> If you can come up with a way to do math without reasoning, that would be, in a sense, even more interesting than AI.

Logic is just syntactic manipulation of formulas. By the early 90s logical reasoning was pretty much solved with classical AI (the last building block being constraint logic programming).

So you'll be able to show me the early-90s era program that can solve original IMO-level problems when supplied with the plaintext questions. Right?

if i presented math problems to the best english mathematicians in chinese, does that mean they arent able to reason? the plain text is an arbitrary constraint

The actual question is, if you presented an undergraduate-level calculus problem to a human who is considered intelligent but who was never given an "understanding" of math in school, would the human be able to solve it? Why or why not?

If so, what exactly would you call the process by which the intelligent human solves the math problem that he or she does not initially understand?

Whatever you call that process is what a reasoning model does. You don't have to call it "reasoning," of course... unless you want other people to understand what you're talking about.

Every public toilet eventually becomes and ad-hoc homeless shelter.

Perhaps in urban settings it does. In the suburbs it is not an issue. Also, it is not an issue if someone looks after the toilet every hour, vacating anyone who doesn't belong.

Covid boosted the sale of canned food, but people avoid the sugary syrup of canned fruits in non emergency situations.

Did they? How long have they been around?

Stockpiling uranium ore, or lowly enriched uranium is much simpler than stockpiling natural gas.

OG actionscript was very similar to Javascript. It only started to diverge when type hints were introduced.

AS2 was mostly following the direction of ES4 — so it wouldn’t have diverged if it hadn’t been abandoned.

Sounds like a less efficient version of the mixture of experts approach.

How does mixture of experts architecture work? Are they debating, or merely delegating?

From what I've read, for each token or input patch, the gate computes a set of probabilities (or scores) over the experts, then selects a small subset (often the top‑[k]) and routes that input only to those.

Ie each expert computes its own transformation on the same original input (or a shared intermediate representation), and then their outputs are combined at the next layer via the gate’s weights.

That’s post hoc combination, not B reasoning over A’s reasoning.

A MoE model is one model with expert parts which use less tokens. Which makes it easier for an expert to diverge to a better optimum state. Its easier to only need to know medicin instead of everything and being able to separate everything away from medicin even if certain names, concepts etc. are the same.

AI agents discussing things with each others would be more like one thinking model thinking throught the problem with different personas.

With different underlying models, you can leverage the best model for one persona. Like people said before (6 month ago, no clue if this is still valid) that they prefer GPT for planning and Claude for executing / coding.

Why are you doing meaningless microbenchmarks?

Are you claiming that this does not show the speed difference between socket vs in process communication?

Since OpenJDK was released there isn't much point maintaining GCJ.

American cities lack medium density mixed commercial-residential areas.