Chip Happens: But Only Thanks to These Non-US Tech Companies

Before chips are delivered to companies such as NVIDIA, they are manufactured to exacting specifications—and a handful of companies outside the United States are critical to that process. Portfolio Specialist Apurva Schwartz and Portfolio Manager Uday Cheruvu discuss these companies and why their competitive advantage might be even more compelling than the downstream US AI firms.

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The Falling Cost of AI Favors Software Companies

Seven months after Chinese startup DeepSeek rattled markets by introducing a powerful open-weight large language model—freely available for anyone to run or modify, and built for a fraction of the typical cost—OpenAI has followed suit. In an apparent bow to the competitive pressure, the US-based company released two open-weight models on August 5, marking another pivotal moment in the economics of artificial intelligence (AI).

Just a year ago, integrating generative AI into software products was expensive, unreliable, and largely experimental. Today, it’s becoming both practical and profitable. As AI model costs continue to fall, software companies are weaving the technology into more of their products to improve customer productivity and create differentiating features that can command premium prices.

Three forces are driving down AI costs: a venture capital–fueled race for scale, the rise of open-weight models, and rapid advances in the underlying hardware.

Large language models are the brain of AI software products—they interpret language, generate content, and automate reasoning. OpenAI, Anthropic, and xAI, with the aid of massive investment by venture capital firms, are among companies racing to build the most capable and efficient models to attract customers and win market share. Together, the three have raised an unprecedented US$80 billion in only a few years. (For context, a total of US$200 billion was raised across the broader venture capital industry in the US last year.) That capital is being used to invest aggressively in workers—in some cases paying over US$200 million for a single engineer—and in techniques that push their models to be faster, cheaper, and more powerful for users.

From Pipelines to Profits: Distribution Models and Durable Growth in Industrial Gases

In this video, Co-Deputy Director of Research Tim Kubarych and Associate Analyst Safia Williams discuss the resilient economics of industrial gas distribution—from pipeline infrastructure to packaged delivery. They unpack how global players such as Linde and Air Liquide leverage long-term contracts, scale, and innovation to fuel consistent growth across a variety of sectors.

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Chipmaking Is Getting More Complex. Daifuku’s Smart Monorails Keep Fabs Running Smoothly

In semiconductor manufacturing, a single speck of dust poses a threat to production. It’s why cleanrooms, the sterile labs where silicon wafers get etched and cut into pieces, and then packaged as finished chips—with thousands of steps in between—contain few humans. To reduce the risk of contamination and defects, materials are largely transported by automated monorail systems that travel along the ceiling.

Source: Daifuku.
While advances in generative artificial intelligence (AI) have put a spotlight on the companies that design and manufacture chips, as well as their data-center customers, providers of cleanroom technology play an increasingly critical role in a world of high-performance computing. Not only is the industry for cleanroom automation characterized by an attractive competitive structure, but new trends and challenges in chipmaking are also improving the growth outlook for this specialized material-handling technology. One player in particular may stand to benefit, and that is Daifuku.