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I think a lot of it comes down to game design is hard.

There's a lot of moving parts that go into it, and even experienced teams have difficulty finding the fun. It's extremely common that games that are now popular and beloved weren't very fun until a few months before they released.

Never happen...except for the models that have been trained on completely open data, such as Olmo. They're not frontier class, but they do exist.

There is definitely a kind of monocrop problem in some fields, where it seems like having a very diverse spread of academic investigation is needed to have enough diverse traces through the search space. And globalization has been flattening that.

AI has been turning computer science into biology for the past decade or so. By which I mean that things like neural networks need to be investigated empirically, constructing methodologies and instruments that more closely resemble how fields like biology and medicine have to probe the very complex and messy reality that is beyond our current capacity to fully express in symbolic precision.

Now math gets to deal with that same reckoning. They were already well on their way there with previous Lean proofs, but this has pushed things beyond that horizon and I'm not sure some of the mathematicians are ready for it.

Because Yahoo in particular was very good at destroying goldmines shortly before they became ultra valuable.

There's a number of places that destroyed vast amounts of data in the wind down of ZIRP that probably regret it now.

The early pre-United States had pamphlets and newsletters. Like, a lot of them. It was a big influence on the early post office. You could get rich running a printing press but you did it by printing for the masses.

The yellow journalism era, on the other hand, was a little closer to the rich owning the press.

I wonder if it partially because "write like a human" is kind of a vacuous request. Like, it's the objective everyone including me has been saying that we want, but there's no one way to write like a human and and humans don't even have a good definition past "I know it when I see it."

There's a lot of work in the humanities about different aspects of good writing, but that's not quite the same thing. And anyway they tend to assume a pre-existing level of writing ability. Students are supposed to learn good writing through practice; there are rules and exercises but they're incomplete.

The portable gas turbine is a somewhat separate issue, in that it's highly illegal but if you have more money than god you can just pay off the fines and the judges.

It's relatively easy to avoid being that egregious about it if you're a little bit patient on construction permits and power contracts.

NIMBY opposition to datacenter construction is orthogonal to that, except insofar as in both cases the construction will gravitate toward places that won't or can't object to the construction.

Technically the current best chess engine is a neurosymbolic hybrid.

But I have found that sometimes the best use of an LLM is to write code for symbolic AI.

Yeah, unfortunately "LLMs are bad at counting" seems to apply to counting parentheses.

With modern tool calling I wonder if a better way to go about it is for the LLM to express the program changes as a function or otherwise use an editor that auto-balances parens. There's a lot of relatively simple tooling that makes it easier to write in a Lisp. The languages tend to lend themselves to being straightforward to check like that.

What's special about Lisp's repl is that it's perfectly possible to construct your entire program in the repl, testing each addition live as you write it. (Many Lisp-focused editors assume you'll want to do this, such as Emacs making it easy to run the interpreter on a single function in a file.) That tooling is lost if you just try to one-shot the file, and before 2026 the majority of LLMs originally just tried to one-shot every file.

But, just like a lot of early LLMs had huge problems with whitespace and numbers because the tokenization was taking efficiency shortcuts that made sense for text but absolutely wrecked code syntaxe, I wonder if the current optimizations are badly formatted for Lisp.

At the very least, using a varient like Clojure that also uses [] and {} in addition to () might help.

Except you can express the higher order structure in s-expressions too, and using an AST usually means expressing it as a different syntax than the other parts of your program.

Or maybe I've just been sleeping on the power of Javascript AST.

From the outside Meta's attempts to pivot from open source releases to fast follow closed models fell flat when they tried to prematurely monetize it. They could have owned the open weight model world but tried to pivot to closed weight chatbots before an actually viable revenue model appeared.

I did start a blog in that time period and this is the first time I've ever heard of this. (Admittedly, I wasn't trying to directly make a living off of it.)

If we use the S&P 500 as a proxy for the top 500 companies, I would guess that a lot more than 0% will be gone by the end of 5 years.

It's hard to find non-paywalled sources for business analysis, but from what I can find it'd be about 20%.