AI is creating a new layer in the tech stack 💻. The last platform shift was the cloud, creating 3 hyperscalers that are now at $173B of ARR.
But how will cloud and AI stack interplay? Will they partner, compete, or both?
The shift to cloud gave birth to three major infrastructure players AWS (2006), Azure (2010), and Google Cloud (2013) - see the picture how this played out over time.
🗽 Reflecting on parallels between cloud and AI shifts, A16Z, a leading VC, see co-opetition b/w hyperscalers and AI players to become AI infrastructure.
“The same market forces are already emerging at the model layer, with OpenAI leading the pack in a competitive setup similar to the early years of AWS.
This time around, AWS and the other big cloud players are the incumbents. They see AI as an extension of their legacy cloud compute business.
Given the high compute demands of running AI models, the current chip shortages, and the capabilities these cloud providers have in providing their own chips or building out data center capacity on third-party chips, most have rolled out their own foundation models to compete at both the compute and model layers.”
🤝 Hyperscalers meantime pitch AI as more of a ecosystem partnerships
Consider what Alibaba Cloud's co-founder and CEO Daniel Zhang recently shared:
"Our best monetization model is to have all the AI companies, all the models using Alibaba cloud infra, our high-performance, low-cost computing power to do their AI.
So, I think while we do our foundational model in Ali Cloud and deploy this and deploy on our cloud infra is to not only just run our own model - is to help our cloud industry partners to use this foundational model to do their fine tune, to build their own model in their vertical industries and in their own customized application”.
Zhang and other big cloud vendors try nurturing an ecosystem to bring as many models as possible to developers and industry partners.
Alibaba even took it a step further and has built ModelScope, a leading open-source online community in China for models and related tools and services. Hosting over 1,000 AI models (including Meta's Llama 2 and their own open-source model, the 7 billion parameter), it has accumulated millions of users since April.
🏆 Platform shifts are usually positive-sum games
A16Z reminds us that "As technology advances, the size of the pie grows for both startups and incumbents." In 2003-2023, aggregate revenue across public B2B SaaS increased 5.9x - from $99B to $587B.
"Software incumbents have grown from generating $99B to $323B, maintaining 55% of market share. Or, put another way, incumbents have added revenue, but lost 45% of the market to new entrants."
It's clear that AI will be central to the evolution of cloud computing, as hyperscalers race to be leaders in this new frontier.
So, will AI drive more competition or collaboration in the cloud?
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