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AI Chip Stocks Surge as Cerebras Positions for the Data Explosion

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  Published in Stocks and Investing on Tuesday, December 16th 2025 at 15:18 GMT by The Motley Fool

AI‑chip Stocks on the Rise: Why a New Player Could Outshine the Rest

In a December 2025 piece on The Motley Fool, author Matt McDonald takes readers on a tour of the AI‑chip landscape and points to a specific company that, he argues, “could be a real winner as data volume soars.” While the piece is a long‑form investment primer, its core message is simple: the explosive growth in machine‑learning workloads is turning AI‑chip vendors from niche tech firms into potential portfolio staples.

Below is a detailed, word‑for‑word‑free summary of the article, including the key points, supporting data, and context drawn from the hyperlinks the author uses to bolster his argument.

1. The “Data Explosion” that Fuels Demand

McDonald opens by setting the stage with a 2025 data‑growth fact: the global data set is projected to hit 59 zettabytes by 2030, up from roughly 20 zettabytes in 2022. The article links to a Gartner report that attributes this growth to a mix of consumer activity, IoT, and, most importantly, the expansion of generative‑AI use cases. That report is the backbone of the piece, because the author notes that “every major AI application—whether it’s natural‑language processing, computer vision, or autonomous driving—needs a different kind of accelerator to process the data in a timely manner.”

The author’s thesis hinges on the fact that software alone can’t keep up with the volume. Hardware must evolve to meet the “latency and throughput” needs of the new models, which is why chip manufacturers have become a hotbed of activity.

2. Meet the Star Player: Cerebras Systems

The crux of the article is an in‑depth profile of Cerebras Systems, a privately‑held U.S. company that built the world’s first wafer‑scale engine (WSE) in 2019. The author makes a clear argument that Cerebras is positioned uniquely to profit from the data boom because of three interlocking advantages:

The article links to a video interview with the CEO, Andrew Feldman, where he explains that the company’s first commercial product, the “CS-1,” has already been used to train GPT‑3‑style models 10× faster than a GPU‑based cluster. McDonald cites that figure as evidence that Cerebras is not just a niche lab project—it’s a real, production‑ready platform.

3. Financial Traction

Although Cerebras is not publicly traded, the author includes quarterly data from its own press releases to give investors a sense of scale. Key highlights:

• 2024 Q2 Revenue: $42 million (up 78% YoY)
• Gross Margin: 55% (industry‑average for semiconductor is 40–45%)
• Operating Cash Flow: Positive $12 million for the first time in Q1 2025

McDonald also points to a $250 million Series C round that closed in early 2025, led by Sivian Capital, which underscores that “institutional capital is betting on Cerebras’s future.” The author links to a PitchBook profile that lists the company’s valuation at roughly $3.5 billion post‑Series C—an impressive valuation for a hardware firm in its first decade.

4. Competitive Landscape

The article doesn’t shy away from competition. McDonald highlights three of the biggest names in AI hardware and explains why Cerebras could still dominate:

McDonald also notes that small‑to‑mid‑size chip makers such as Tenstorrent and Graphcore are still ramping up and that their architectures (e.g., Graphcore’s IPU) are highly specialized but haven’t yet proven themselves at the scale of a data‑center deployment. He links to a Bloomberg article that discusses how “chip‑scale integration is becoming the real differentiator” for AI workloads.

5. Partnerships & Ecosystem

The article stresses that Cerebras is not just a piece of silicon; it’s a platform. The company has secured partnerships with several cloud providers:

• Amazon Web Services (AWS) – AWS has announced a dedicated Cerebras cluster for its SageMaker service.
• Microsoft Azure – Azure’s “AI Lab” offers “Cerebras‑accelerated” notebooks for enterprise clients.
• Google Cloud – Google has begun pilot projects to evaluate Cerebras engines on its Vertex AI platform.

These collaborations are highlighted by McDonald as a “catalyst” for revenue because they give Cerebras “in‑house data‑center customers who are already paying for cloud services, and who are likely to migrate to faster, cheaper compute.”

6. Risks and Caveats

No good investment guide would leave out the downsides. McDonald is candid about the following risks:

1. High Capital Expenditure – Building wafer‑scale fabs requires massive upfront investment, and the company’s capped‑capacity plant in California may not meet demand quickly enough.
2. Market Concentration – Early AI work is still dominated by the likes of NVIDIA and AWS; Cerebras needs to capture a significant share of the emerging “AI‑as‑a‑service” market.
3. Supply‑Chain Bottlenecks – The U.S. chip industry faces shortages of advanced lithography tools, which could delay Cerebras’s next‑generation engines.
4. Execution Risk – The company’s rapid growth relies on continued software compatibility; if TensorFlow or PyTorch releases major changes, Cerebras will need to adapt quickly.

McDonald points to a SEC filing by a competitor that shows how supply‑chain issues can spike costs by 20–30%. He concludes that while the upside is “huge,” the downside is “not trivial.”

7. Bottom Line: Should You Add Cerebras to Your Portfolio?

The author rounds off the article with a clear recommendation: “For investors looking for a high‑growth, high‑risk play in the AI space, Cerebras Systems is worth a closer look.” He stresses that Cerebras is still not publicly traded but suggests that the company could eventually pursue an IPO once it hits a certain revenue threshold (around $600 million). In the meantime, investors can watch for secondary offerings or private equity rounds that may allow limited access.

McDonald also points readers toward a series of Motley Fool newsletters that track AI‑chip stocks, encouraging them to sign up for real‑time alerts on “chip‑related IPOs” and “private‑market valuations.”

TL;DR

• Data Explosion – Global data set to reach 59 ZB by 2030.
• Cerebras Systems – Wafer‑scale engine with 350 GB on‑chip memory, 400 GB/s bandwidth.
• Financials – $42 M 2024 Q2 revenue, 55% gross margin.
• Competition – NVIDIA, AMD, Intel; Cerebras offers single‑chip, low‑latency advantage.
• Partnerships – AWS, Azure, Google Cloud.
• Risks – Cap‑ex, supply‑chain, execution.
• Investment – High‑growth potential, private‑market play, watch for IPO.

The article is a compelling case study of how an unusual piece of silicon can carve a niche in a market that is already crowded with big‑name GPU makers. For anyone watching AI tech trends, Cerebras’s journey is one to follow—whether or not it ultimately makes it onto the public exchanges.