Subsea Cables & Internet Infrastructure

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. 

What a deal!!! Get yourself a promotion, buy now. 🙂 A point: SG1. Z point: Maruyama CLS. Service: Layer 100G Wave. Interface: 100GE. Term: 1 Year. Delivery: Under 4 weeks.

Some claim that Pangram, an AI program, is good at detecting AI written text. So I tested it on Shakespeare. Apparently the Bard was using AI in the 16th century ... Large language models (LLMs) are not logic engines. They are huge nonlinear statistical models with huge number of parameters, in some cases as many as three trillion. LLMs are black boxes. They spit out answers, but it is not clear how they reach those conclusions. Moreover, complicated statistical models are fragile. This means they provide reasonable answers the majority of the time, but will from time to time produce bizarre responses. In contrast, human intelligence is quite robust. Outliers are extremely rare. 

 https://drive.google.com/file/d/1DgndmDXSnGOa5BiWZsVv0pQ_bEx45bhw/view?usp=sharing

Term: three years. NRC: $8,500. Delivery: 4-6 weeks. Remark: Equiano has the lowest latency between Capetown and Lisbon. A point: LS1, Lisbon Equinix. Z point: CT1, Capetown, SA. Customer responsible for cross connects. 

Without an investment grade rating, Anthropic will be unable to tap the funds of most mutual and bond funds despite a trillion dollars in compute commitments over the next three years. This dramatically increases the likelihood of a liquidity crisis and possible bankruptcy. "The FT says the investment giant Blackstone, the anchor investor in a recent $63 billion deal to finance Anthropic’s chips, told investors in the deal that it expects the AI lab to receive a “high” junk rating after its IPO. Previously, the FT notes, Blackstone had said the opposite: that the Claude maker would receive an investment-grade rating (indicating low risk for lenders) before 2027 rolls around." Click here for more details: https://techcrunch.com/2026/10/30/anthropic-expected-to-receive-high-junk-rating-from-credit-agencies-following-ipo-report-says/.