As we wrap up another quarter, AIM reviews how different cloud service providers have performed. In the latest quarter, Amazon Web Services (AWS) earned $27.5 billion in revenue, reporting a 19% increase from the same quarter a year ago. Microsoft’s Intelligent Cloud revenue reached $24.1 billion, a jump of 20%. Meanwhile, Google Cloud’s revenues jumped 35%, reaching $11.4 billion.
AWS continues to lead in market share with 31%, followed by Azure at 20% and Google Cloud at 12%.
At the Core of Generative AI Growth
While holding an earnings call, Microsoft CEO Satya Nadella revealed the company’s AI business is on track to surpass an annual revenue run rate of $10 billion in the next quarter. According to him, Microsoft is the fastest company in history to reach this milestone.
Nadella shared that Microsoft is experiencing an increase in the number of customers utilising Azure AI services to build their own co-pilots and agents. “Azure OpenAI usage more than doubled over the past six months as both digital natives like Grammarly and Harvey, as well as established enterprises like Bajaj Finance, Hitachi, KT, and LG, move their apps from testing to production,” he said.
Citing the example of aerospace company GE Aerospace, Nadella mentioned that the company has used Azure OpenAI to build a new digital assistant for its 52,000 employees. “In just three months, it has been used to conduct over 5,00,000 internal queries and process more than 2,00,000 documents,” said Nadella.
Microsoft was the first hyperscaler to deploy NVIDIA’s Blackwell system with GB200-powered AI servers.
Furthermore, in terms of LLMs, Microsoft has expanded its capabilities by adding support for OpenAI’s latest model family, o1. “We’re also bringing industry-specific models through Azure AI, including a collection of best-in-class multimodal models for medical imaging,” said Nadella.
Having said that, Microsoft is expecting a$1.5 billion loss from its investment in OpenAI.
On the other hand, AWS is confident about its generative AI business. “AWS’s AI business has a multibillion-dollar revenue run rate that continues to grow at a triple-digit year-over-year percentage,” said AWS chief Andy Jassy, adding that it is currently growing more than three times faster than AWS did during its evolution stage.
Jassy disclosed that Amazon will spend about $75 billion in 2024, primarily on infrastructure, data centres, and other resources essential for running AWS. “We’ll spend more than that in 2025, with the majority allocated to AWS,” he said while mentioning that the increases are primarily driven by generative AI.
Similar to how Microsoft is betting on OpenAI, AWS is working closely with Anthropic. The company recently added Claude 3.5 Sonnet to Amazon Bedrock, alongside Meta’s Llama 3.2 models, Mistral’s Large 2 models, and multiple Stability AI models.
Jassy also shared that customers love Amazon Q. “We’re continuing to see strong adoption of Amazon Q, the most capable generative AI-powered assistant for software development and for leveraging your own data. Q has the highest reported code acceptance rates in the industry for multiline code suggestions,” he added.
Notably, Amazon recently added an inline chat feature to Amazon Q, powered by Claude 3.5 Sonnet.
At the same time, Google chief Sundar Pichai revealed that Google Gemini API calls have increased 14x times in the past six months.
Google Cloud offers the Vertex AI platform, which features a comprehensive suite of MLOps tools for using, deploying, and monitoring AI models. This platform also offers the Gemini API.
Lowering Cloud Costs
One common goal among all three cloud service providers is to reduce cloud costs for their customers. Jassy said as customers begin to scale their implementations on the inference side, they quickly realise that it can become costly.
To lower these costs, AWS is developing Trainium and Inferentia, its own custom silicon ships. “The second version of Trainium, Trainium2, will start to ramp up in the next few weeks, and I think it’s going to be very compelling for customers on a price-performance basis,” Jassy further said.
Similarly, Google is currently developing Trillium, its sixth generation of Tensor Processing Unit (TPU). “Using a combination of our TPUs and GPUs, LG AI Research reduced inference processing time for its multimodal model by more than 50% and operating costs by 72%,” said Pichai.
Google CFO Anat Ashkenazi revealed that the company invested $13 billion in capital expenditures (CapEx) during the latest quarter. She disclosed that 60% of that investment in technical infrastructure went towards servers and about 40% towards data centres and networking equipment.
Likewise, Microsoft is building Maia 100, an AI accelerator specifically created for large-scale AI workloads deployed in Azure.
Moreover, Nadella said that Microsoft is not in the business of selling raw GPUs for others to use to train their models. Instead, he highlighted the rapid growth in AI-related revenue driven by inference.
He expressed confidence in the quality of Microsoft’s revenue, as it comes from established enterprise needs rather than model training. Nadella also specified that $10 billion of this revenue is coming from inference.
Additionally, Microsoft CFO Amy Hood said that revenue growth from inference and applications helps fund further training investments. She stressed that training is not a separate phase but part of a continuous cycle of investment, growth, and development in AI for the company.
Microsoft, AWS, and Google’s competition will continue to spiral. The conversation now shifts to agents from LLMs, which will require even more computing.
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