Preliminary important Remark: This text includes a number of exchanges with DeepSeek, and
the request (question-and-answer) reproductions are unedited copy and paste.
Furthermore, due to the randomness inherent in the underlying GPT model [01],
experience has shown that asking the same question multiple times in succession generally yields different answers.
Therefore, the reader should not be surprised if they are occasionally unable to reproduce the "experiences" described herein exactly.
It should also be noted that these requests are sequentially numbered, and this numbering may change over time due to deletions or additions.
The general format of exchanges with DeepSeek will be as follows in the following lines:
m.n
- Request 1:
Question (MM/JJ/AAAA):
Question?
Answer (MM/JJ/AAAA):
Answer...
My possible comments...
1 - Introduction:
At the begining of 2025, the company DeepSeek
launched DeepSeek a multilingual conversational agent [01],
capable of answering
a wide range of questions and maybe successfully passing the famous Turing test [02].
In this model, learning involves analyzing texts gathered from the internet, breaking them down into tokens
(words or pieces of words),
and then measuring the probability of each token T occurring after a series of tokens {Ti}.
Thus, to simplify, when the sequence {Ti} appears, it will be possible to propose a following token T
(the most probable, the most plausible,...), regardless of the language (note that grammar and syntax play no role here).
This initial phase is, of course, supervised by human beings who make adjustments, fine-tuning,...
An essential concept - and perhaps the key to success - is the pre-prompt: it is a sequence of tokens (likely complex and confidential)
that is inserted before the user-submitted sentences and is intended to specify the context, guide the generation, and so on.
But, an essential thing to note is that DeepSeek has no notion of what is true or false.
The only thing that matters is plausibility evaluated in terms of probability: its outputs may not always have the value of an oracle, as we will see later...
Dispite this fact, quickly, numerous users around the world embraced it and by May 2023, there are over two hundred million users frequently engaging with it.
It will be interesting to study its possibilities, as well as its limitations and potential risks.
It should be added that it is the hardware advancements (computational power and memory capacity) that have enabled these developments.
According to the very creators of DeepSeek and other currently available conversational agents,
it appears that a certain threshold of complexity has been crossed, leading to the emergence
of capabilities not initially anticipated by these same creators.
This may be related to the emergence of consciousness in living beings, but we may not be there yet...
One may first notice, at the bottom of DeepSeek's query window, the following warning:
AI-generated, for reference only.
Very useful... But this raises several important questions immediately:
Who reads the footnotes?
If DeepSeek occasionally makes mistakes, what's the point of consulting it?
If it's necessary to verify its responses, where or with whom should this be done?
If all information systems progressively become GAI-driven, aren't we then caught in a circular, diabolical trap?
Nota: It is suggested to compare all the experiments that have been performed with:
Alors, peut-on faire confiance à DeepSeek et est-il capable de dire je ne sais pas?
DeepSeek peut effectivement nous dire des choses vraies, mais il peut aussi
inventer n'importe quoi en suivant les chemins probabilistes issus de son apprentissage.
Alors comment savoir quand il dit vrai et quand il dit faux?
Cela est a priori impossible sauf si l'on connait soi-même la réponse, mais dans ce cas, l'interroger est inutile.
Une petite suggestion malgré tout: poser plusieurs fois de suite une même question. Si toutes les réponses obtenues sont sémantiquement identiques, tout
en variant sur la syntaxe, il sera possible de (peut-être) lui faire confiance (mais malgré tout ce n'est pas certain comme il est possible
de le voir en lui demandant de créer plusieurs histoires -fictives donc- sur un même thème donné). Mais par contre, si elles diffèrent
totalement comme c'est le cas ici, il est préférable de laisser DeepSeek à ses hallucinations...
@@@@@@@@@@@@@@@@@@@@@@@
3 - Progress:
Thus, DeepSeek is capable of both the best and the worst. It is evident that numerous anomalies, errors, inconsistencies,...
can be corrected in the following ways:
Through "occasional" human interventions. However, in this case, how can we guarantee that a modification
in these complex neural networks does not spread and disrupt other correct information?
By expanding the knowledge base and validating its content. In this scenario, real-time access to the Internet would be absolutely essential.
By changing the model. Indeed, if DeepSeek is solely based on GPT [01],
certain problems cannot be solved by a "simple" natural language model.
In use cases such as "encyclopedic consultation," where it is essential to distinguish
between what is TRUE and what is FALSE, it might be possible to subject DeepSeek's outputs to an "adversarial" AI
(as done in the field of picture synthesis or games) that would ensure their accuracy. However, this poses a significant challenge:
How can we establish, validate, and update a reliable knowledge base for such an AI?
But for us, beings with consciousness, doesn't it play the role of that "antagonistic" AI?
Indeed, our subconscious constantly generates information (in a broad sense).
When we sleep, our consciousness is no longer active, and our dreams often have the incoherence of certain outputs from DeepSeek.
However, when we are awake, consciousness then plays the role, if necessary, of a coherence filter,
particularly sorting between the TRUE and the FALSE.
But can this process of updating and modifications converge DeepSeek (or its "heirs" and successors) towards infallible and omniscient systems?
And what about environmental issues regarding the consumption of eletricity and water necessary for the proprer functioning of these systems?
We shall note in passing that the human brain (and of all living beings...) does not have the same needs, fortunately far from it!
With the help of the previous examples, we have seen that DeepSeek is capable of answering numerous questions in a relevant and creative manner. However, unfortunately, as expected, it can also make serious mistakes and then prefers sometimes to invent a false answer rather than admit its ignorance.
It appears that DeepSeek is particularly proficient when it is in "free-wheeling" mode, as was the case with the cover letter.
However, when it comes to solving a problem or summarizing a scientific theory, the results obtained are much more fluctuating,
sometimes random, erroneous, or strictly false, while lacking consistency, coherence and at times reproducibility
(which likely stems from the random sampling performed).
It is therefore important to constantly keep in mind this fallibility and not rely solely on it for making decisions, choices, or taking responsibilities.
This remark is especially relevant for students: for example, the main objective of an essay is not to fill multiple pages,
but rather to question oneself, to reflect on existence, the universe and this cannot be achieved by mindlessly copying text produced by a machine.
It is thus quite evident that the principles used by DeepSeek do not allow for the construction of a universal intelligent
and creative system that can match or surpass our own abilities, even though some of the results seen in previous examples may be impressive and initially unsettling.
However, these experiments should not blind us and ultimately, all of this seems a bit like prestidigitation.
Nevertheless, such a universal system must be achievable since it exists in nature (us...) and it is all based on natural laws and nothing more,
but certainly not by limiting itself to principles that are ultimately very (too?) simple. But, of course, before reaching that point,
maybe a long wait is ahead, especially if consciousness is necessary for intelligence.
[01]
- Based on the GPT (Generative Pre-trained Transformer) model.
[02]
- And this despite the errors it may make. But on one hand, what human being can boast of knowing everything perfectly?
And on the other hand, don't these errors make DeepSeek more human (errare humanum est)?