Posted by andsoitis 5 hours ago
One distinct memory stands out. I could not wrap my mind around the Object-Oriented extensions on Pascal. I read, re-read, and re-re-read the section of the book describing what polymorhpism is and how it worked, probably at least a dozen times. Somehow it seemed really important and I kept coming back to it. I worked the examples. And then one day the ah-hah moment arrived. I remember it felt like a shock, why it was useful and what I could do with it. I promptly used my knowledge to write a new game using OOP principles to guide the rudimentary "characters" of various geometric shapes at the core of the game.
Fun times, and very formative to me!
And: "A Personal History of Compilation Speed, Part 2" https://prog21.dadgum.com/47.html
This final version for Windows 3.1 might be compatible with 32-bit Windows installations under WoW16, no?
Windows 11 was the first version to ship that was 64-bit only.
He offered three courses. CompSci 1 used Turbo Pascal and Delphi. CompSci 2 used C++ and Java. CompSci 3 used Microsoft Turbo Assembly and a language of the student’s choice.
We had to write our code and save them to floppy discs for submission since the lab systems had DeepFreeze installed on Win95, so any local storage wouldn’t persist.
Didn't realize DeepFreeze is that old. My lab used Angel Custodius[0], which was a hardware-based solution. It used a PCI-slot and the buffer was an IC on the PCI board.
It worked the same, rebooting the computer would restore the frozen state, because changes were never committed to disk.
It also was OS-agnostic, because it ran before booting anything. If you had a Linux server and got hacked, you just restarted it, though it remained vulnerable until you disabled the protection and actually patched it.
If you wanted to introduce changes you had to press a combination of keys to bypass it, by introducing the password. Mainly to apply pending Windows Updates.
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[0]: https://web.archive.org/web/20040210055959/http://www.custod...
You could have different templates that all built off of the same base which made switching between different specialized classes in the lab super easy.
We had two courses at my school in early post-Wende East Germany ('91 onwards, on Amstrad PC2386 386/20 MHz machines): a beginner's computer course with OS intro (MS-DOS 4.01 and Windows 3.0), office applications, and typing... and a programming course via the GW-BASIC (later QBasic) to Turbo Pascal (much later Delphi) pipeline.
A cool thing about TP was that it had simple and convenient support for inline assembly, which was the gateway drug for me learning more low level programming.
It’s really sad that Delphi didn’t take off like VB. It was a superior environment in every way. Faster programs, better UI, much better language, and I would argue easier to use (in VB you spent a lot of time working around the limitations of BASIC in my experience). Hard to compete with Microsoft though.
I didn’t realise at the time that, with the advent of web apps (and my interest in them), that chapter of my life would be the last time I would work with such a clean, integrated dev environment.
I agree, but AI also there is hope!
For many years I've worried about the ever-growing depth of abstraction in computing. There are few alive now who actually understand all of the layers on abstraction involved in modern computing, and who can debug the truly strange edge case bugs and vulnerabilities introduced by the interoperation of these many complex layers.
For a time I imagined it to be an unsolvable problem, and that there would always be only a special class of neurodivergent hyper-specialists who still mostly had to work in large teams to even come close to understanding a stack in full. We're reaching the point where a single human lifespan just isn't enough to learn it all, even for those of us with what Dilbert called "The Knack". By the time you're proficient in all of it - you're dead.
Now there is a new kind of intelligence. One that CAN fit it all in a single mind, and one that will outlive us all and continue to learn long after our meat has gone bad.
As long as the AI's stay aligned, and we find ways to build them more efficiently there's a non-zero chance that they actually make it all better instead of worse. Genuinely long-term planning and the ability to TRULY grasp the full stack COULD actually happen. At least if we use these new systems in service of the greater good, and not just to play silly games on the stock market.
Besides, it's an exaggeration. I've been programming for 35 years, and Turbo Pascal was one of my first languages. I wrote OWL code! Seeing that splash screen brought back memories. But I can understand and debug problems that cross almost any layer of the software stack. Anything from some ReactJS library to kernel code to UEFI. I'm now 42 so the idea nobody can understand or debug interactions across layers before they die is for the birds. The stack isn't that deep.
[1]https://tech-insider.org/discord-electron-rust-gpui-rebuild-...
The fact that we are celebrating that a chat app only uses 300MB ram at launch instead of 1GB seems absolutely ludicrous to me
The early versions of Skype used about 30MB RAM while in a video call and by the early 2000s standards it was bloatware. Before that we used WebEx in the 90s which was a browser ActiveX or Java applet and RAM use was about 6MB in a video call. In the early / mid 90s I used CU-SeeMe for video calls and its RAM footprint was just over 2MB on Mac System 7
Something has clearly gone very wrong in the software development process in the last 2-3 decades and while Im encouraged to see that some people are interested in reversing that trend I still find the resource wastage has me shaking my head sometimes
Sometime in the late 90s there started a fundamental change in the software development process. We changed from optimising software for the end user (development is difficult) to optimising the software development process for the developer at the expense of user resources
One of the main selling points of Turbo Pascal was OWL: the Object Windows Library, which was just a big OOP abstraction over Win16. Here's some sample code:
https://github.com/TeamVault/pascal-programs/blob/master/Pas...
Doesn't look radically different to how a GUI app that targets a native framework would look today. OWL added bloat to make developer lives easier. It was ever thus.
>Doesn't look radically different to how a GUI app that targets a native framework would look today
Modern "Native" frameworks are part of the problem. I cant comment on Windows current state as I havent used Windows since I moved my gaming rig from Windows 7 to Linux many, many years ago but even then Windows frameworks were a complete mess
Take Libadwaita for example. I migrated an old, very simple disk image manipulation utility app last year from GTK2 to modern gnome. No change in capabilities, a simple clone in GTK4 / Libadwaita. It went from using ~19MB to ~185MB without any additional functionality simply by switching the "Native" framework
After my comment https://news.ycombinator.com/item?id=49235430 I've investigated the high RAM jump issue a bit further. It turned out, 60 MB comes from MESA / video graphics driver, right after the first function call, that triggers OpenGL/... context initialization. Thus:
GTK2 14 MB
GTK3 24 MB
GTK4 38 MB (+ 60 MB video acceleration)
What’s our disaster recovery strategy in the event of war and loss of internet?
Or worse yet, a near extinction event and we are forced to rebuild civilisation from memory?
Some of these might seem like extreme edge case scenarios but then history is full of disasters that people didn’t prepare for because they assumed they were too big to fail.
Would you not say that AI is an expression of the sum of all human knowledge? And as humans continue to generate more knowledge, it too, will be added to the AI's representation of it all?
If you did, then I apologise. But my point is about accessing that knowledge when AI isn’t available. Not about how AI discovered its corpus to begin with.
Absolutely we should use all the tools at our disposal which enhances productivity. But that doesn’t mean we shouldn’t also learn how’re to do things for ourselves too.
To use a contrived example, there’s no shame in using a dishwasher. But if you cannot wash dishes by hand when the dishwasher breaks down, then you know you have problems.
I made the general tech-dependence statement, but it sounds like you think it is only AI tech that shouldnt' depend on. I wouldn't worry about it; humanity has proven itself to be INCREDIBLY resilient and adaptable when the things we've come to depend on go away or change materially.
Like I said, I have zero issue being “AI first”. 90% of my day-to-day is using AI. But the part I objected to in the OP was “we don’t need to know things because we have AI” (to paraphrase. So I was asking the question: what if AI goes away?
I agree humans are resilient. But that’a not a good excuse for complacency.
Do we really want to put ourselves in the same situation?
It's like a religion isn't it.
I had played a lot with the Spectrum (a Sinclair zx spectrum 128k) and its BASIC interpreter but that was mostly copying from magazines and changing some parameters. And BASIC is weird :)
A few years later in school in the 90s, Pascal was "the" language that most people learned the basics in, at least in my country.
Unknowingly I sort of absorbed all that and it only started making sense when a few years later I decided to get into actual programming with perl and eggdrop bots and plugins or whatever they were called.
Damn, the 90s, IRC and Quake were awesome!
I used Turbo Pascal in 8th grade to create a simple type of 3d wireframe CAD-like tool on the PC in my bedroom.
Then in AP Computer Science in high school we had (TUI) Turbo Pascal also.
I always remember that type/style of TUI fondly. It periodically pops up in my head out of nowhere. Like just yesterday I randomly decided to add a Borland-style menu to my Starship prompt as an experiment. I accomplished that by writing about two sentences to an AI.
My actual job at this point is feeding tasks into AI and judging whether it answered just the way I wanted.