A safer way to play the AI boom is to invest in companies selling the underlying compute infrastructure rather than the hyperscalers buying it. This strategy captures the upside of the secular trend while avoiding direct exposure to how the massive capital expenditure is funded, which may involve risky credit.

Instead of betting on specific AI models like ChatGPT, a more robust strategy is to invest in the underlying infrastructure that all AI development requires. This 'onion' approach focuses on second-order essentials like semiconductors and data centers, which are poised to grow regardless of which consumer-facing application wins.

Instead of building AI models, a company can create immense value by being 'AI adjacent'. The strategy is to focus on enabling good AI by solving the foundational 'garbage in, garbage out' problem. Providing high-quality, complete, and well-understood data is a critical and defensible niche in the AI value chain.

The investment mania has moved beyond AI model providers. The new game for savvy investors is identifying and backing the next inevitable supply chain constraint—like memory chips or data center cooling—which will profit regardless of which AI software company ultimately wins.

In the AI gold rush, don't bet on the "miners" like Google and Meta, who are spending billions on a new, high-risk game. Instead, invest in the "pickaxe makers"—the essential toll bridges like TSMC and ASML that every AI company must pass through, ensuring your investment has a higher probability of success.

Instead of betting on which AI models or applications will win, Karmel Capital focuses on the infrastructure layer (neocloud companies). This "pick and shovel" strategy provides exposure to the entire ecosystem's growth with lower valuations and less risk, as infrastructure is essential regardless of who wins at the top layers.

Instead of chasing high-valuation, first-order AI players like GPU makers, THL focuses its investment thesis on second or third-degree beneficiaries. These companies provide critical, capital-light IP or embedded software that endures through tech cycles, offering better long-term value for middle-market investors.

Instead of betting on unknowable AI winners, a better strategy is to find quality companies the market has written off as "losers" due to AI fears. Similar to the unloved "old economy" stocks during the dot-com bubble, these perceived victims could offer significant upside if the disruption threat is overblown.

The AI investment case might be inverted. While tech firms spend trillions on infrastructure with uncertain returns, traditional sector companies (industrials, healthcare) can leverage powerful AI services for a fraction of the cost. They capture a massive 'value gap,' gaining productivity without the huge capital outlay.