"It's all just a roll of the dice, isn't it Clive?"
"Well, the way you approach it, yes. Yes it is. And again, my name is not Clive."
Micron continues to tell investors that it no longer cyclical in this new, AI-driven market for memory.
In spite of that, Micron's trailing P/E is about two-thirds that of the NASDAQ 100. It's forward P/E is even more dramatically discounted: investors are only paying 20% the forward P/E they are paying on the rest of the NASDAQ.
This with a price of $1,065 after their quarterly earnings announcement in after-hours trading on 30 September 2026.
"Doctors say the explosion of new treatments can also be too much to keep up with: The Food and Drug Administration has approved an average of one new cancer treatment a week for the past five years, an exceptional pace." [from The New York Times reporter Gina Kolata.]
What if Nvidia's Jensen Huang had the same deal as Elon Musk, or if Musk had the same deal as Huang? That is, what if the two men owned the same percentage of the company they founded and those companies had the same P/E ratio? The apples to apples comparison is kind of stunning.
The inputs
Nvidia earned $192.88B on a ~$5.4T market cap, a trailing P/E of about 28. Tesla sits at 345x P/E on roughly $4B of earnings. Musk holds ~20% of Tesla and ~38% of SpaceX, which blends to about 30.6% weighted by value. Huang holds roughly 3.5% of Nvidia.
Extreme A — everyone gets Musk's ratios
Musk is already there, so he's unchanged at about $930 billion. (By Forbes' calculations, Musk has been the world's first trillionaire, a milestone he briefly crossed after SpaceX went public.)
Nvidia at Tesla's 345x: $192.88B × 380.61 = $66 trillion. That single company would exceed the entire US stock market by a comfortable margin and be roughly half of world GDP.
Huang at Musk's 30.6% of that: About $20 trillion. That is, Huang would have a net worth roughly equal to China's GDP, and greater than every country on earth except the US.
Extreme B — everyone gets Huang's ratios
Huang is already there, so he's unchanged at roughly $190 billion.
Tesla at 27.5x P/E: about $110B. SpaceX has no earnings, so using Nvidia's price-to-sales of 17.4x on $23B revenue gives about $400B. Combined, Elon's two companies would be valued at roughly $510B if they were priced relative to sales or earnings at similar level as Nvidia.
Musk at Huang's 3.5%: $18 billion.
| Musk | Huang | |
|---|---|---|
| Musk's rules | $930B | $22.5T |
| Huang's rules | $18B | $190B |
| Actual today | ~$930B | ~$190B |
The punchline
Huang wins both extremes. Under Musk's generous rules he's worth 24 times Musk. Under his own stingy rules he's still worth more than ten times Musk. There is no symmetric treatment — same multiple, same ownership share — under which Musk comes out ahead.
Which means Musk's position as the world's wealthiest person doesn't survive equal treatment in either direction. It exists entirely because the two men are being scored by different rules simultaneously: Musk gets a triple-digit multiple on negligible earnings and a thirty-percent ownership stake, while Huang gets a twenty-seven-times multiple on colossal earnings and a three-percent stake. Take either advantage away and the ranking inverts. Take both and it inverts by an order of magnitude.
I recently heard a couple of guys who short stocks on Steve Eisman's podcast. Eisman asked them about their experience at shorting Tesla, which seemed to them clearly overvalued. The one guy quipped, "We learned that you never short a cult." It is, indeed, a curious set of beliefs that sustain Elon's net worth.
I'm optimistic about how AI might change voting.
Roughly a third of Americans identify as Democrats and a third as Republicans. The remaining third — the independents who decide elections — have the most to gain from AI, because they're the ones party labels serve worst.
Google search let you type "November election" and find websites arguing for or against candidates and propositions. Useful, but it amounted to locating advocacy that already existed, written months earlier for someone other than you. More arranged marriage than courtship.
An AI conversation works differently. You can say: "I think wealthier people should pay more in taxes, but I'm unsure about the mechanism in Proposition 40.[California Proposition 40, One-Time Wealth Tax for State-Funded Healthcare, Education, and Food Assistance Programs Initiative, more popularly known as the billionaire tax.]
"What are the pros and cons?" Or: "Are there studies on how a billionaire tax might affect startup activity in California?" You bring your own bundle of values and half-formed theories about how the economy works, and the answers get built around them rather than around a position someone was already selling.
You might come away more committed to the billionaire tax than any group campaigning for it. You might find it violates something you care about and decide you can't support it. Either way, the conclusion is more likely to be yours. (And yes, one is vulnerable to manipulation from AI. The odds of that are never zero but my own experience of exploring AI's ability to parse arguments suggest they are at least as objective as policy wonks and professors - perhaps more so. And their responses - unlike found content on the internet - is a direct response to your specific inquiry. And one is hardly limited to a single AI for such queries.)
The shift is from finding a prerecorded message to having a conversation — one where you're heard before you listen.
If this works, political advertising should lose some of its grip. A voter who can say "this matters more to me than that" is harder to move with thirty seconds of television, and money in politics buys less.
Here's a way to test it: the share of ballots that include votes on propositions.
Down-ballot measures consistently draw fewer votes than races for president, senator, or governor. Propositions are confusing and time-consuming to understand, and voters who don't know how one aligns with their values often skip it rather than guess.
If people find a process that gives them confidence about an obscure measure, that drop-off should shrink. Rising proposition turnout wouldn't prove AI caused it, but it would be the first visible sign that voters have found a new way to decide what they actually want.