It seems a common misconception that images cannot be loaded from outside of the source code directory, but you can. Love’s love.graphics.newImage function doesn’t accept file paths outside of the source directory, but it’s pretty easy to work around.
Assume the following file structure:
working directory/
src/
main.lua
image.png
And here’s the code that will load that image:
-- images must be opened in binary mode
local file = io.open("image.png", "rb")
local data = file:read("*all")
file:close()
local byte_data = love.data.newByteData(data)
local image = love.graphics.newImage(byte_data)
I see people running into this problem all the time and no one seems to dig deeper. While it’s bad practice for many uses to do this, sometimes it’s necessary. For example, I made a little mapping program that can load maps from drag-and-drop – which always means files outside of the source directory.
And so you hopefully don’t waste the same amount of time, here are just the conclusions:
Take breaks every 20 to 70 minutes. Finding the right frequency for you may take trial and error. Multiple sources agree that something near 50 minutes of work with 10 minutes of break works well. The Pomodoro technique combines more frequent shorter breaks with infrequent longer breaks, and is commonly used. The longer you go between breaks, the longer your breaks should be.
A break is only effective when you do something different from what you’re doing now. The primary differences that matter are using different areas of the brain (or not trying to utilize your brain during a break), a difference in eye-focus (stop looking at screens if you were, look far away if you were focused on something right in front of you), and a difference in physical activity (move more if you weren’t moving, or stop for a bit if you were).
(Vacations have beneficial effects, but these seem to be limited in scope and duration. I believe this take is missing important nuance.)
If you wish to read all my notes on this topic, they are publicly available here. (Note: In case that website goes down, I do regularly back up my notes (and blog posts) using the services linked to on Archives & Sources.)
I’m late to the party, but maybe that’s better. I’ve forgotten some of the hype around AI, and the pace of innovation has settled down a little. Think of ChatGPT as a thinking tool with access to an internet-sized – but imprecise – database. That database was last updated in September 2021, and is imprecise because due to how neural networks work. The thinking part of this tool is rudimentary, but powerful. It does many things well with the correct input, but also fails spectacularly with the “wrong” input.
I separate the idea of what ChatGPT is from how it functions and where its knowledge comes from, because it helps me think of uses while remembering its limits. For example, I used it to help me journal more effectively, but when I tried to probe its knowledge of Havana Syndrome – a conspiracy theory commonly presented as fact by USA officials, it expressed useless information, because it has no conception of how it knows anything, or where its knowledge comes from.
Things ChatGPT is Good At
This list is presented in no particular order, but it is important to stress that AI often lie and hallucinate. It is important to always verify information received from AI. This list is based on my experiences over the past month, and will be updated as I use ChatGPT more. It is not comprehensive, but is intended to be what I find most useful.
Socratic method tutoring: The Socratic method is essentially “Asking questions helps you learn.” ChatGPT is very good at explaining topics, just make sure you verify its explanations are factual. (Questions I asked: Why are smooth-bore tanks considered more advanced while rifling in guns was an important innovation? Why do companies decrease the quality of tools over time?)
Writing: ChatGPT tends to be too verbose, but you can make it simplify and rewrite statements, and it can help you find better ways to write. (I asked it to explain the Socratic method a few times, then wrote my own version.)
Scripting: I created a utility script for file statistics in 2-3 hours by refining output from ChatGPT. The end result is more reusable, better written, and more functional than it would’ve been if I had worked on it alone. And that’s ignoring the fact that I got something I liked far faster than I would’ve on my own. (Just.. you need a programmer still. It can do some pretty cool things on its own, but also forgets how to count often.)
Planning: This is a todo item for me. I haven’t successfully used it for planning yet, but I intend to, and have heard of good results from others.
Things ChatGPT is Bad At
Facts & math: AI hallucinate. Check everything they teach you.
Finding sources: ChatGPT’s knowledge is formed by stripping the least useful data out of most of the internet, and who said what is far less important than specific pieces of knowledge – like how do you make a heading in HTML?
An unbiased viewpoint: While ChatGPT is fairly good at avoiding most bias, everything is biased. Removing bias completely is impossible. Discussing anything where there is strong motive to present a specific viewpoint will lead to that viewpoint being presented more often than an unbiased viewpoint.
Violent, illegal, and sexual content: While it is possible to bypass OpenAI’s strict handling of content, it is difficult, inconsistent, and can lead to having access revoked. Sadly, this prevents many ethical use cases due to a heavy-handed approach, and embeds the bias of OpenAI’s team into the model directly. There are ways around this with non-ChatGPT models. (Note: That channel is not the most reliable source..)
What to do in Minecraft: I tried somanyTIMES to get interesting ideas. It just can’t do it.
Things ChatGPT is Okay At
It’s important to know where AI can be a useful tool, but must be used carefully due to mixed results, so I am also including a list of things that work sometimes.
Advice: Similar to the Socratic method, a back and forth conversation can help you with your thoughts. Just be aware that ChatGPT can give some really bad advice too. For example, I wanted to see what it had to say on turning hobbies into jobs, and it covered none of the downsides, only talking about it as a purely positive experience.
Game design: I have spent too much time telling ChatGPT to design games for me. It will generate an infinite rabbit-hole of buzzwords and feature ideas, but cannot understand the concepts of limited time or scope. If you try to follow its designs, you will never complete anything.
Summarizing: If given text as input directly, when it is short enough, a summary can be reliably generated. If asked to summarize something extremely popular before its data cut-off, the summary can be okay. The drop-off on this is insane. Try asking it about Animorphs for example, something talked about occasionally, and certainly known about, but not something it can summarize.
This draft sat around for about 2/3rd of a month nearly complete. I would like it to have even more information, but I would like it more for it to be public. Apologies if it was a little short for you, but hopefully someday I’ll make a better version.
Updates
2024-10-16: Added a note about one of my sources and embedded the video of another. 2025-11-19: Removed an old note that was really out of place for a long time..
Google Chrome on my laptop randomly decided my blog’s domain doesn’t exist. Except, it clearly does. Searching for a solution tells me to do everything from restarting the computer to deleting all browser history – which should be obviously wrong, not to mention annoying. Here’s the laziest quickest way I solved it:
Considering Google decidedto beevil (notice those are 3 separate links) and does the same mass data hervesting and privacy violations as every other big tech company, we shouldn’t be using anything they touch. However, the least we can do and still have a compatible browser is to stop using their “secure” DNS provider anyhow..
This is related to Semi-Empirical Stellar Equations. I have had some questions easily answered, and others which are difficult or impossible to get the kind of accuracy I want.
I’m going to order what I’ve learned by the order I am planning to use these equations, marking equations loosely based on empirical data with an asterisk, and double asterisks for things I’ve completely made up to simplify calculation.
Radius of Surface* (Rsurface): 5500km mean, 1550km standard deviation
Density* [based on common rock types] (Dplanet): 4.7g/cm3 mean, 0.55g/cm3 standard deviation
Vsim exists to support a simulation of an entire planet’s atmospheric contents using my simple fluid simulation mechanic. The magic constant used to calculated Pr is based on Earth’s atmosphere, it can be changed to set an exact “atmospheric height” while maintaining other properties of this simulation.
Atmospheric Pressure at Altitude** (Paltitude): Paltitude [unit: kPa] = Psurface * exp(Pr * maltitude) [Pr may be -Pr, I don’t remember]
This post is obviously incomplete, but it’s been a while since I posted anything here, and I felt like I should go ahead and share what I’ve been up to.
