Question 1

What is AI infrastructure?

Accepted Answer

AI infrastructure refers to the physical layer of hardware that makes artificial intelligence computationally possible. It includes specialist chips (such as GPUs), high-performance servers, data centres, and networking equipment. Without any one of these components, large-scale AI systems cannot function — making it a distinct and tangible investment category, separate from AI software or applications.

Question 2

What is a GPU and why does it matter for AI?

Accepted Answer

A GPU, or graphics processing unit, is a specialist processor capable of performing vast numbers of calculations simultaneously. Training large AI models demands exactly this kind of parallel processing power, which is why GPUs have become the central hardware component of modern AI infrastructure. NVIDIA is currently the dominant supplier of GPUs used in AI workloads.

Question 3

What does ASML do?

Accepted Answer

ASML is a Dutch company that manufactures extreme ultraviolet (EUV) lithography machines — the equipment used by leading chip foundries to produce cutting-edge processors. Without ASML's machines, the world's most advanced AI chips simply cannot be fabricated. This gives the company a near-monopoly position in a critical stage of the semiconductor supply chain.

Question 4

Why are Big Tech layoffs good for hardware companies?

Accepted Answer

When large technology companies reduce their workforces, they free up significant recurring expenditure. Rather than returning all of that capital to shareholders, many firms have openly stated their intention to redirect it into AI infrastructure — data centres, servers, specialist chips, and networking equipment. This capital reallocation creates durable, measurable demand for hardware suppliers like NVIDIA, Dell Technologies, and ASML.

Question 5

What are the risks of investing in AI infrastructure stocks?

Accepted Answer

Key risks include concentration risk (a large share of the theme's market value is tied to a small number of companies, particularly NVIDIA), demand disappointment (if AI spending grows more slowly than expected), geopolitical risk (especially for ASML, which faces US-China export restrictions), and valuation risk (several stocks trade at elevated multiples). All investments carry risk and you may lose money.

Question 6

Is AI infrastructure a long-term investment or a short-term trade?

Accepted Answer

Based on the article's analysis, this is considered a structural rather than cyclical opportunity. Hardware spending tends to be durable — once a company commits to a particular infrastructure architecture, switching costs are high, creating revenue stickiness for established suppliers. The scale and speed of corporate investment in AI computing capacity suggests the buildout could define the next decade of technology infrastructure.

Question 7

How is AI infrastructure investing different from investing in AI software?

Accepted Answer

AI software investments are often tied to adoption rates, licensing, and user growth — metrics that can be difficult to measure. AI infrastructure represents a more tangible bet: real hardware, purchased by real companies, at growing and measurable scale. Every major technology company building AI capability must buy physical chips, servers, and networking equipment, regardless of which AI software applications ultimately succeed.

Question 8

Top AI infrastructure companies to watch?

Accepted Answer

According to the article's research, three companies are central to the AI infrastructure buildout. NVIDIA designs the GPUs that power AI model training and inference. Dell Technologies assembles enterprise-grade AI server racks and storage systems. ASML manufactures the lithography machines without which advanced AI chips cannot be produced. Each occupies a distinct and critical position in the hardware supply chain.

Question 9

Why is now a good time to look at AI hardware stocks?

Accepted Answer

The AI infrastructure buildout is entering a more intense phase, shifting from software and talent investment towards physical capacity. Data centres are being built at pace, chip orders are stretching supply chains, and networking equipment vendors are reporting strong order books. Corporate balance sheets are being actively restructured around AI, with workforce reductions at major tech firms serving as a financing mechanism for this hardware expansion.

Question 10

Is Meta's restructuring linked to AI spending?

Accepted Answer

Yes. The article highlights Meta as a clear example of capital reallocation in action — workforce reductions are freeing up recurring expenditure that is being redirected, at scale, into AI hardware. This pattern is not unique to Meta; several of the largest technology firms have been explicit about channelling cost savings into AI infrastructure investment rather than returning all savings to shareholders.

Question 11

Can I invest in AI infrastructure stocks with a small amount of money?

Accepted Answer

Yes. One practical barrier to this theme has historically been the high individual share prices of companies like NVIDIA and ASML. Nemo addresses this by offering fractional shares starting from just $1, allowing investors to build exposure to these stocks without needing to purchase a full share. All trades on Nemo are commission-free, making it accessible for investors starting with smaller amounts of capital.

Question 12

Is Nemo a regulated platform for investing in US stocks?

Accepted Answer

Yes. Nemo is regulated by the ADGM FSRA and offers SIPC protection up to $500,000. The platform provides commission-free access to US stocks and ETFs through fractional shares, alongside AI-powered research tools that offer additional context on each holding. It is designed to offer investors in Africa a regulated and straightforward route to building exposure to global investment themes.

When Big Tech Cuts Jobs, the Hardware Bills Keep Rising

When Big Tech Cuts Jobs, the Hardware Bills Keep Rising

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