So Far, Broadcom Has Been One of the Biggest Winners of the Q4 2024 Earnings Season (AVGO) whose market cap just surpassed $1 trillion last week.
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Broadcom has had an excellent year of steady growth as a leader in semiconductor technology design and manufacturing. With a gain of 118% this year, driven primarily by advances in artificial intelligence (AI) technology, AVGO stock looks poised to end 2024 on an extremely high note.
While Broadcom’s profits this year haven’t been as high as Nvidia’s (NVDA) the AI chip market may be on the verge of a major paradigm shift that could significantly benefit the former. During last week’s Q4 earnings call, Broadcom CEO Hock Tan made a high revenue forecast for the next two years, a forecast that highlights an emerging trend in the AI chip industry.
Over the past two years, industry-wide demand has propelled Nvidia to the top of the booming AI market. Many companies are hyper-focused on building large language models (LLMs), and Nvidia produces the only GPUs (graphics processing units) powerful enough to run many AI systems.
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So far, no company has managed to produce a GPU that can truly rival Nvidia’s in terms of processing power and efficiency. However, during last week’s Q4 earnings call, Tan discussed some elements that indicate the AI chip market may be changing in ways that benefit companies building custom silicon chips, especially eXtreme Processing Units (XPUs), unlike the general-purpose GPUs made by Nvidia.
For context, GPUs are considered very versatile and can typically handle a wide range of computing tasks. Nvidia’s chips are part of a robust software ecosystem, making them easy to use.
XPUs, on the other hand, are highly specialized and often tailored for more specific, intensive computing tasks, typically along the lines of AI and machine learning. They may be more limited in nature, but Broadcom’s fourth-quarter earnings report shows that specialty chips are gaining an edge over more general-purpose chips.
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As noted, Tan sees significant revenue opportunities for Broadcom’s AI and AI Networks. He predicts a range of $60 billion to $90 billion for 2027, a significant increase from last year’s estimate of $15 billion to $20 billion.
The CEO attributed Broadcom’s strong AI growth to its custom XPUs and AI networks, highlighting a specific type of customer that seems to be embracing these chips over traditional GPUs.
“Specific hyperscalers have embarked on their respective journeys to develop their own custom AI accelerators, or XPUs,” he said, referring to cloud computing and data storage companies that conduct hyperscale computing. Broadcom’s hyperscaler partner list includes Amazon (AMZN) Web services, Google (GOOGL) Cloud and Microsoft (MSFT) Azure.
Tan also revealed that Broadcom has been selected to work with two additional hyperscalers and is “in advanced development for their own next-generation AI XPUs.”
Broadcom’s success and growth plans make it clear that the custom silicon chip market is growing. But if so, will companies that produce commodity GPUs, especially Nvidia, be threatened?
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At first glance, it might be easy to assume that the rising popularity of XPUs will threaten Nvidia’s market dominance. A report was published in July 2024 Everything about industries explored this topic and discussed the usefulness of Application Specific Integrated Circuits (ASICs), another custom silicon chip that is similar in functionality to the XPU.
Given the role XPUs have played in Broadcom’s recent earnings results, the issue of custom silicon chips seems even more relevant now. However, one expert believes the market has room for both and that growing demand for both types of AI chips will drive growth for both Broadcom and Nvidia in the coming year.
Ophir Gottlieb is the CEO of Capital Market Laboratories, a sell-side research and financial technology company. He spoke to The Street on Broadcom’s recent earnings call and what it will likely mean for chip makers.
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“I think one type amplifies demand for the other, and it’s kind of a reinforcing cycle,” he says. “Not only is it not a zero-sum game, I think it’s synergistic.”
Gottlieb also undermined the appeal of more specialized chips versus Nvidia’s more general-purpose processors, highlighting that leading tech companies run their AI platforms on their own software layer. In his words:
“If you have a custom software layer, you build the chips specifically to function with that software. And that’s why it’s more effective, more efficient. It won’t be more efficient in an overall sense.”
In a note to investors recently published on Broadcom, Gottlieb states that “While NVIDIA dominates GPUs for AI, Broadcom’s custom silicon tackles hyperscaler-specific workloads with unparalleled efficiency,” reinforcing this bullish thesis about both companies.
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