marsten

The economics of that don't work out. Government is a small market and can't drive frontier innovation at the scale it's happening today, let alone in the future.

Look at the defense industry: The Big 5 contractors (Boeing, RTX, General Dynamics, Lockheed Martin, Northrop Grumman) capture most of the discretionary military budget, and the largest of them is in the $300B valuation range (Boeing, which has substantial non-government revenue). Fine businesses but nowhere near Anthropic's valuation.

Bottom line, the government doesn't have deep enough pockets.

In many ways investing in a very late IPO like SpaceX, Anthropic, or OpenAI is the worst of all worlds for the public investor.

On the one hand you'll never see a 100x return – that's been captured by private equity. But there's still a lot of long-term risk because these companies haven't proven they can deliver free cash flow to justify their valuations. Investing in SpaceX or Anthropic at $1T valuation is very different from investing in Apple or Nvidia.

I've been a continuous subscriber since the early 1980s.

The magazine's low point was the infamous op-ed in 2021 about E.O. Wilson a few days after the biologist's death. It was basically a woke hit piece accusing him of scientific racism and white supremacy, with no evidence from his body of writing. It also criticized the genetics community at large for the term "normal distribution", which it took as offensive for implying that anyone outside the peak is "abnormal". (Never mind that "normal" has a technical definition in statistics.)

It's improved a lot over the last few years.

Still, I fear it may soon go the way of BYTE. Not because the need isn't there or because the market is gone, but because people get information in such different ways now.

There's also the way AI itself tends to work: In my experience it very rarely refactors existing code when it's adding something new.

AI tends to layer new code on top and you get a steaming mess very quickly if you aren't careful.

Democracy never handles situations well where one side of an issue is a small highly motivated group, and the other side is a larger group that kinda-cares.

It's the reason we subsidize farmers. It's the reason our tax code remains so complicated. It's also why it's hard to get anything built: Existing owners are highly motivated to block development, and the potential beneficiaries (people who might someday live there, etc.) are too diffuse to mount a defense against them.

Math is likely moving into a big science era, much like experimental particle physics and astronomy did before it.

Once AI mines the easy unsolved problems, it will take large token budgets to make meaningful advances. That will need to be funded and planned at a societal level, like the great facilities of the other big sciences.

Mathematics will become more like an observational science, with some mathematicians specialized in interpreting the results that come out of the big AIs.

> The AI was able to race its car very well, but it took a lot of risks that a human player probably would not.

There is a parallel with autonomous vehicles in real life. On northbound 1 in SF going through GG Park, the left turn lane onto Crossover Drive is always backed up. Waymos often do a very late merge into that turn lane in order to jump the queue and save time. With 360 degree sensing they can do this safely in real time but it feels too risky for most humans to attempt.

This is the direction of experimental particle physics and observational astronomy, where the budgetary scale at which progress occurs means we now fund these efforts at a societal level. These fields have graduated beyond "tabletop science".

For 3000 years mathematics has only been a "tabletop science". Even big programs like the classification of finite simple groups have been comprised of small teams chipping away at different (publishable) parts of an overall program.

This latest Navier-Stokes advance cost something like $22m in tokens, already well beyond what a mathematician's research grant can fund. As the easy open problems get mined, the cost of frontier progress will continue to climb. Some part of mathematics as a field will need to transition from tabletop science to big science: Coordinated top-down programs addressing high-priority objectives.

TBD is what the role of individual mathematicians will look like in a "big science" paradigm, but we could look to experimental high energy physics for ideas. For all practical purposes, AI converts math from a theoretical field into an experimental/observational one.

What is extremely valuable in slime mold organizations is clear direction from above on the relative importance of different objectives.

This doesn't have to be very specific - senior people often aren't in a position to decide on specifics. But even very general feedback can help the rank and file cut through "what should we do?" disagreements. In my experience those disagreements drain productivity faster than anything.

I think most people see AI as an economic inevitability, immune to what any of us thinks. Why spend the time and energy making a reasoned critique if nobody has a real choice in the end? It's like railing against the concept of money or the existence of the mosquito.

Alas I suspect that no combination of business and technical decisions could have allowed Commodore to succeed long term. They never had the scale or product market fit to succeed in the 32 bit era. Apple barely made it.

I too learned C on an Amiga 1000. Somehow I scrounged together $300 to buy the Lattice C compiler and all its manuals – a steep price in 1985-86. Funny to think that much better tools are now free.

A lot of people believe in Musk and will invest in anything he wants to do. Is this rational? It depends on how it plays out.

I think we may be seeing a new type of capitalism that maybe Steve Jobs and Warren Buffet hinted at: A business empire built around the outsized ambitions of a single charismatic individual. The valuations of Tesla and SpaceX only make sense if you attach an enormous premium to Musk the individual.

Second-highest P/E is Tesla, currently at 97.

Apart from Palantir and Tesla, the other big companies are trading at what would historically be considered reasonable P/Es given their growth rates and profitability.

What's really changed in the last 20-30 years is the incredible profit generated by the tech industry, and the defensive moats the biggest companies have built.

Japan is a classic example. You can drop your wallet there and someone will send it to you with all the cash intact. It makes you realize how much overhead it causes when you need to guard against cheaters and thieves.