Thanks, Ben, for writing this up! I very much enjoyed reading your intuition.

I was a bit confused in a few places with your reasoning (but to be fair, I didn't read your article super carefully).

1. Nvidia's market price can be used to calculate its expected discounted profits over time, but it can't tell us when those profits will take place. A high market cap can imply rapid short-term growth to US$180 billion of revenues by 2027 or a more prolonged period of slower growth to US$180B by 2030 or 2035. Discount rates are an additional degree of freedom. We can have a lower level of revenues (of not even US$180B) if we assume lower discount rates. CAPM isn't that useful since it's an empirical disaster, and there's the well-known fact that high-growth companies can have lower, not higher, discount rates (i.e. the value/growth factor). 
2. Analysts are forecasting very rapid growth for Nvidia's revenues and profits. You mention Jan-2025 fiscal year-end revenues of $110 billion. The same source has analyst expectations for Jan-2026 year-end revenues of $138 billion. Perhaps you can find analyst expectations that go even further but these are generally rare and unreliable. So you could say that analysts expect Nvidia's revenues of $138 billion in 2025 (ending Jan-26) and continue your analysis from there. However, analyst expectations are known to have an optimistic bias and aren't as predictive as market prices.
3. I was confused about how you used the 3-year expected life of GPUs within your analysis. It's irrelevant when it comes to interpreting Nvidia's market price since Nvidia's future sales pathway can't be inferred by how long its products last. The more appropriate link applies to when Nvidia's customers must have high sales levels given that Nvidia is selling its GPUs, say in 2025. If we add 3 (GPU life) to 2025 (last available year for analyst estimates), we get 2028 (not your 2027), with Nvidia's revenues at $138 billion based on analyst expectations (not your US180 billion based on the market price).
4. I wasn't sure why you needed to estimate 'consumer value' or 'willingness to pay.' This inflated your final numbers by 4x in your title of 'trillions of dollars of value.' And confusingly, it conflates how value is used in other parts of your article. Bringing in 'consumer value' is weird because it's not commonly calculated or compared in economics or finance. Value generally refers to that implied by market transactions, and this applies to well-known concepts like GDP, income, addressable market size, market value, sales, profits, etc (how you use it in most of your article). So we don't have a good intuition for what trillions of consumer surplus means, but, we do for hundreds of billions of sales.
5. So instead of ending with 'trillions of consumer value' for which there are no intuitive comparisons, it's better to end with x billions of sales (profits aren't reliable since high growth companies can go years and years without them, e.g. Amazon). You can then compare this with other historical episodes of industries/companies with high sales growth and see if this growth is likely/unlikely for AI. How fast did Internet companies, or the SaaS industry (software as a service), or Apple get to this level of sales? Is it likely (or not) that AI software companies can do the same within y years?
6. In case you haven't seen these, here are some related resources that might be useful. 1) Damadoran's valuation of Nvidia (from June 2023 so already dated given Nvidia's rapid growth), 2) Sequioa's talks on the large AI software potential (not much in terms of hard numbers but more for useful historic analogs), and 3) ARK's AI note from 2023 (self-promoting and highly optimistic but provides estimates for the AI software market in the many trillions by 2030). 

Thanks, Ben! I enjoyed reading your write-up and appreciate your thought experiment.

You cannot derive revenue, or the shape of revenue growth, from a stock price. I think what you mean is consensus forecasts that support the current share price. The title of the article is provably incorrect.

Stock prices represent risk and information asymmetry, not just the P/E ratio.

The big 5 tech companies (google, amazon, microsoft, facebook, apple) primarily do data analysis and software (with apple as a partial exception). That puts each of the five (except apple to some extent, as their thread to hang on is iphone marketing) at the cutting edge of all the things that high-level data analysis is needed for, which is a very diverse game where each of the diverse elements add in a ton of risk (e.g. major hacks, data poisoning, military/geopolitical applications, lighting-quick historically unprecedented corporate espionage strategies, etc).

The big 5 are more like the wild west, everything that's happening is historically unprecedented and they could easily become the big 4, since a major event e.g. a big data leak could cause a staff exodus or a software exodus that allows the others to subsume most of their market share (imagine how LLMs affected Google's moat for search, except LLMs are just one example of historical unprecedence (that EA happens to focus way closer on, relative to other advancements, than wall street and DC), and most of the big 5 companies are vulnerable in ways as brutal and historically unprecedented as the emergence of LLMs).

Nvidia, on the other hand, is exclusively hardware and has a very strong moat (obviously semiconductor supply chains are a big deal here). This reduces risk premiums substantially, and I think it's reasonable likely that they would even be substantially lower risk per dollar than holding stock diversified between all 5 of the big 5 tech companies combined; I think the big 5 set a precedent that the companies making up the big leagues are each very high risk including in aggregate and Nvidia's unusual degree of stability, while also emerging on the bigleagues stage without diversifying or getting great access to secure data, might potentially shatter the high-risk bigtech company investment paradigm. I think this could cause people's p/e ratio for Nvidia to maybe be twice or even three times higher than it should, if they depend heavily on comparing Nvidia specifically to google, amazon, facebook, microsoft, and apple. This is also a qualitative risk that can also spiral into other effects e.g. a qualitatively different kind of bubble risk than what we've seen from the big 5 over the last ~15 years of the post-2008 paradigm where data analysis is important and respected.

tl;dr Nvidia's stable hardware base might make comparisons to the 5 similarly-sized tech companies unhelpful, as those companies probably have risk premiums that are much higher and more difficult to calculate for investors.