Yes, it's clearly helpful in programming a variety of platforms. I once asked 
chatGPT if it knew how to program in a certain less commonly used programming 
language and it *modestly* replied that as a large language model it knew how 
to program in all programming languages! 

I also found deepseek interesting because it explains its reasoning before 
giving its final response. For fun, I once responded "thank you!" for a good a 
good response by deepseek and it was entertaining to watch it try to figure out 
why I did that and what the addition of a "!" might mean. It finally concluded 
correctly that I simply liked its response. It was, of course, an unnecessary 
computation it had to perform, so one should not do that.

I think it is useful to try different AI bots. It is a very competitive race 
towards AGI so one can expect many changes. At present, Claude seems better for 
programming tasks, but that could change.

Jim


F. James Rohlf                                    
Distinguished Professor, Emeritus and Research Professor
Depts: Anthropology and Ecology & Evolution
Stony Brook University
On 3/25/2026 8:55:40 AM, Mauro Cavalcanti <[email protected]> wrote:
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Dears Jim, Joe, and Carmelo,

I would like to add my two cents to this interesting discussion.

Based on my own experience (and practical experiments) with AI, I do agree with 
most of the findings and opinions put forth by Jim. I have also found that AI 
is mostly useful to assist in writing and/or debugging code in scripting 
languages like R and Python, but AI is also helpful with programming in more 
traditional, compiled languages like Pascal. At its present state, AI is now 
really more helpful to solve programming problems than skimming the 
documentation or (worse), asking questions in Stackoverflow and waiting a long 
time for answers that are either wrong or irrelevant.

However, I observed that DeepSeek definitely is more efficient than ChatGPT, as 
it seems to be more 'objective' and less prone to 'hallucinate' (I had some 
definitely disturbing sessions with ChatGPT when it 'hallucinated' and not 
surprisingly did not generate anything useful). I have never experienced such 
'hallucinations' with DeepSeek. From my limited experience with Perplexity, it 
seems to be yet more objective than DeepSeek.With Claude I have no experience.

With best regards,

-
Dr. Mauro J. Cavalcanti
E-mail: [email protected] [mailto:[email protected]]
GitHub: https://github.com/maurobio 
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ORCID: https://orcid.org/0000-0003-2389-1902 
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"Life is complex. It consists of real and imaginary parts."

   

Em qua, 25 de mar de 2026 04:51, 'F. James Rohlf' via Morphmet 
<[email protected] [mailto:[email protected]]> escreveu:

Right, that is why I mentioned the idea of sharing and downloading prompts that 
people have tried and found to work properly. It will be useful to share good 
prompts so everyone does not have to repeat the same mistakes.

I worry is that as AI learns more the prompts may have to change. I would hope 
that meanings of words would just become more precise but because AI 
communicates using a "natural language" the meanings might also drift over time 
as in the case of human languages. That could be a real problem for 
computational applications! The prompts may have to become more mathematical 
than they usually seem to be now in order to minimize that problem. 

Jim

__________________
F. James Rohlf, Distinguished Prof. Emeritus 
Dept. Anthropology and Ecology & Evolution 
Stonybrook University


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-------- Original message --------
From: Carmelo Fruciano <[email protected] 
[mailto:[email protected]]>
Date: 3/24/26 8:02 PM (GMT-10:00)
To: [email protected] [mailto:[email protected]]
Cc: Morphmet2 <[email protected] [mailto:[email protected]]>
Subject: Re: [MORPHMET2] Thoughts on morphometric software and AI

Dear Jim,
Thanks for starting this stimulating discussion and everyone else for 
contributing.

In my experimentation with some models I have found - like yourself and other 
people replying - that these tools may be helpful for certain "non-critical" 
tasks to, indeed, increase the efficient use of human time (but, even then, 
there might be arguments to the contrary) but may also silently introduce 
problems which may be hard to spot.

Like you, I do see the potential for these tools and I am very open to the idea 
of them helping in my work.

Going to your more general initial points about the implications of AI and 
whether we'll all soon just write prompts to perform analyses (which is the 
most stimulating part of the conversation), I can think of at least three 
factors that make that problematic in the short run.
*
Most users who want to perform empirical analyses do not have the in-depth 
knowledge required for spotting problems in code, let alone in what's happening 
under the hood of a ready-made AI "app"
*
Often existing software relies both on peer-reviewed papers and on the domain 
expertise of scientist coders who developed the tools. Essentially, most users 
will trust software partly because of the academic accomplishments of the 
people who wrote it. It is an interesting topic and we may discuss about 
whether "it is right" but, to the point, at this stage it is unclear whether 
one can say these "AI models" have "expertise" and who is "accountable" (in a 
broad sense) for what they produce
*
There is a non-deterministic component in the behaviour of these models as they 
are today. For instance, providing a prompt worded differently may return 
different outputs. This raises all sort of issues in terms of reproducibility, 
trustworthiness and ability to actually describe what has been done (which is 
critical for things like drafting manuscripts and going through peer review as 
we know it today).
To my understanding of these tools - which is admittedly quite limited - some 
of these issues stem from the nature itself of these models (e.g., the language 
component, the fact that they do have a context window that gets filled at some 
point, and so on). So, while I think they are very useful tools, I don't think 
they will be - in the very near future (say, one or two years) to replace 
existing software. On the longer term, maybe, who knows!

Just my two cents,
Carmelo



Carmelo Fruciano Department of Biological, Geological and Environmental 
Sciences University of Catania https://www.fruciano.org/ 
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From: '[email protected] [mailto:[email protected]]' via 
Morphmet <[email protected] [mailto:[email protected]]>
Sent: Wednesday, 25 March 2026 03:07
To: Joe Felsenstein <[email protected] [mailto:[email protected]]>
Cc: Morphmet2 <[email protected] [mailto:[email protected]]>
Subject: Re: [MORPHMET2] Thoughts on morphometric software and AI
 
Right, but the trend seems to be towards decreasing the efficiency of 
software/scripts/prompts execution and increasing the efficient use of human 
time. Human time may be more valuable (or just have a rapidly decreasing 
attention span).

Oh, I did not have the foresight to save any of those old IBM 650 manuals. Too 
busy learning new stuff to think about the day when those might be fond 
memories. Of course, they are now all online (IBM 650 Manuals 
[https://protect.checkpoint.com/v2/r01/___https://piercefuller.com/collect/650man/index.html___.YzJ1OnN0b255YnJvb2s6YzpnOjc1YWQwNGJmMGQ4NDJjMDdlNWYyMDhkN2RiNGRmZTQxOjc6ZWFkNjphNjE1NzZkZGEwYWVlOWU4NzA3ZTlkMjhlMDJiYjZjYTJhODI4NmNkODhmYjk1ZmI4NTNmNmY4OTdlNjJkMWFhOmg6VDpG])
 and available for the day I might be feeling nostalgic. Thanks for the 
reminder!

Jim


F. James Rohlf                                    
Distinguished Professor, Emeritus and Research Professor
Depts: Anthropology and Ecology & Evolution
Stony Brook University
On 3/24/2026 3:10:21 PM, Joe Felsenstein <[email protected] 
[mailto:[email protected]]> wrote:
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its authenticity.


Jim noted that AI was:

"Computationally less efficient (so much faster computers are required) but 
easier for humans to use with even less technical knowledge of how computers 
actually work."

It is computationally less efficient if one has to do the AI interaction for 
each 
data set.  But if it is just making Python or R code and giving you that, 
then not computationally much less efficient than just doing your own 
R or Python.

(Reading Jim's list of successive stages, I was 
reminded of much past pain.  I didn't quite start 
with the IBM 650 (instead iof CDC 1604 in 1961), 
but I have saved, from Jim Crow's lab, the user 
manuals for the 650.)

Joe

----
Joe Felsenstein,   [email protected] [mailto:[email protected]], 
[email protected] [mailto:[email protected]]

Department of Genome Sciences and Department of Biology,
University of Washington, Seattle
----
PS Please do not use  [email protected] [mailto:[email protected]].  
It is an alias
and mail systems often recognize that and think it is spam.

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