owulveryck

This is a transcription of the talk: Organization, Collective, Decision by Dave Snowden at USI 2022

Table of Contents

• Hope without optimism
  • About the talk
    • Resources
  • About robustness and resilience
• Sensemaking and the problem of inductive approach to learning

AndrasKovacs

Garbage collection with zero cost at non-GC time

Every once in a while I investigate low-level backend options for PL-s, although so far I haven't actually written any such backend for my projects. Recently I've been looking at precise garbage collection in popular backends, and I've been (like on previous occasions) annoyed by limitations and compromises.

I was compelled to think about a system which accommodates precise relocating GC as much as possible. In one extreme configuration, described in this note, there

rain-1

This worked on 14/May/23. The instructions will probably require updating in the future.

llama is a text prediction model similar to GPT-2, and the version of GPT-3 that has not been fine tuned yet. It is also possible to run fine tuned versions (like alpaca or vicuna with this. I think. Those versions are more focused on answering questions)

Note: I have been told that this does not support multiple GPUs. It can only use a single GPU.

It is possible to run LLama 13B with a 6GB graphics card now! (e.g. a RTX 2060). Thanks to the amazing work involved in llama.cpp. The latest change is CUDA/cuBLAS which allows you pick an arbitrary number of the transformer layers to be run on the GPU. This is perfect for low VRAM.

• Clone llama.cpp from git, I am on commit 08737ef720f0510c7ec2aa84d7f70c691073c35d.

rain-1

Purpose

Bootstrap knowledge of LLMs ASAP. With a bias/focus to GPT.

Avoid being a link dump. Try to provide only valuable well tuned information.

Prelude

Neural network links before starting with transformers.

juliusgeo

20 million digits of pi in under a minute with Julia

I recently discovered a relatively obscure algorithm for calculating the digits of pi: https://en.wikipedia.org/wiki/Gauss–Legendre_algorithm. Well, at least obscure compared to Chudnovsky's. Wikipedia notes that it is "memory-intensive" but is it really? Let's compare to the MPFR pi function:

function gauss_legendre(prec)
    setprecision(BigFloat, prec, base=10)
    GC.enable(false)

Spuffynism

Solving a Dungeons & Dragons riddle using prolog

Bringing back the magic of Christmas using the magic of prolog

As part of a holiday D&D one-shot session where Santa Claus's toy factory had been sabotaged, our dungeon master presented to us, a group of Christmas elves, a riddle to solve.

9 cards, labeled with the names of Santa's reindeer were presented to us. The instructions indicated that we had to find the order reindeer were in, according to this riddle:

Vixen should be behind Rudolph, Prancer and Dasher, whilst Vixen should be in front of Dancer and Comet. Dancer should be behind Donder, Blitzen and Rudolph. Comet should be behind Cupid, Prancer and Rudolph. Donder should be behind Comet, Vixen, Dasher, Prancer and Cupid. Cupid should be in front of Comet, Blitzen, Vixen, Dancer and Rudolph. Prancer should be in front of Blitzen, Donder and Cupid. Blitzen should be behind Cupid but in front of Dancer, Vixen and Donder. Rudolph should be behind Prancer but in front of Dasher, Dancer and Dond

maxgoren

/*
	This started from coding ternary heapsort while on my lunch break.
	It then occured to me that the heapify algorithm could be easily
	extended to any m-ary heap (except of course, a 1-ary heap(list?))
	as shown heapify creates a pentary-heap. changing the #define MARY value
	will set the branching value of the heap.
*/

#include <stdio.h>
#include <stdlib.h>

brendanzab

September 2022:

This has spread to a far wider audience than I had anticipated - probably my fault for using a title that is in hindsight catnip for link aggregators. I wrote this back in 2021 just as a bunch of personal thoughts of my experiences using Rust over the years (not always well thought through), and don't intend on trying to push them further, outside of personal experiments and projects.

Managing a living language is challenging and difficult work, and I am grateful for all the hard work that the Rust community and contributors put in given the difficult constraints they work within. Many of the things I listed below are not new, and there's been plenty of difficult discussions about many of them over the years, and some are being worked on or postponed, or rejected for various good reasons. For more thoughts, please see my comment below.

My personal list of Rust gr

multiversecoder

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multiversecoder

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