The chief market strategist at a billion-dollar asset management firm says Wall Street is getting artificial intelligence completely wrong, mistaking a historic infrastructure buildout for a repeat of the 1990s software cycle.
In a new post on X, Wellington-Altus’s top strategist, James Thorne, says investors are misjudging the scale and nature of the AI boom.
Thorne points out that AI is not static technology or compiled code, but an entirely different class of system that requires a different set of resources.
“As Wall St wrongly proclaims, this is just like the 90s.
AI isn’t just another 90s-type software revolution; it is something fundamentally different. Traditional software of the 1990s was pre-compiled: built once, stored, and executed repeatedly with minimal computation. The code ran as a static tool.
AI, on the other hand, generates intelligence in real time. Every output must be computed on demand, reasoning through context to manufacture each token of information. This makes AI an active, power-hungry industrial process, less like software execution, more like a live factory of computation. Each response requires memory, continuous GPU cycles and vast energy input.”
According to Thorne, the constraints shaping AI’s economics now lie in the physical world, not just in software engineering.
“The new bottlenecks aren’t coders, they’re watts, chips, memory and concrete. Data centers, transmission lines, nuclear generation, and natural gas capacity become the physical backbone of intelligence production.”
Thorne says the shift marks the early stage of a once-in-a-generation investment cycle, not a late-cycle push.
“Ignore the noise. This is the opening stage of the largest capital expenditure boom in modern history, validated when even Warren Buffett buys a hyperscaler.”
The latest data from the U.S. Securities and Exchange Commission shows that Warren Buffett’s Berkshire Hathaway freshly opened long positions in Alphabet, buying 17.85 million GOOGL shares valued at $4.33 billion in Q3 of 2025.
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