Oct. 28th, 2025

thewayne: (Default)
*SIGH*

I'll let the Slashdot summary do the initial speaking for me:

A global shortage of jet engines is threatening the rapid expansion of AI data centers, as hyperscalers like OpenAI and Amazon scramble to secure aeroderivative turbines to power their energy-hungry AI clusters. With wait times stretching into the 2030s and emissions rising, the AI boom is literally running on jet fuel. Tom's Hardware reports: Interviews and market research indicate that manufacturers are quoting years-long lead times for turbine orders. Many of those placed today are being slotted for 2028-30, and customers are increasingly entering reservation agreements or putting down substantial deposits to hold future manufacturing capacity. "I would expect by the end of the summer, we will be largely sold out through the end of '28 with this equipment," said Scott Strazik, CEO of turbine maker GE Vernova, in an interview with Bloomberg back in March.

General Electric's LM6000 and LM2500 series -- both derived from the CF6 jet engine family -- have quickly become the default choice for AI developers looking to spin up serious power in a hurry. OpenAI's infrastructure partner, Crusoe Energy, recently ordered 29 LM2500XPRESS units to supply roughly one gigawatt of temporary generation for Stargate, effectively creating a mobile jet-fueled grid inside a West Texas field. Meanwhile, ProEnergy, which retrofits used CF6-80C2 engines into trailer-mounted 48-megawatt units, confirmed that it has delivered more than 1 gigawatt of its PE6000 systems to just two data center clients. These engines, which were once strapped to Boeing 767s, now spend their lives keeping inference moving.

Siemens Energy said this year that more than 60% of its US gas turbine orders are now linked to AI data centers. In some states, like Ohio and Georgia, regulators are approving multi-gigawatt gas buildouts tied directly to hyperscale footprints. That includes full pipeline builds and multi-phase interconnects designed around private-generation campuses. But the surge in orders has collided with the cold reality of turbine manufacturing timelines. GE Vernova is currently quoting 2028 or later for new industrial units, while Mitsubishi warns new turbine blocks ordered now may not ship until the 2030s. One developer reportedly paid $25 million just to reserve a future delivery slot.


Now, in some cases the jet engine is in place as a power backup in case main grid power fails. But in many cases, such as Leon Muskbrat's xAI data centers, he's running them full-time while he's waiting for generating stations to be built! And yes, the locals are not happy because he's installing more turbines than he's permitted for. And, of course, the local town councils are doing squat to enforce permits because JOBS!

One interesting Slashdot commenter said "Yes during the dotcom bubble the company my dad worked for made HVAC and UPS equipment for data centers, and they declined the opportunity to build out bigger capacity to meet orders instead of just letting the queue grow longer because their management figured it was a bubble. So, they survived the pop because instead of having unused factories, they just had some cancelled orders. The turbine manufacturers probably feel the same or just don't feel like trying to build factories during a trade war anyhow."

The big question, of course, is how much will this cause problems with the production of jet aircraft? These jet engine generators take engines made for... wait for it... jets. The Boeing 767 is specifically mentioned, that plane is currently in production, and engines are needed for newly-made aircraft and also to service the fleet that is now flying. In the world of 'money talks, BS walks' I suspect that the vulture capitalists backing AI may be able to throw more cash towards data centers, pulling more orders for engines than the airlines can. Could this disrupt global air travel? Will the engine makers, such as GE, be stupid enough to build more capacity and when the AI bubble bursts, be on the hook for billions of dollars that suddenly is no longer needed?

Now, there's one other point that I don't get. There are thousands and thousands of jet engines on the used markets available right now. Okay, maybe they're not quite as powerful as something that's strapped onto a 767. So maybe you need two or three or four to make that much power. But they're available right now. SO WHY AREN'T YOU GOBBLING UP THE USED MARKET?

Article behind a paywall:
https://www.tomshardware.com/tech-industry/turbine-shortage-threatens-ai-datacenters-as-wait-times-stretch-into-2030

https://hardware.slashdot.org/story/25/10/28/0151205/jet-engine-shortages-threaten-ai-data-center-expansion-as-wait-times-stretch-into-2030
thewayne: (Default)
The PSF isn't a huge organization, but they do a lot of work. They have an annual budget of about $5 million and applied, and were close to receiving, a grant for $1.5 mil from the National Science Foundation to “address structural vulnerabilities in Python and PyPI.". PyPI is a library used by TONS of Python projects and has been subject to what's known as supply-chain attacks.

So what's a supply-chain attack? In brief, you take a library that's commonly used. Let's say it let's you send output to a PDF within your Python program, a fairly common task, and something that most programmers don't want to reinvent and won't bother inspecting the library for vulnerabilities. The attack happens when a bad guy changes the code for that PDF library then uploads changes to the master, and now, in addition to generating the PDF, it sniffs around your computer and does... stuff. Infects it with malware, perhaps. Gains admin access and strolls around the network. Looks for crypto wallets and steals them. It can do all sorts of stuff. That, in very simplified form, is a supply-chain attack. And if the program you are writing is released as open source and lots of people download it, THEY all are capable of being subverted!

The PSF was going to use the money to implement some automatic code inspection systems so any changes uploaded into the PyPl library would automatically be inspected, etc., to reduce the threat of supply-chain attacks. Lots of good stuff.

But there was a problem...

The grant application was close to being approved when the board that reviews such applications noticed that the "...foundation’s mission statement includes a goal “to support and facilitate the growth of a diverse and international community of Python programmers,” which conflicted with the grant requirements."

And there was another problem. The grant application, if you agreed to accept it, you also accepted that the NSF could claw-back funds if they wanted to! Basically, you take the $1.5 mil, spend it, and a few years later they decide you're too woke and take it all back, directly out of your bank account. And if your cash flow was a little tight at that time, well, sorry! Your foundation just went negative and is no longer solvent!

The board of the FSF decided to withdraw their grant application with the NSF and pursue other avenues to complete their missions.

https://arstechnica.com/tech-policy/2025/10/python-foundation-rejects-1-5-million-grant-over-trump-admins-anti-dei-rules/

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