1. https://ksp-kos.github.io/KOS_DOC/ 2. https://krpc.github.io/krpc/

While the first form seems to work with `pyproject.toml`, it seems like the second form in the global `uv.toml` only accepts actual dates and not relative times. Trying to put a relative time (either in the form "7 days" or "P7D") results in a failed to parse error.

There is some discomfort/soreness for the first few days after switching. My dentist's instructions were to wear each for at least a week and then switch to the next set whenever I wanted after that. Basically at whatever rate I was comfortable/could tolerate. I'm now at set 15 and have switched most of them after a week while a few I delayed a couple of days because I had something happening where I didn't want to worry about any discomfort.

Comments URL: https://news.ycombinator.com/item?id=46387217

Points: 3

# Comments: 2

(With help from Claude completing the list)

https://grok.com/share/c2hhcmQtMw_d7bf061f-2999-46b6-a7fb-58...

Although it does eventually come to the right conclusion... sort of.

The last commit[0] is a fix for date parsing to bring it in line with the GNU semantics, which seems like a pretty good candidate.

Edit: Or not, see evil-olive's comment[1] for a more likely candidate.

0: https://github.com/uutils/coreutils/commit/0047c7e66ffb57971...

1: https://news.ycombinator.com/item?id=45687743

https://en.wikipedia.org/wiki/Project_Sanguine

"Records in the IBM Random Access Memory Unit are stored on the faces of magnetic disks."

"The stored data in the Random Access Memory Unit are read and written by access arms."

"The IBM 355 RAM units provide extemely large storage capacity for data... Up to four RAM units can be attached to the 650 to provide 24,000,000 digits of RAM storage."

The main memory on the other hand: "The 20,000 digits of storage, arranges as 2000 words of memory on the magnetic drum..."

The vulnerability was originally reported to the library maintainers on September 12, 2024, but no fix is available.

The original paper, published in 1987, is "Flocks, herds and schools: A distributed behavioral model"[1]. The implementation was done in Lisp on a Symbolics 3600 Lisp Machine.

Edit: One quite interesting paragraph from the paper regarding performance:

The boid software has not been optimized for speed. But this report would be incomplete without a rough estimate of the actual performance of the system. With a flock of 80 boids, using the naive O(N²) algorithm (and so 6400 individual boid-to-boid comparisons), on a single Lisp Machine without any special hardware accelerators, the simulation ran for about 95 seconds per frame. A ten-second (300 frame) motion test took about eight hours of real time to produce.

Once again, amazing how far hardware has advanced.

1. https://dl.acm.org/doi/10.1145/37402.37406

https://peps.python.org/pep-0617/

Records and specific rules for all categories can be found at https://www.speedrun.com/factorio

The one thing that stood out to me with the original blog post and a quick glance at the code was that it appeared as if the pad was certainly not actually random.

Could anyone that has actually understood it a bit more confirm or reject this?

Edit: It seems that the random generation can be found starting here https://github.com/Vulacode/RANDOM/blob/d6a1a1d694b22e6a115b... With three methods, one (RAND2) seems to use the basic interpreter rng more or less directly and the other two seem to be fairly simple prngs seeded from the basic interpreter's rng.

I don't actually know what the state of basic interpreter rngs was in the early '80s but I would be fairly surprised if they're anything that is secure.

Although it seems there has been no activity since the rename happened almost a year ago?

1. https://www.hyphanet.org/freenet-renamed-to-hyphanet.html