A couple of weeks ago, we featured a piece on what use cases for Generative AI enterprises are adopting since the emergence of ChatGPT. This piece in the Economist looks at which companies are making money by selling AI related hardware, software or services.
It begins by helping us understand the four layers in the AI stack:
“AI-powered applications sold outside the stack; the AI models themselves, such as GPT-4, the brain behind ChatGPT, and repositories of them (for example, Hugging Face); the cloud-computing platforms which host many of these models and some of the applications (Amazon Web Services, Google Cloud Platform, Microsoft Azure); and the hardware, such as semiconductors (made by firms such as AMD, Intel and Nvidia), servers (Dell) and networking gear (Arista), responsible for the clouds’ computing power”
It reminds us how in each generation of technological change, there have been new winners ending up dominating:
“The PC boom in the 1980s and 1990s propelled Microsoft, which made the Windows operating system, and Intel, which manufactured the chips needed to run it, to the top of the corporate pecking order. By the 2000s “Wintel” was capturing four-fifths of the operating profits from the PC industry, according to Jefferies, an investment bank. The smartphone era did the same to Apple. A few years after it launched the iPhone in 2007, it was raking in more than half of handset-makers’ global operating profits.”
Will AI create its own giants?
“At every layer of the stack, value is becoming more concentrated. In hardware, model-making and applications, the biggest three companies have increased their share of overall value created by a median of 14 percentage points in the past year and a half. In the cloud layer Microsoft, which has a partnership with ChatGPT’s maker, OpenAI, has pulled ahead of Amazon and Alphabet (Google’s parent company). Its market capitalisation now accounts for 46% of the cloud trio’s total, up from 41% before the release of ChatGPT.”
But this is based on market values which are based on the market’s expectations of future profits which may or may not materialise. Of all the layers, the hardware guys led by Nvidia are the ones who are already seeing those profits as users (enterprises) will have to first build the physical infrastructure before the models and the apps on top of those. However, there is competition emerging in each of these layers. Whilst Nvidia’s position seems to be secure for now, its biggest customers – the cloud guys (Google, Amazon and Microsoft) are all working on building their own chips to retain as much value with them. Indeed, the market seems to be suggesting as much.
“The combined market value of Alphabet, Amazon and Microsoft has jumped by $2.5trn during the AI boom. Counted in dollars, that is less than three-quarters of the growth of the hardware layer, and barely a quarter in percentage terms. Yet compared with actual revenues that AI is expected to generate for the big-tech trio in the near term, this value creation far exceeds that in the other layers. It is 120 times the $20bn in revenue that generative AI is forecast to add to the cloud giants’ sales in 2024. The comparable ratio is about 40 for the hardware firms and around 30 for the model-makers.”
What explains the market’s optimism on the cloud providers?
“First, the tech titans possess all the ingredients to develop world-beating AI systems: troves of data, armies of researchers, oodles of computing power and plenty of spare cash. Second, the buyers of AI services, such as big corporations, prefer to do business with established commercial partners than with untested upstarts.
Third, and most important, big tech has the greatest potential to control every layer of the stack, from chips to applications. Besides designing some of their own chips, Amazon, Google and Microsoft are investing in models and apps. Of the 11 model-makers in our sample, nine have the support of at least one of the giants. That includes the Microsoft-backed OpenAI, Anthropic (Google and Amazon) and Mistral (Microsoft again).”
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