GTA I and II had really fun car physics. Just driving around and evading police was fun, in a way the later 3d games in the series didn't quite capture for me
It still feels great to play! I love the history too, it's actually a great example of why prototyping "toys" is so important in product development. It allows you to play with isolated concepts without baggage or the expectation to make things production grade. Just getting straight to the point.
I ruined someone's car park learning to do handbrake turns, about 5 years before GTA 1 came out. But (coincidentally) only a few miles from Dundee where GTA was developed! I went to university with some of the people who had done Lemmings levels.
I think the fractal solver is bugged, but maybe I am just using it wrong. It says placing a cone in the red zone will block the vehicle, but either the colors are inverted or the backend is off, because everything is red except a few spots.
Otherwise very fun. I managed to park a truck the solver called impossible :)
Interesting that he namechecks Thrust from 1986, an absolutely amazing game for the BBC Model B, and I guess the first 'physics' game I ever encountered. The 'towing' physics were amazing.
I'm sorry, I really want to like and understand this, but the diagrams are worthless and mostly incomprehensible.
I would've liked to understand more about why it works the way it does, how it achieved the correct feel etc, not just regurgitate whatever the code does.
I would've liked to know more about how the author achieved what they did, not a blog post anyone with an llm could've written.
The diagrams seem to have been written (or generated[1]) while looking at the project source code, and use the sort of bass-ackwards approach to code documentation of giving a “post-hoc summation” that only makes sense when you’ve already read the code, rather than serving as an introduction to the code for someone who hasn’t read it yet.
That being said, AFAICT, the diagrams are also basically irrelevant to the article in its capacity as a high-level overview of the project. You can just ignore them for the purpose of reading the article.
It’s when digging into the project source code that you should look at those diagrams, and then feel frustrated by how much they suck. :)
===
[1] This seems to happen a lot with LLM-generated code docs / diagrams / etc, when the docs are written in the same session as the code itself, but later; the LLM seems to see the docs as “following” the prior work in its linear context, and so mistakenly writes as if the reader of the docs will have also read whatever’s in the context before getting to the docs. That assumption, of an incrementally-growing shared context that can be implicitly made reference to by “later” text to compress that “later” text, makes a lot of sense when generating one long linear stream of prose, or even when generating a series of chain-linked entries (like conversation responses, or chapters of a book); but doesn’t work out when generating a web/graph of separate bits of text. This is kind of a fundamental flaw in producing coding agents as fine-tunes over conversational base models, and it’s one that coding—agent harnesses have yet to really focus on addressing.
If you accelerate the Car, then switch the configuration from Car to Brick, the brick won't slow down.
Not sure whether is it intended but it feels wrong.
I'd say you're fully off the mark here. That page contains serious architectural insight on how to make a "designed" car feeling work within a "physically correct" collision engine. Getting the balance right is super hard and he explains how to do it. I'm confident no AI could do that architecture, so this is most likely hours of hard work with a thin layer of LLM gloss on top.
No, I don't want to see the prompt. Yes it has some llm tics, but it's clear that he went back and forth before arriving at this. Why would I be interested in the transcript?
yes and? someone sharing the details of an extremely popular project is super cool. comments like this will not encourage more people to share more cool things.
I'd be ecstatic if more people used AI to share more cool things they've done. that'd be awesome. more of this blog post please.
But very little of the author shines through here, at least after the intro. I, too, would like to hear more about how someone built stuff, but this is not it.
>One weekend in late August 1996, I wrote a 2D physics simulation which later became the basis of the vehicle system in the eventually popular game "Grand Theft Auto" aka "GTA".
I don't mean to be... judgemental, but if you had the talent to go something like this, why devolve on the remake? One could think that a person with your level of skill would be one of the main vanguard for hand coding. Again, I don't want to be too judgemental, as I am not a great programmer and use assisted tools when planning and designing personal apps, but I am just curious.
Why needlessly do extra work when it's easier than ever before to modernize what is already made? Why would he want to be a vanguard for "hand coding"?
So often it feels like people lose track of the actual conversation happening in the comments in favor of posting a cute quip for points...
This thread originated with one poster expressing disappointment that someone of the author's acumen would choose this path, and another poster asked why the author (or someone of their skills) should have chosen a different path. I weighed in with an answer to that question.
Obviously the author did not see things the way I suggested, or else the conversation would not have happened.
I've been a developer for not nearly as long as the author but long enough that at some point it felt like I was writing the same code and same abstractions over and over again and sometimes a new novel problem would reinvigorate my love of programming but today I'm happy to let an LLM write the tedious code while I give the more fun high level architectural direction and when reviewing the code sometimes I'll give it a nudge in a different direction. I suspect the author has written code like the 2d car physics many times over. Just my 2 cents.
Laughing vampires dance!
Great story, programming and mechanics.
And shortly after I learned how expensive tyres were, I stopped doing handbrake turns.
And shortly afterwards, in addition to all the different physics-in-action experience, I learned about how car insurance excess works.
http://truckslop.joshu.dev/
I think the fractal solver is bugged, but maybe I am just using it wrong. It says placing a cone in the red zone will block the vehicle, but either the colors are inverted or the backend is off, because everything is red except a few spots.
Otherwise very fun. I managed to park a truck the solver called impossible :)
Note: Using safari on an iPad of that matters.
https://youtu.be/Dt44PEIWBRg?is=CbVTRyDfo8Nt56fH
Thrust was by Jeremy C. Smith who went on to work on Exile with Peter Irvin
It'd be amazing to hook is up with the engine sound simulator: https://github.com/ange-yaghi/engine-sim
I would've liked to understand more about why it works the way it does, how it achieved the correct feel etc, not just regurgitate whatever the code does.
I would've liked to know more about how the author achieved what they did, not a blog post anyone with an llm could've written.
That being said, AFAICT, the diagrams are also basically irrelevant to the article in its capacity as a high-level overview of the project. You can just ignore them for the purpose of reading the article.
It’s when digging into the project source code that you should look at those diagrams, and then feel frustrated by how much they suck. :)
===
[1] This seems to happen a lot with LLM-generated code docs / diagrams / etc, when the docs are written in the same session as the code itself, but later; the LLM seems to see the docs as “following” the prior work in its linear context, and so mistakenly writes as if the reader of the docs will have also read whatever’s in the context before getting to the docs. That assumption, of an incrementally-growing shared context that can be implicitly made reference to by “later” text to compress that “later” text, makes a lot of sense when generating one long linear stream of prose, or even when generating a series of chain-linked entries (like conversation responses, or chapters of a book); but doesn’t work out when generating a web/graph of separate bits of text. This is kind of a fundamental flaw in producing coding agents as fine-tunes over conversational base models, and it’s one that coding—agent harnesses have yet to really focus on addressing.
Much of the text is generated as well.
Ran out of steam, I guess...
I'd be ecstatic if more people used AI to share more cool things they've done. that'd be awesome. more of this blog post please.
I don't mean to be... judgemental, but if you had the talent to go something like this, why devolve on the remake? One could think that a person with your level of skill would be one of the main vanguard for hand coding. Again, I don't want to be too judgemental, as I am not a great programmer and use assisted tools when planning and designing personal apps, but I am just curious.
Seems the author chose option 2 and focused on the article instead.
This thread originated with one poster expressing disappointment that someone of the author's acumen would choose this path, and another poster asked why the author (or someone of their skills) should have chosen a different path. I weighed in with an answer to that question.
Obviously the author did not see things the way I suggested, or else the conversation would not have happened.