cdavid

The common excuse is indeed wrong, as pypy proved. IMO the real issue is the python C API.

The python C API is the "killer app" of python, and what gave its edge against otherwise similar languages (ruby/js). That's makes it unique (the whole scientific stack). But a lot of early choices leaked into this API, and this (+ preference from guido for simple implementation) is at odds with doing JIT: lots of global state (instead of explicitly passing interpreter state), ref counting, no tagged pointers meaning boxing/unboxing everywhere, etc. Some of those are getting gradually fixed, but that's a slog, though maybe AI can accelerate a lot.

I had high hopes for HPy but that unfortunately fizzled out.

This is not done everywhere. I've never hired in the US, but worked for companies in Europe and JP, from <100 people companies to FAANG, and all of them opened dedicated listing for every position we had to fill.

The population rejected more autonomy with a large majority (>70 %) in the last referundum.

For once Cholesky is less general than QR: Cholesky only makes sense for positive matrices, while QR works for any matrix (including non square).

Also QR is a primitive for operations like finding eigenvalues, and I don't think Cholesky can be used there.

The author explicitly mentioned syncing to his parents house. Even the "RAID is not backup" should be more nuanced IMO once you are talking about FS that supports regular snapshots.

It is especially strange not to see it in the list given GiTS is heavily featured (according to the comments, I can't access the page or web archive ATM).

Patlabor movie 2 was directed by the same director as the original 1995 GiTS animation movie. Both patlabor 1 / 2 have similar themes to GiTS, and are heavily cyber punk in themes and esthetics.

The metaphor breaks quickly because as a first approximation the electricity "quality" does not depend on the provider, and will not change overtime. That's not true of LLM output.

For NumPy/Pytorch, the C API is much bigger issue than pickle. I have not looked at the architecture of this, but given it uses its own IR + replaces ref counting w/ a GC, I am assuming it does not have C API compatibility.

The same way cloud is about doing the exact opposite.

Understanding a bit of accounting / corporate finance opened my eyes to many things.

That's debatable. We can't go back in history, but if it were not for ML/data science, I believe python 3 would have killed python. At that time web dev / CLI utilities were major use cases, and that was the time golang became mainstream.

Data science, and then ofc DL being done through python just when python 3 was kinda usable (around 3.3/3.4) was a struck of luck timing-wise.

Also NI, etc. was very linked to the scene from the early days.

Cubase, etc. have no such link that I know how, but there was still the strong hacker culture around atari and to a lesser degree amiga (vs PC), when PC was just not usable for anything low latency in mid 90ies.

I wanted to understand the implementation of some numerical algorithms, and the tech reports were not enough.

I cloned the repo of said library, gave it claude and asked it to write a new technical report in math notation, but with annotation with link to the code so that I can pick up the details. It basically one shotted the full report and that helped me re-implement it in "pure python + numpy", "manually".

no because it does not come from the same budget