nestorD

Some great thoughts, many of which extend beyond mathematics.

One in particular, about sharing secrets, that had not crossed my mind (I have found that virtually no one ticks the "do not train on my data" box...):

> Similarly, it seems that mathematicians already concerned and guarded about what they write in research statements and research proposals. After all, an administrator or a reviewer may upload those documents into an LLM to get help in writing a report, thus potentially compromising the confidentiality of unpublished research.

My thinking is that cloning existing apps is missing the point. It still takes a disproportionate amount of time to get all of the functionalities and quirks of the original right. But, it takes no time to get the handful of things you need working, on your system. That is where I see the most potential: there is little need for massive pieces of software that do everything, I can build the components I need, customized for my use case, and move on.

I started programming at 18 right after highschool (which, I guess, is late by HN standards: a number of my peers had played with Python first and hated Ocaml).

I did so! (quirks of the path I took in the French educational system)

I went through a book similar to the one above, with no internet connection. The first few weeks were rough: I did not quite know what a type was and the compiler error messages were unforgiving and hard to understand without that context. But, once I grokked the core ideas (a proper idea of what could be done with recursion took much longer), things went surprisingly smooth. I definitely credit it with making me a better programmer.

> For example there is less joy to be had in learning a programming language in 2026 than there was in 2016, because there is less utility in it now.

I... disagree. The joy I get from learning a programming language does not come from knowing that it is useful. Rather, it comes from engaging with its abstractions and figuring out the associated mental puzzles.

On a related note, I recently realized that I am barely writing code these days (instead I am reviewing a lot of LLM-written code and nudging it in the right direction) which will make doing the advent of code (which I usually use to play with a language I have never used) without any LLM help even more enjoyable: it will be both the fun of figuring out those puzzles in a new language, and stretching my code-writing muscles.

It's what put MuJoCo on my radar recently! But I was surprised to not see him do any kind of gradient descent to optimize his hyperparameters. MuJoCo has a JAX backend so it should be fairly straightforward.

For people wondering why the Islamic world would have had more texts, many of which are of western (Greek/Latin) origin, than the western world. The problem is that, as the Roman empire collapsed, papyrus supply disappeared in the west (while north Africa still had papyrus, and later early paper) forcing copyist to use-significantly more expensive and lower supply-parchment. As the texts on papyrus started to crumble to dust, monks had to decide which ones to save given the limited writing material available (so they saved a lot of Saint Augustin...).

Her book Steering the Craft, is very much her writing workshop distilled into book form.

In theory, yes! If this metric ever becomes a widely used standard, one would have to start accounting for that...

But, in practice, when asking a model to pick the best answer they see a single question / answers pair and focus on determining what they think is best.

It presumes some models are better than others (and we do find that providing data with a wide mix of model strengths improves convergence) but it does not need to be one model, and it does not even need to be transitive.

I doubt it. The I Ching does not really have bad / low interest hexagrams. Also historians who studied the topic seem pretty sure that the yarrow stalk method is a recent introduction (by I Ching standards, we are talking about a bronze age divination tool...).