In this Q&A, members of Schroders’ public and private equities teams consider which types of tech companies may be best placed to reap the rewards.
What kinds of companies operate in the generative AI segment? Ankur Dubey, Investment Director, Private Equity at Schroders: “We need to understand the ‘technology stack’, i.e. the set of technologies needed to build a generative AI application. There are four layers to the stack:
- The compute layer is the base of the stack. Generative AI systems require large amounts of computing power and storage capacity to train and run the models. Hardware (semiconductor chips) provides the computing power and cloud platforms like Amazon Web Services, Microsoft Azure or Google Cloud Platform provide services like virtual machines and storage.
- Next comes the foundational model layer. Foundation models are systems with broad capabilities that can then be adapted to a range of different, more specific purposes. Arguably this is the most important layer of the generative AI stack. These foundation models are large statistical models built using sophisticated machine learning algorithms that generate human-like responses derived from large volumes of data they're trained upon. Foundation models are split into closed source and open source models. Closed source software is proprietary – only the company that owns it can modify it - whereas open source means the source code is publicly available and programmers can change it.
- Infrastructure layer. These are the tooling/infrastructure companies for apps that don’t use proprietary foundational models. Such apps need the infrastructure companies to help them fully utilise the technology available at the foundational level. Apps with proprietary models (like ChatGPT) don’t need to rely on third parties in the infrastructure or foundational models layers.
- Finally, top of the stack is the application layer, which is the software via which users interact with the underlying AI technology. This can include OpenAI’s ChatGPT product or an internally built solution like Schroders’ in-house AI product, named “Genie”.
What kinds of companies will make the most money from generative AI?
Ankur Dubey: “The jury is still out on which of these layers will accrue the most value. It is still early days for the technology after all. However, we can agree that so far the ‘compute’ layer has emerged as a winner and the example of NVIDIA – with its share price up c.190% year-to-date (FactSet, as at 30 June) - shows the market agrees.
“That said, there is a question over whether the cutting edge technology being designed by NVIDIA today could be commoditised over time.”
Michael White: “For now, the ‘picks and shovels companies’ in the compute layer look like winners thanks to their existing dominant positions. As generative AI use cases grow, the demand for chips will grow too and NVIDIA is an expert with a dominant market share in the GPUs (graphic processing units) that are essential for AI processing.
“On the cloud side, the cloud computing market is an oligopoly. At least for now, the big players like Amazon Web Services, Microsoft Azure and Google Cloud Platform will likely retain their advantage having invested significantly in infrastructure and established customer relationships in recent years.
“But, we must remember that new tech enables new ways of doing things and creating entirely new businesses. For example, Netflix was enabled by the internet and was allowed to flourish because it offered a superior product to traditional pay TV in a way that threatened existing media companies.
“Similarly, Uber is a company whose business model can only exist because of smartphones and the mobile internet. It certainly seems as though this exciting new technology will provide new ways of doing things, but it is perhaps too early for those businesses to have emerged yet – this is what we are looking for”.
Mike McLean, Senior Investment Director, Private Equity: “Looking outside the tech industry itself, one possibility is that companies that are data-rich, for example those that own a large amount of proprietary user-generated content, could become valuable simply because of the value of that data in training AI models.
“From a venture capital side, flows into AI companies have surged in recent years, as the chart below shows. And the flows into AI companies are growing many multiples faster than the venture capital market overall. There was a drop off last year in dollars invested into the AI space, but that reflects a dip in the venture market more generally.
“The key point is that AI is an increasingly important element of the types of companies being created in the market today”.
Further reading : AI revolution: who’s profiting now from generative AI?
