AI Broke Moore’s Law [Here’s How I Plan To Profit]

The unprecedented demand for AI computing is growing twice as fast as Moore's Law, creating a critical bottleneck in power and infrastructure, which presents a significant investment opportunity beyond just chipmakers.

• AI demand outpaces Moore's Law, shifting focus from chip size to power and infrastructure.

• A half-trillion-dollar annual investment in data centers and energy is needed to meet AI growth.

• Investment opportunities are expanding to data centers, energy, and infrastructure, not just chip manufacturers.

AI computing demand is rapidly outpacing Moore's Law, creating a severe bottleneck in energy, cooling, and infrastructure, not just chip production. This shift marks the post-Moore's Law era, where progress depends on smarter architectures and massive energy networks, requiring hundreds of billions in annual investment through 2030. This scenario is expected to drive a massive economic boom, with significant investment opportunities in data centers, energy, and infrastructure companies.

The Post Moore's Law Era

• 00:00:58 Moore's Law, which predicted computing power would double every two years while costs fell, has been accurate for 50 years, with transistor counts on chips growing from thousands to billions. However, AI, particularly since ChatGPT, has 'ripped up the rulebook' by requiring exponential amounts of data, energy, and minerals, a scale Moore's Law never envisioned. This marks a 'hockey stick moment' where the real bottleneck isn't chip manufacturing but power, cooling, and infrastructure, necessitating massive investments to meet demand.

The Infrastructure Bottleneck

• 00:02:27 Physical limits have been reached on how small chip components can be made, making power, cooling, and infrastructure the primary bottlenecks for AI scaling. Data centers, which are the backbone of AI, require years to plan and build, along with significant energy capacity development from nuclear, natural gas, and renewables. Analysts estimate a staggering $500 billion must be invested in data centers annually until 2030 to keep pace with AI demand, indicating an unprecedented scale of infrastructure development.

Investment Opportunities Beyond Chips

• 00:04:18 While chipmakers like Nvidia have seen massive growth, the future winners of the AI boom are expanding to companies controlling the infrastructure and energy that power the revolution. The smart money is focusing on data centers and AI infrastructure stocks, with major players like Nvidia, Microsoft, Google, Meta, and Blackstone making substantial investments. Surprisingly, some Bitcoin miners are also repurposing their facilities and existing cheap energy infrastructure for AI workloads, becoming hidden beneficiaries of the AI boom.

Key Investment Sectors

• 00:09:02 Three main areas offer significant investment opportunities: GPU and semiconductor leaders like Nvidia, AMD, and TSMC, as every AI model relies on GPUs; energy stocks, including nuclear, natural gas, and renewables, due to AI's enormous electricity demands; and potentially rare earth metals companies, as the increasing demand for GPUs, batteries, and robots will require more of these critical materials. Investing in these foundational elements of the AI revolution is seen as a way to capitalize on its transformative impact on the global economy.