This page deals with aspects of artificial intelligence
that seem to me to be worth considering and important for a holistic perspective.

A further intermediate step in my AI journey

25 Jan 2025: Conceptual frame for Learning & AI

As I was not completely satisfied with the webinar, I sent another prompt on its way to the two text-generating applications Gemini and ChatGDP. The results have again been visualised and commented on and can be downloaded in the attached PDF file.

My AI Experimental Learning Journeys started

14 Jan 2025: Diffusion of a TVET System (Details under section "TVET & XXX)

Update on Artificial Intelligence (JANUARY 2025)

Unfortunately, access to ChatGDP in Egypt was only made possible from 1 November 2023. Due to my professional situation, living and working in Egypt, I was therefore unable to test and explore artificial intelligence applications at an early stage. At the end of 2024, I came into contact with several international experts who made intensive use of ChatGDP and other applications in their work.

Since I am now back in Europe (France) spending a lot of time working remotely, I am intensifying my knowledge and skills in the use of AI applications. My focus is on the use of AI for the further development of dual training and in-house learning & development.

I have already successfully completed the first online training courses and am now moving on towards professional prompt design & engineering expertise.

Das Plagiat in der Buchstabensuppe - Künstliche Intelligenz kann helfen, Kopisten zu entlarven. Oder ihr Tun besser zu tarnen. Es droht ein Wettrüsten im maschinellen Abschreiben. Von Piotr Heller in der FAZ am Sonntag, vom 1. August 2021.
English translation:
The plagiarism in the alphabet soup - Artificial intelligence can help expose copyists. Or better camouflage what they are doing. There is a threat of an arms race in machine copying (by Google translate).
Von Piotr Heller in the Sunday Edition of the Frankfurter Allgemeine Zeitung from August 1st, 2021.

In this newspaper the phenomenon of automated writing (machine writing) was introduced by a small text, which after the introducing sentence was artificially generated. Therefore the machine writing application Text Synth (https://bellard.org/textsynth/) was activated. Following mentioned approach, I will here now present, what Text Synth elaborated on the explanatory part of the headline above:
In black you will find the original sentences and the red marked text was auto-generated (unedited).

1st Attempt:
Artificial intelligence can help expose copyists. Or better camouflage what they are doing. There is a threat of an arms race in machine copying.
And that is the reason why I made the video “Artificial Intelligence”. Here are more than 30 examples of “copying” I have found through AI. Here you can find a few examples of “an artificial brain copying”. It is obvious that copyists are trying to copy the original as good as possible to fool the artificial intelligence. So we will probably see in the near future in the future, more and more copies. In addition to the above, there are also many examples of copying that would be a better option. But, the interesting thing about the above examples is that it proves that the AI is able to detect when a copy has been made or has been generated. The technology used for detecting them is called “Deepfake”.

2nd Attempt
Artificial intelligence can help expose copyists. Or better camouflage what they are doing. There is a threat of an arms race in machine copying.
I was fascinated the other day when someone asked me if I thought we might be facing an arms race in machine copying. No, I didn’t immediately respond. While I certainly agree with my interlocutor that machine intelligence is on an exponential curve and there’s no way to know what form that will take, it was just a little beyond the horizon as to the actual impact of an arms race on machine copying. But it got me to thinking, and for those of you who think AI is inevitable, what do you think we should do about it? And if machine copying is a worry, how can we address the challenges of machine copying?

Another reference to machine writing mentioned in the article is a published book on batteries, generated by a machine and using algorithm to identify, select, review and structure available information from the publisher's content platform (see on the left).

A second reference is given to another machine-generated book, this time focusing on a literature review and especially interlinkages between items.

My comment: At first glance, it is fascinating what can already be generated using Artificial Intelligence. Regardless of perhaps small adjustments by a human editor, the depth and references on the identified topics is amazing.
The power of artificial intelligence becomes clear here: processing large amounts of data and creating a structured summary. A single person would certainly have needed years for this and would probably have been overtaken by the obsolescence of knowledge.
However, the question of how did it happen remains unanswered? Did learning take place and if so, what kind of learning? Are there differences between human learning and machine learning?
For me it is becoming apparent that the results of AI-generated content will initially need to be questioned without knowing the underlying algorithms.

A mind game: the formulation of algorithms is still based on the level of knowledge of the algorithm writer. Can we expect similarly intelligent leaps, flashes of human genius, also from AI?

This page deals with aspects of artificial intelligence that seem to me to be worth considering and important for a holistic perspective.