Palantir Technologies (NASDAQ: PLTR) CEO Alex Karp has singled out a select group of four companies he views as the true standouts in the current artificial intelligence infrastructure build-out. The list places Palantir alongside Nvidia (NASDAQ: NVDA), Micron Technology (NASDAQ: MU), and SK Hynix (SKHY), with Karp arguing that only these names carry decisive weight in the new era.
At first glance, the four businesses appear to occupy entirely different lanes. Nvidia supplies the GPUs that train and run AI models. Micron and SK Hynix dominate the memory side of the equation. Palantir sits further downstream, providing the software layer that turns raw data into actionable intelligence. What ties them together, however, is a shared financial metric — the Rule of 40.
The Rule of 40 is a straightforward gauge for assessing whether a high-growth technology company is building a durable business. The calculation simply adds annual revenue growth to operating profit margin. When the sum exceeds 40, it signals that growth and profitability reinforce each other rather than compete, allowing a company to reinvest while still delivering healthy bottom-line results.
Palantir’s Rule of 40 score has climbed exponentially during the AI wave. In the first quarter of 2025, the figure stood at 83%; a year later, it soared to 145%. The leap is driven by two mutually reinforcing trends. Revenue is accelerating as more commercial customers adopt its Artificial Intelligence Platform (AIP), while operating margins simultaneously expand because the company spreads its fixed development and sales costs across a larger, growing revenue base. Incremental customers add revenue with relatively little extra cost, improving profitability in lockstep with sales growth.
Although they operate in different parts of the AI value chain, all four companies share two traits that produce industry-leading Rule of 40 results.
First, surging revenue is directly tethered to insatiable AI demand. Nvidia’s revenue has exploded because its GPUs have become the default engines for AI training and inference in hyperscale data centers. Micron and SK Hynix enjoy parallel tailwinds, as AI workloads require ever-larger amounts of high-bandwidth memory — without sufficient memory, even the most powerful GPU clusters hit latency bottlenecks. Palantir’s growth stems from corporations and government agencies needing software to organize siloed datasets that feed AI systems and to turn model outputs into operational decisions.
Second, operating leverage turns accelerating sales into outsized profits. Each business requires significant upfront capital — for research, chip fabrication, or software development — but once those investments are in place, new revenue flows through with high incremental margins. Nvidia can sell more GPUs without proportionally expanding core design expenses. Memory producers improve factory utilization rates to spread fixed costs across higher volumes. Palantir’s software model benefits from the fact that once AIP is integrated, the marginal cost to acquire a new customer or expand use cases within an existing client is minimal.
The result is consistent across the group: revenue growth and profit margins rise together, making their Rule of 40 scores stand out even in a crowded AI landscape.
Among these four stocks, Nvidia is seen as offering the most compelling risk-reward profile. Its forward price-to-earnings ratio looks reasonable when measured against expected growth, and the company’s reach across the entire AI compute layer — from chips to networking equipment and the surrounding software ecosystem — gives it multiple levers to benefit as AI capital expenditure accelerates.
Palantir, by contrast, trades at a richer valuation that already prices in elevated expectations for continued commercial acceleration. Should growth moderate, the stock leaves relatively limited margin of safety. Micron and SK Hynix remain essential memory suppliers, but their role within the broader AI chip stack is narrower; they do not control the foundational compute architecture the way Nvidia does.
Nonetheless, all four companies are well-positioned for the multiyear AI infrastructure build-out. Their shared ability to generate both accelerating revenue growth and expanding profit margins makes them natural complements rather than competing alternatives. A diversified AI-themed portfolio that includes exposure to compute, memory, and platform leaders stands to capture the full scope of AI infrastructure spending while balancing the unique risks and opportunities each company carries.
