolies.

“The [utility] business model allows long-term predictable cash flows,” said Gautam Jain, a senior research scholar at the Center on Global Energy Policy at Columbia University. Utilities are allowed to keep a percentage of what they invest in, typically 8 per cent to 10 per cent, as earnings, he added.

AI has driven much of the excitement around utilities with some investors expecting a larger rate of return. Rodney Rebello, portfolio manager and vice-president at Reaves Asset Management, said over the next few years some utilities are well positioned to have growth accelerate to high single digits and in some cases double digits.

“There is this notion that [utilities] could be seen as AI beneficiaries,” he said. “The demand for power is . . . causing a sector that already had a lot of favourable attributes to have growth that is in some cases comparable to the broader market as a whole.”

According to data from PitchBook, private equity exit activity — when a firm realises a return on its investment — in US utilities jumped to $14.6bn this year, up from only $430mn and $3.16bn in 2024 and 2023, respectively.

But not everyone is enthusiastic about private equity’s recent activity.

Households and businesses take on the capital costs that utilities spend on infrastructure upgrades, as well as higher electricity prices. Some worry private equity could further drive up power bills.

“Private equity has developed a reputation of being opportunistic investors,” said Alissa Schafer, climate and energy director at the Private Equity Stakeholder Project, a group that is critical of the buyout industry. “Access to electricity is something that people need every day . . . It is concerning if the primary motivation for the company running it is to get as much money as possible.”

The Allete deal in Minnesota faced opposition from the state attorney-general, environmentalists, consumer advocates and industrial electricity buyers. Opponents of the deal cited the 19 per cent premium BlackRock paid for the Minnesota Power parent and warned Allete could take on extra debt that will cause its cost of capital to rise. This would result in higher rates for households and businesses.

“This approval comes over the clear objections of consumer advocates and utility customers,” said Karlee Weinmann, research and communications manager at Energy and Policy Institute, a watchdog organisation that advocates for clean energy and opposed the Allete deal. 

“Regulators have now made a big bet that BlackRock’s ownership of Allete will yield much different results than private equity typically delivers. Evidence on the record suggests otherwise.”

Regulated utilities need approval to raise prices for its ratepayers, which some analysts and investors expect to act as a mediator between company and consumer interests. Regardless of who owns the utility, rising energy demand will cause US households and businesses to face higher electricity costs in the future.

Jain said: “The prices are going to go up no matter who the investors are.”

Three US-based scientists honoured for showing how strange submicroscopic effects can be harnessed in electronic devices

John Clarke, Michel H Devoret and John M Martinis have won the Nobel Prize in physics for the discovery of quantum mechanical effects that lay the ground for a potential new generation of powerful computers, sensors and encryption technology.

The three researchers will share SKr11mn ($1.17mn) for showing how strange quantum phenomena could be exploited in real-world electronic devices, the Nobel Assembly said on Tuesday as it announced the second of its three annual science awards.

“It is wonderful to be able to celebrate the way that century-old quantum mechanics continually offers new surprises,” said Olle Eriksson, chair of the Nobel committee for physics. “It is also enormously useful, as quantum mechanics is the foundation of all digital technology.”

All three researchers are affiliated with US institutions. Clarke is at University of California, Berkeley, Devoret at Yale University and University of California, Santa Barbara, and Martinis at University of California, Santa Barbara.

“My feelings are that I am completely stunned, of course,” said Clarke, speaking by voice call to the audience at the award announcement at the Royal Swedish Academy of Sciences in Stockholm. “It had never occurred to me in any way that this might be the basis of a Nobel Prize.”

Quantum technologies exploit how the behaviour of matter at the scale of atoms and their constituent particles can differ sharply from that of everyday objects.  

Quantum effects underpin modern electronics, in components such as the transistors in microchips in computers and mobile phones.

The prize-winners showed how the “bizarre properties of the quantum world can be made concrete in a system big enough to be held in the hand”, the awards committee said.

The honour recognises groundbreaking experiments carried out by the three researchers in 1984 and 1985, including an investigation of a quantum mechanical effect called tunnelling.

Tunnelling on the submicroscopic scale of the quantum world allows particles to move through physical barriers. The analogy in human experience would be if a tennis ball thrown against a wall went straight through it.

The scientists showed tunnelling and other quantum effects could take place in a circuit made from superconductors, which can conduct electric current with no electrical resistance.

This provides a basis for efforts to develop new quantum technologies. These include sensors to locate objects underground and computers to perform calculations beyond state-of-the-art existing machines.

“This year’s physics prize is about putting quantum mechanics, which we know from the subatomic world . . . on to an electrical circuit on a chip,” said Göran Johansson, an awards committee member, as he brandished a disc embedded with electronics in illustration. “It’s really a discovery that opened up our understanding for how quantum physics can appear also on this scale.”

The 124-year-old Nobel awards were set up according to the will of Alfred Nobel, a Swedish scientist and businessman who invented dynamite. The physics prize winner is chosen by a special committee at the Royal Swedish Academy of Sciences.

On Monday, Mary E Brunkow, Fred Ramsdell and Shimon Sakaguchi won the Nobel in Physiology or Medicine for discoveries about the regulation of the human immune system. The chemistry award is due to be announced on Wednesday.

Gapping down
In reaction to earnings/guidance:

Other news:

Gapping up
In reaction to earnings/guidance:

Other news: