[Fis] FIS discussion

Tue Oct 6 13:31:11 CEST 2026

 Dear Jorge and colleagues,

 Thank you for asking, and I agree. The task you describe is one for which TPA with Theme is intended; the free education version 6 can be found on https://urldefense.com/v3/__http://www.patternvision.com__;!!D9dNQwwGXtA!QA-cqZV-lFMcCtGb8OB81P9HxO39QCdHJUp7dGYV-Lzl2ACWDhH8dKGCFQv-KhEMi0kq-ij4cfg$ <https://urldefense.com/v3/__http://www.patternvision.com/__;!!D9dNQwwGXtA!QA-cqZV-lFMcCtGb8OB81P9HxO39QCdHJUp7dGYV-Lzl2ACWDhH8dKGCFQv-KhEMi0kqCrLJ65c$ >

I expect to present the new Theme 7 version online in December, where you would be welcome to attend and receive a beta version. It can handle bigger data, and processing is faster using a parallel algorithm on either CPU or GPU.

Moreover, a new version of a data-coding tool for this kind of data is about to be ready, where events can be coded immediately on a smartphone or smartwatch; the earliest version: ((PDF) Why Search for Hidden Repeated Temporal Behavior Patterns: T-Pattern Analysis with Theme<https://urldefense.com/v3/__https://www.researchgate.net/publication/332818235_Why_Search_for_Hidden_Repeated_Temporal_Behavior_Patterns_T-Pattern_Analysis_with_Theme__;!!D9dNQwwGXtA!QA-cqZV-lFMcCtGb8OB81P9HxO39QCdHJUp7dGYV-Lzl2ACWDhH8dKGCFQv-KhEMi0kq-Q01I7w$ >); the new version is called ThemeWatch 2.0, and I would be happy to provide you with a free beta version.

Regarding the use of AI, I think you could feed the detected T-patterns into an AI tool such as ChatGPT or Claude and ask it to create, for example, a flowchart grammar to summarize the structure. I look forward to trying this and would be happy to do so with you and your data when ready.

Best regards,

Magnus.

________________________________
From: Fis <fis-bounces at listas.unizar.es> on behalf of Jorge Navarro López <jnavarrol at unizar.es>
Sent: 29 September 2026 17:03
To: fis at listas.unizar.es <fis at listas.unizar.es>
Subject: Re: [Fis] FIS discussion

Dear Magnus, Pedro and colleagues,

Thank you, Magnus. I found your ideas very interesting, particularly the discussion around T-patterns.

It made me think about some of the work we are doing on doctor–patient co-decision. We analyse medical consultations as sequences of doctor and patient interventions, looking at sentiment, emotions, entropy and how these evolve during the conversation.

Reading your message, I was wondering whether T-patterns could help us look at these interactions from another perspective: not just how individual measures change over time, but whether there are recurring patterns in the way doctors and patients interact and make decisions together.

We are also starting to explore the use of LLMs in this context, so I found your connection with AI especially interesting. Perhaps there is some common ground here between T-patterns, NLP/LLMs and the analysis of human interaction.

I would be very interested to hear your thoughts.

Best regards,

Jorge

El 28/09/2026 a las 20:34, Pedro C. Marijuán escribió:
Dear Magnus,

Many thanks for your inspiring presentation. I think the functional importance of the fixed memory of "written" strings in the emergence of biological complexity and of social complexity has not been sufficiently highlighted.

On the one side, individuation and species as reproductive communities became possible, and on the other, learned individuals and national as well as religious collectives could be formally structured. Still they form the kernel of our world.

"Scripture" was at the heart of medieval monastic system, which was ruined by the "automation" of texts by the printing press, and wiped out by all the industrial new power and written materialization possibilities. Then, the AI text autonomy of today opens a new era on the unknown.

Around all these systems, the idea of selfsimilarity is tempting, running well in some limited realms, but in general it finds major organization dissimilarities... How could be solved the very different information regimes across scales?

In particular T patterns in behavior look quite cogent, can you explain it a little bit?

Regards,
--Pedro

-------------------------------------------------
Pedro C. Marijuán
Grupo de Bioinformación / Bioinformation Group
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El sáb, 26 sept 2026 10:50, Marcus Abundis <marcus.abundis at gmail.com<mailto:marcus.abundis at gmail.com>> escribió:
Hi Magnus,

I am unsure of what patterns (I need specific examples) you have in mind when you mention ’patterns’. I don’t disagree that such patterns exist, or their importance, but I just don’t know what YOU mean by patterns when you use the word here. In some ways I see what you speak as simply the transition from a purely mechanical stimulus-response 'material inanimate world', onto a more fluid stimulus-processing-response 'adaptive animate world'. The latter realized via 'materially encoded substrates' (information: matter used in a specific manner, that encodes 'behavioral functions' and more), where innate 'meaningful patterns' mark the advent of 'abstraction' . . . later followed by cognitive abstractions, onto society, etc. It thus implies a broad type of a 'theory of meaning', no?

I do not recall anyone writing SPECIFICALLY about this vital 'encoded' inanimate-adaptive transition, but in some ways this transition is also fairly self-evident in the advent of genomics, no? Does one REALLY need to assign new terms (T-strings, T-patterns, etc.) to this matter?! IF one instead detailed SPECIFIC patterns tied to this inanimate-adaptive transition, and other adaptions beyond that, THAT would be important work, I think.

I too work in this area of research, but from a slightly different perspective. Perhaps of interest . . . I attach a draft copy of a related paper I am currently working on that covers this area, for planned presentation at IOCPh2026 in late October.
Understand-able Rudiments in World Modeling<https://urldefense.com/v3/__https://drive.google.com/file/d/1AeML8jcHiGFRR648eZO38vUHCIuRFp0x/view?usp=share_link__;!!D9dNQwwGXtA!UzDd2M9OeN6-i5mBUUQ98Ctv3AV9h8l-7WsbFpghySlO2KLZzfJ-BeRnYpbs56BdxYsI_67kjgX_0MrDUqYrOqaRE4M$>

Marcus
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