Intro I have recently been toying with some new…toys I got for my workbench. One of them being quadruple 7-segment display. I had mistakenly purchased the version without a “backpack” that contains an LED driver, so I had to figure how how to drive the device manually.
Here is the data-sheet: https://cdn-shop.adafruit.com/datasheets/1001datasheet.pdf
How this device works is rather simple:
All LEDs are tied to the same pins. This means the top LED for each number is the same pin to be powered.
I recently had driven a single-color LED matrix using a Raspberry Pi, which was more difficult than it needed to be because I decided to send the bytes myself. However, I had a bi-color matrix and wanted to get it to work, just with an easier method.
Luckily Adafruit has a library that we can use for this. Now, what to display? It is 8x8, so that sounds perfect for some retro game sprites.
Greetings! We decided that we were going to use our garden guide generator to make a site for the plant hardiness zone that we are located in. You can access it here: https://zone8b.fyi.
The guide currently has around 20 vegetables set up but more will be added.
The code for the site, as well as what is used to generate the site, can be found here: https://github.com/LetsEatLabs/Zone8Site
With the release of the new GPT-4 models that support “function calls” I decided it was time that we actually produce something of use. We were inspired by this post that used the new API features to draft up a recipe application.
We have recently been really focused on our container garden, so doing something related to that seemed like the best idea to start with.
When we started our garden this year we took effort to generate an Excel spreadsheet that laid out all of the plants next to each other and overlaid their sowing and harvest months.
I have started giving GPT some of my own sentences I am unhappy with in prose and asking for it to repeat it in a more “active voice”. I do not paste it into my writing — I read the results and edit my original sentences as I wish, if I wish.
I believe that this process will likely find me reaching out to GPT less and less as I become more familiar with the writing style I am seeking.
The world has been taken by storm with the use of LLMs.1 We see it all over the place currently with some of the most famous examples being OpenAI’s ChatGPT, Bing Chat (also OpenAI powered)2, and Facebook’s LLaMa (which you can run on your own hardware)3.
It would behoove us to learn how to use this new technology, as it really does feel like another Dot-Com moment.
We were inspired by shell_gpt and we wanted to make our own for some different use cases.
Introduction Plastic is everywhere these days — it is an unavoidable fact of life. You put your leftovers in Tupperware, you use a plastic ladle to serve your soup, and you even use plastic cups for your hot coffee. You then clean these out using plastic scrub brushes and other such utensils. We often think about what goes into our food, but how often do we consider what our food goes into?
Originally published December 19, 2020 on Medium.com
Summary This article assumes you have a running Raspberry Pi (Pi 3 or newer) server running either Ubuntu Server or Raspbian. This guide was written using Ubuntu 20.04 - but you can also use Raspbian and its built-in raspi-config if you choose.
What we are going to set up is a Raspberry Pi that is configured to act as a “man in the middle” (MITM) for anything that is connected to its LAN port.