Cogent Communications Holdings, Inc. Oppenheimer 29th Annual Technology, Internet & Communications Conference

Yeah. Sure, Tim. First, thanks for inviting me to your conference. I'd like to thank investors for their time and Oppenheimer for this venue. Cogent is in the middle of that infrastructure revolution for two distinct reasons. One, we are the largest carrier of internet traffic in the world. AI is possible because of the internet, AI will be distributed over the internet, and it will be integrated into the internet. We have actually seen internet traffic growth begin to accelerate. In the most recent quarter, year-over-year growth accelerated from 12% in the first quarter to 16% in the second quarter. That acceleration in traffic growth follows a pattern of many other applications, whether it be streaming or gaming, where a particular application drives demand. We are now at the very beginning of agentic AI being embedded into everything. That will change the internet two ways.

It will create more traffic, and it will also change the directionality of traffic, as users will have to upload data to then be tokenized and run through LLM for inference. The second part of the AI revolution impacts our wavelength business. That is optical transport. Oftentimes, the development of an LLM is in a different location than where the data is being stored. Because the GPU represents about 60% of the total capital cost in that data center, you want to make sure that those GPUs are being utilized 24 hours a day, seven days a week at peak efficiency. While the internet is cheaper on a per bit-mile basis, it inherently has no defined latency and will require the processor to buffer those bits. The premium that is charged for wavelengths of about two and a half times as much per bit-mile is easily justified.

While there has been a historic demand for private line or wavelength services from international carriers, regional carriers, content distributors, cloud providers, we are now seeing a surge in that demand from AI training, either by hyperscalers or by neoclouds. You are correct, Tim, there has been $1 trillion of capital deployed to date. There is another $6 trillion that has been announced for deployment. Much of this demand is still being developed. There is an acute shortage of power. There is an acute shortage of data center space. There is a shortage of processing. At the end of the day, what you are trying to do is produce the most number of teraflops at the lowest amount of power input and the lowest amount of cost.

We are seeing that proliferate to a lot of new data center construction, which then will have waves to link them back to historical storage sites. I think for all aspects of Cogent's business, these trends are a positive.

I am a firm believer that AI is as transformational to society as the internet has been. I think it will become embedded in everything we do. I think it will make us richer and more productive. I do have some real concerns about the way in which AI is being developed today, the ability to monetize that, and how their investors will get a return on capital. I think there are really four different points that are important. The first one is, today, we are developing AI in a very brute force method using a lot of power. While the power efficiency of next generation GPUs continues to improve, it is clear that for a long time we are going to be power constrained, so we need to be more efficient in our power utilization if we expect to continue to develop new LLMs.

Secondly, there is a bottleneck on the type of processor that allows companies like NVIDIA to have 85% gross margins and 90-plus percent market share. I am a firm believer in capitalism, and I think there will be a number of new entrants coming in to make the cost of that compute come down and be more power efficient. The second question is, the LLMs that are being developed will eventually become fungible with one another. If you look at the original Turing test, it was, can you determine if a computer or a human is answering the question? If you cannot decide, it is probably artificial intelligence if it is a computer. I would actually argue that a correct test would be, if I ask a question of 10 LLMs and get 10 different answers, I have not yet converged on artificial intelligence.

If I ask 10 different models the same question and get the same answer, but did it through different models, I believe we will have true artificial intelligence at that point.

Yeah. Yeah. True cognitive intelligence, when you can ask a question across multiple models and get a consistent answer.

I think we're within a decade of getting that, maybe less. It's highly dependent on, can we train the models more efficiently? If we can, I think we can get there pretty quickly. The third question is, how are companies going to monetize that output to get a return on their investment? There, I don't see a clear answer. I think it's very different than the dot com boom that you and I both lived through, Tim, where private equity and venture put in capital, and it dried up. Here, we've got very well capitalized, somewhat monopolistic companies deploying huge amounts of capital, and taking advantage of bonus depreciation and the tax attributes of being subsidized in that development. So I think we'll continue to see capital pour into this sector, but I believe the ultimate ROICs on that capital will be very low.