veekaybee

Anti-hype LLM reading list

Goals: Add links that are reasonable and good explanations of how stuff works. No hype and no vendor content if possible. Practical first-hand accounts of models in prod eagerly sought.

Foundational Concepts

Pre-Transformer Models

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

manuelbl

ESP32 as Bluetooth Keyboard

With its built-in Bluetooth capabilities, the ESP32 can act as a Bluetooth keyboard. The below code is a minimal example of how to achieve it. It will generate the key strokes for a message whenever a button attached to the ESP32 is pressed.

For the example setup, a momentary button should be connected to pin 2 and to ground. Pin 2 will be configured as an input with pull-up.

In order to receive the message, add the ESP32 as a Bluetooth keyboard of your computer or mobile phone:

1. Go to your computers/phones settings
2. Ensure Bluetooth is turned on

philster

Build TensorFlow 1.3 with SSE4.1/SSE4.2/AVX/AVX2/FMA and NVIDIA CUDA support on macOS Sierra 10.12 (updated October 5, 2017)

These instructions were inspired by Mistobaan's gist, ageitgey's gist, and mattiasarro's tutorial.

Background

I always encountered the following warnings when running my scripts using the precompiled TensorFlow Python package:

W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations.
W tensorflow/core/platform/cpu_feature_guard.cc:45] Th

hofmannsven

Git

Global Settings

• Related Setup: https://gist.github.com/hofmannsven/6814278
• Related Pro Tips: https://ochronus.com/git-tips-from-the-trenches/
• Interactive Beginners Tutorial: http://try.github.io/
• Git Cheatsheet by GitHub: https://services.github.com/on-demand/downloads/github-git-cheat-sheet/

Reminder

Press minus + shift + s and return to chop/fold long lines!

JonnieCache

-/macro fio-dec system, june 1963
 007652	640500		szm=sza sma-szf
 007652	650500		spq=szm i
 007652	761200		clc=cma+cla-opr
-	define senseswitch A
-	repeat 3, A=A+A
-	szs A
-	term
-	define init A,B
-	law B