Subsea Cables & Internet Infrastructure

Google has been the undisputed leader in hyperscaler projects. I believe this reflects its web search and advertising businesses. These involve relatively high traffic flows due to transactions, transfers of personal and web site data, and updating edge servers. Many of the projects listed below are joint projects with network operators and other hyperscalers. Google's solo projects include Dhivaru, Proa, Topaz, SOL, TPU, Boson, Grace Hopper, Junior, Monet, Dunant, Curie, Firmina, Equiano, Nuvem, Umoja, three Indian cables, Bulikula, Tabua, Honomoana, Halailia, Taihai, SOL, TalayLink, Alisios, Canoa, Olaluz, and others.  Facebook's solo projects include Anjana, Waterworth, Petal, Aurora, and Orca. Facebook is more likely to do joint projects rather than take 100% ownership and control. I think this reflects less international traffic because its social media traffic stays within certain regions like North America, Japan, Europe, Africa, etc.

The famous Léon Thévenin cable ship holds the Atlantic record for repairs with 30 over a 29 year period. I believe a repair in this context includes fixing multiple cables during a single outing. The record refers to repairs within the Atlantic Ocean Agreement service area. It is not a cable laying vessel. Léon Charles Thévenin was a French telegraph engineer famous for his Thévenin's theorem, an extension of Ohm's law to complex electrical circuits.

Microsoft has declined to renew a compute agreement with Oracle, partly on the grounds that the Nvidia chips are too old. This supports Michael Burry's contention that GPUs depreciate faster than the five or six years life span that the AI industry uses in accounting treatments. This in turn suggests that AI data center profits are exaggerated. "Microsoft Corp. is winding down an arrangement to rent AI computing from Oracle Corp., part of a larger reassessment of billions of dollars in cloud partnerships. In recent months, Microsoft has been turning off rented computing capacity from Oracle after declining to renew the contract, according to people familiar with the matter. Over time, the computing Microsoft was renting became less useful because it no longer fit the company’s specifications, said the people, who requested anonymity to discuss a private matter. The Oracle hardware used older-generation Nvidia Corp. chips, the people said." Click for more details: https://...

The SLTE footprint has dramatically shrunk over the last quarter century due to Moore's Law and better optics. As the footprint and power requirements fell, the incentive to migrate the SLTEs to carrier neutral data centers increased because colocation costs fell.

 Microsoft has declined to renew a compute agreement with Oracle, partly on the grounds that the Nvidia chips are too old. This supports Michael Burry's contention that GPUs depreciate faster than the five or six years life span that the AI industry uses in accounting treatments. This in turn suggests that AI data center profits are exaggerated. "Microsoft Corp. is winding down an arrangement to rent AI computing from Oracle Corp., part of a larger reassessment of billions of dollars in cloud partnerships. In recent months, Microsoft has been turning off rented computing capacity from Oracle after declining to renew the contract, according to people familiar with the matter. Over time, the computing Microsoft was renting became less useful because it no longer fit the company’s specifications, said the people, who requested anonymity to discuss a private matter. The Oracle hardware used older-generation Nvidia Corp. chips, the people said." Click here for more details: ht...

Recently a client wanted a port and burst Layer 2 service, similar to what Megaport offers in many parts of the world. The customer wanted to pay a fixed port fee and a variable fee for bursting traffic. In the past this setup used Layer 2 Switched Ethernet. The drawback was the cost of Ethernet switching, network management, and the possibility that the provider would severely overbook the service. Making money on such a service is very hard without overbooking. However, most large capacity providers just sell dumb, Layer 1 pipes. So until recently smaller ISPs had few options. Either Megaport or standard chunky Layer 1 waves. The challenge is that many ISPs has peak traffic well below standard 100G wave services, but above 10G. So rightsizing the network is extremely hard. The good news is that the Optical Internetworking Forum developed the FlexE interface standard, which I view as a Layer 1.5 option. It enjoys all the advantages of layer 1 in terms of hard traffic separation, optic...

1. Massive capital expenditures. Much higher capital intensity per rack than a standard data center.  2. Extremely high operating costs due to the power intensity of AI infrastructure. 3. Low customer switching costs shift negotiating power from supplier to customer.  4. Huge gap between capex and revenue flows: 2 to 5 years. 5. Heavy dependence on debt financing and hence vulnerability to rising risk premiums and interest rates. 6. Underlying technology, large language models, is fundamentally flawed according to many computer scientists. This is corroborated by persistent hallucinations and weak problem solving abilities. 7. Large language models show sharply diminishing returns to scale. 8. Luck is required because there are only a few, very large customers for these projects and loss of a single customer can kill a project. Luck is also important because any of these data center projects requires upgrades to the power transmission grid and also generator capacity.