Hellisotherpeople

You probably don't know how to do Prompt Engineering

(This post could also be titled "Features missing from most LLM front-ends that should exist")

Apologies for the snarky title, but there has been a huge amount of discussion around so called "Prompt Engineering" these past few months on all kinds of platforms. Much of it is coming from individuals who are peddling around an awful lot of "Prompting" and very little "Engineering".

Most of these discussions are little more than users finding that writing more creative and complicated prompts can help them solve a task that a more simple prompt was unable to help with. I claim this is not Prompt Engineering. This is not to say that crafting good prompts is not a difficult task, but it does not involve doing any kind of sophisticated modifications to general "template" of a prompt.

Others, who I think do deserve to call themselves "Prompt Engineers" (and an awful lot more than that), have been writing about and utilizing the rich new eco-system

bessarabov

git log --author="Linus Torvalds" --date=iso | perl -nalE 'if (/^Date:\s+[\d-]{10}\s(\d{2})/) { say $1+0 }' | sort | uniq -c|perl -MList::Util=max -nalE '$h{$F[1]} = $F[0]; }{ $m = max values %h; foreach (0..23) { $h{$_} = 0 if not exists $h{$_} } foreach (sort {$a <=> $b } keys %h) { say sprintf "%02d - %4d %s", $_, $h{$_}, "*"x ($h{$_} / $m * 50); }'

virus-warnning

import subprocess

import cairo
import wx
import wx.lib.wxcairo

WIDTH = 400
HEIGHT = 300

surface = cairo.ImageSurface(

tomokishii

#
#  mnist_cnn_bn.py   date. 5/21/2016
#                    date. 6/2/2017 check TF 1.1 compatibility
#

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function

import os

bearfrieze

Comprehensions in Python the Jedi way

by Bjørn Friese

Beautiful is better than ugly. Explicit is better than implicit.

-- The Zen of Python

I frequently deal with collections of things in the programs I write. Collections of droids, jedis, planets, lightsabers, starfighters, etc. When programming in Python, these collections of things are usually represented as lists, sets and dictionaries. Oftentimes, what I want to do with collections is to transform them in various ways. Comprehensions is a powerful syntax for doing just that. I use them extensively, and it's one of the things that keep me coming back to Python. Let me show you a few examples of the incredible usefulness of comprehensions.

rrag

There are many tutorials and articles available online which explain functional programming. Examples show small functions, which are composed into others which again get composed. It is hard to imagine how it would all work, then come the analogies and then the math. While the math is necessary to understand it can be difficult to grasp initially. The analogies on the other hand, (at least for me) are not relatable. Some articles assume the reader knows the different terminologies of FP. Over all I felt it is not inviting to learn.

This introduction is for those who have had a tough time understanding those analogies, taken the plunge to functional programming but still have not been able to swim. This is yet another tutorial on functional programming

Terminology

Functions as first class citizens

Functions are first class means they are just like anyone else, or rather they are not special, they behave the same as say primitives or strings or objects.

myusuf3

To remove a submodule you need to:

• Delete the relevant section from the .gitmodules file.
• Stage the .gitmodules changes git add .gitmodules
• Delete the relevant section from .git/config.
• Run git rm --cached path_to_submodule (no trailing slash).
• Run rm -rf .git/modules/path_to_submodule (no trailing slash).
• Commit git commit -m "Removed submodule "
• Delete the now untracked submodule files rm -rf path_to_submodule

CarloNicolini

"""
 RALIGN - Rigid alignment of two sets of points in k-dimensional
          Euclidean space.  Given two sets of points in
          correspondence, this function computes the scaling,
          rotation, and translation that define the transform TR
          that minimizes the sum of squared errors between TR(X)
          and its corresponding points in Y.  This routine takes
          O(n k^3)-time.

 Inputs:

tmoertel

# Transforming the vanilla recursive fib into the iterative DP version
# through a series of mechanical steps.
#
# For more on converting recursive algorithms into iterative ones, see:
# http://blog.moertel.com/posts/2013-05-11-recursive-to-iterative.html


# original function

def fib(n):

arvearve

Mathematics: What do grad students in math do all day?

by Yasha Berchenko-Kogan

A lot of math grad school is reading books and papers and trying to understand what's going on. The difficulty is that reading math is not like reading a mystery thriller, and it's not even like reading a history book or a New York Times article.

The main issue is that, by the time you get to the frontiers of math, the words to describe the concepts don't really exist yet. Communicating these ideas is a bit like trying to explain a vacuum cleaner to someone who has never seen one, except you're only allowed to use words that are four letters long or shorter.

What can you say?