<div dir="ltr">For sure, the more info the better, but I do not think it will be a big difference.</div><br><div class="gmail_quote gmail_quote_container"><div dir="ltr" class="gmail_attr">On Sat, Jan 10, 2026 at 4:53 PM Hilaire Fernandes via Cuis-dev <<a href="mailto:cuis-dev@lists.cuis.st">cuis-dev@lists.cuis.st</a>> wrote:<br></div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex"><u></u>
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<p><font size="4">I am wondering if LiveTyping could not be a
leveler to add object semantic while training an AI.</font></p>
<p><font size="4">Hilaire</font></p>
<div>Le 05/01/2026 à 00:12, Phil B via
Cuis-dev a écrit :<br>
</div>
<blockquote type="cite">
<div>If you're thinking about anything serious with an LLM, I
think you're going to want to go with a RAG solution that feeds
in code from the image as well as other relevant code (from
Smalltalk as well as other languages) and other information for
what you are working on. Could you feed in just the code from a
Smalltalk image into a 1 million+ token context window? Sure,
but I don't think you'd get nearly the results you're
expecting... unless you're doing image development rather than
application/library development. I have gotten some stunning
results with RAG-based systems and lesser used programming
languages/libraries precisely because the RAG environment had
comprehensive coverage of how to solve problems in other
languages and it was able to translate the answer in my target
language.</div>
</blockquote>
<pre cols="72">--
<a href="http://mamot.fr/@drgeo" target="_blank">http://mamot.fr/@drgeo</a></pre>
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