AI Stack Will be Based on Layers, Just Like All Other App Ecosystems

“Digital infrastructure” tends to refer to physical assets like data centers, fiber optic networks, cell tower networks and cloud computing “as a service” providers, at least as seen by investors in and operators of such assets. 

And even the cloud computing providers (AWS, Zaure, Google Cloud and so forth) most often viewed as the key customers for digital infra providers, rather than core parts of the digital infrastructure business itself. 

However, as AI capabilities become more integral to business operations, there is an argument that digital infrastructure should also encompass AI as a service (AIaaS) capabilities which extend beyond hardware to include software models, language models, and AI platforms. 

Right now that is perhaps not the case, as investors and operators of language models tend to be distinct from traditional “digital infra” providers and investors. 

The “AI ecosystem” is different from the “digital infra” ecosystem, as the former necessarily includes chips, servers, language models, other AI systems and apps. 

As a practical matter, the expanded definition probably will not happen, for several reasons. For starters, financial analysts and operators of “computing” businesses tend to be different from “digital infra” analysts and operators. The former tends to be anchored by “software and hardware” interests, while the latter tends to be dominated by “real estate” interests. 

Foundation models and language models such as  GPT-4, Gemini, and Claude will tend to be the province of “software” industry analysts and practitioners; “hardware” analysts and practitioners such as Nvidia as well as the traditional “computing” ecosystem participants and analysts. 

In other words, the analysts and businesses that are in “middleware” and software stacks and tools, plus applications, are distinct from the analysts and businesses that supply “real estate” functions such as data transmission and data center operations. 

“Cloud computing” might be the function of many data centers, both including AI operators and all other software hosting, but there still are key differences between the businesses of computing and connectivity real estate and the actual software applications that use those real estate assets and platforms. 

So “infrastructure” and “applications” (including language models and AI as a service) will likely continue to remain separate areas of interest.