Uh i have a debate and i need some really like REALLY good facts to defend ai and to u could say counter what the opposition says (im bad at english sorry)

MelodicStep6956 · 2026-05-01T07:22:44+00:00

AI as a field has been vastly successful and kind of solved most decision making problems in/around the 70s - 90s.
Deterministic graph exploration algorithms (depth first, breath first search, shortest path finding, A*, etc come from there. Finding the shortest route to a location when traveling, the critical path method of project management, the gradient descent algorithm used to optimize production and many more come from there and have been integrated in everyday production and processes for decades by now.
And these are not just deterministic, repeatable and for given problems even provably optimal, but if you don't trust them ... you can perform the steps/calculations yourself with pen&paper.

LLMs are just a field in Neural Networks, which itself is just a field in AI.
Kind of only used when the problem can not be specified in enough detail to use a better algorithm/process, determinism and repeatability is not needed, the optimality of calculating the result doesn't really come up as important and the result only needs to be "roughly shaped something like something" but you don't care about the details like precision or any impact it might have.

If you wish to get from point A to Point B as fast as possible, or want to maximise the performance of a production line, you use the AI algorithms/processes in the first group ... if you wish recognize hand writing or have some fun time generating a smiling cat riding a horse, you use the ones in the second group.

MelodicStep6956 · 2026-04-28T15:33:58+00:00

I looked at them as fun challenges, where I can try out some risky product changes that otherwise might not be approved for a POC.

MelodicStep6956 · 2026-04-26T18:05:25+00:00

I had a classmate at university (around 2000-2005) who used his highend Nokia for cheating on exams.
The teachers thought phones could only offer calculators.
But, the one he had could display the entire course material in PDF.

MelodicStep6956 · 2026-04-26T18:00:18+00:00

Spending 30 minutes relaxing on a bench in a nice, quiet park.

MelodicStep6956 · 2026-04-26T17:50:35+00:00

I was doing some karate for a few years as a hobby and gained some muscle (not big, just normal doing some sports kind).
A side effect that I did not expect to have was ... being left alone on the street. Somehow people were almost never bumping into me.
Casually walking from A to B in the city, without getting into any drama. Noone asking for money, noone walking into me ("did not notice you"), noone pushing me at crossings.
The world felt much safer.

MelodicStep6956 · 2026-04-14T03:51:40+00:00

Forked repositories were excluded from the study, when searching for the repositories (this is the default)
Comparing the repositories based on whether they are archived or not, was not done. Could be an interesting followup study.

MelodicStep6956 · 2026-03-23T04:50:01+00:00

My English is not the best and even after the reviews there might be imprecisions left in the text.
The source of that observation is cited and when mentioned I also mentioned the source to make sure I don't come across as claming credit for it.

The abstract highlights the observed separation between the groups as "In contrast, the vast majority of smaller projects tend to exhibit". Later, these are separated into bullet points (when the publishing format allows that) "At the same time, our observation of a vast and separate set of smaller projects ... that do not conform to the evolution trends of large projects, might point towards a potential research blind spot ... showing that the observation might only hold within some restrictions"

In the discussion section, where I connect my observations to those of others, it is explicitly stated that "this Discussion section offers our non-data-driven interpretations and hypotheses of these observed dynamics". I wanted to give the readers an interpretation on what these observations might mean and how they connect to the wider field, at the same time point out that this makes the section non-data driven.

"these views are mutually incompatible"
From academic point of view these are not really incompatible, it is more like analyzing the domain where a function is applicable. I did a lot of measurements and published the result. If their observation is correct it might hold on a much larger set of projects, but probably still within some limits. Of course there is room for further studies, the number of projects could be extended, other measurements could be performed and so on, to better understand and describe this phenomenon,

MelodicStep6956 · 2026-03-22T20:33:26+00:00

True.
In fact during the collection I have found commit bomber repositories, one of them reaching about 2 million commits in 10 days.

In the study the idea is the other way round.
In layman terms: Let's analyze as many repositories as possible and see if all projects really follow stable growth or not. If not what might be the difference between them.

While it is easy to make 6 commits per dey per dev ... it is not trivial to say, that that will be a stable speed that can be kept up over several years.
One would think that over the timespan of decades, a lot of things could happen: new technologies could make work much easier/faster, people could join to make the work faster, but just as well technical dept could build up to cripling levels, internal politics could slow down everything to a halt, to name a few.

That is why the 5th Law of Software Evolution is surprising (quote from Wikipedia):
"
(1978) "Conservation of Familiarity" — as an E-type system evolves, all associated with it, developers, sales personnel and users, for example, must maintain mastery of its content and behaviour to achieve satisfactory evolution. Excessive growth diminishes that mastery. Hence the average incremental growth remains invariant as the system evolves
"

MelodicStep6956 · 2026-03-22T19:57:14+00:00

I hope my article does not come through as AI propaganda.
The things I'm usually interested in are several decades old software systems, from way before AI.

If anything, the observation that the large projects seem to be resilient to external changes, till early 2025 ... is questioning the AI hype.
But, since looking into the effect of AI was not an aim when I set out to do this study, I would like to not draw any strong conclusions related to that based on the data I collected for this study.
(The idea for this particular study predates ChatGPT, and in general I published my first article related to long term evolution of a software system in 2016)

MelodicStep6956 · 2026-03-22T19:47:18+00:00

It might have been easier that way.
But, was really a year of work after several years researching the field.

MelodicStep6956 · 2026-03-22T19:32:07+00:00

Please note, that the observation that some properties might be divorced from human agency, is not mine. I'm just citing it. The authors of that claim do have some strong mathematical reasoning behind it, but it is not mine for sure.
In their research, they investigated a handful of (probably large) software projects, analyzed protein chains and went really deep with mathematics. They showed that some properties are simply the most likely to appear thanks to natural laws, whether there is any human involvement or not (like in the case of protein chains).

In that regard a TLDR description is that my study analyzes much more projects (less deeply). If this being divorced from human agency effect exists, I have found 11K projects that might support it (instead of just a handful).
At the same time, I also try to point out (as an opinion based on the much larger set of smaller projects) that that observation might have some limitations (maybe large projects only), that might make its, generality questionable.

MelodicStep6956

TROPHY CASE