<html><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"></head><body dir="auto"><div dir="auto">Langchain is an agent framework started by Harrison Chase. A Langchain agent uses LLMs to reason in a perceive-reason-act cycle. One could argue that Langchain agents are able to think, and we are even able to watch them thinking</div><div dir="auto">https://github.com/langchain-ai/langchain</div><div dir="auto"><br></div><div dir="auto">deeplearning.ai has free courses about Langchain</div><div dir="auto">https://www.deeplearning.ai/short-courses/langchain-for-llm-application-development/</div><div dir="auto"><br></div><div dir="auto">-J.</div><div dir="auto"><br></div><div><br></div><div align="left" dir="auto" style="font-size:100%;color:#000000"><div>-------- Original message --------</div><div>From: Russ Abbott <russ.abbott@gmail.com> </div><div>Date: 1/28/24 9:58 PM (GMT+01:00) </div><div>To: The Friday Morning Applied Complexity Coffee Group <friam@redfish.com> </div><div>Subject: Re: [FRIAM] Honeymoon over! </div><div><br></div></div><div dir="ltr"><div style="font-family:arial,helvetica,sans-serif;font-size:small;color:#000000" class="gmail_default">Sorry you couldn't get through. The abstract for the abstract had to be submitted separately. Here it is.</div><div style="font-family:arial,helvetica,sans-serif;font-size:small;color:#000000" class="gmail_default"><br></div><div style="font-family:arial,helvetica,sans-serif;font-size:small;color:#000000" class="gmail_default">LLMs are strikingly good at generating text: their output is syntactically correct, coherent, and plausible. They seem capable of following instructions and of carrying out meaningful conversations. LLMs achieve these results by using transformers to produce text based on complex patterns in their training data. But powerful though they are, transformers have nothing to do with reasoning. LLMs have no means to build or to reason from internal models; they cannot backtrack or perform exploratory search; they cannot perform after-the-fact analysis; and they cannot diagnose and correct errors. More generally, LLMs cannot formulate, apply, or correct strategies or heuristics. In short, LLMs are not a step away from Artificial General Intelligence.<br></div><div style="font-family:arial,helvetica,sans-serif;font-size:small;color:#000000" class="gmail_default"><br></div><div style="font-family:arial,helvetica,sans-serif;font-size:small;color:#000000" class="gmail_default">A pdf of the full abstract is attached.</div><div><div data-smartmail="gmail_signature" class="gmail_signature" dir="ltr"><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><font><u style="color:rgb(33,33,33);font-family:"Helvetica Neue",Helvetica,Arial,sans-serif;font-size:16.5px;line-height:20px"><br></u></font></div><div dir="ltr"><font><u style="color:rgb(33,33,33);font-family:"Helvetica Neue",Helvetica,Arial,sans-serif;font-size:16.5px;line-height:20px"> </u></font><span style="color:rgb(33,33,33);font-family:"Helvetica Neue",Helvetica,Arial,sans-serif;font-size:16.5px;line-height:24.75px"> </span>-- Russ</div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div><br><div class="gmail_quote"><div class="gmail_attr" dir="ltr">On Sun, Jan 28, 2024 at 10:12 AM Steve Smith <<a href="mailto:sasmyth@swcp.com">sasmyth@swcp.com</a>> wrote:<br></div><blockquote style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex" class="gmail_quote"><u></u>
<div>
<br>
<blockquote type="cite">
<div dir="ltr">
<div style="font-family:arial,helvetica,sans-serif;font-size:small;color:rgb(0,0,0)" class="gmail_default"><br>
</div>
<div style="font-family:arial,helvetica,sans-serif;font-size:small;color:rgb(0,0,0)" class="gmail_default">And
if you're interested, my <a href="https://pretalx.iacapconf.org/iacap-2024/me/submissions/N388VQ/">long abstract submission to
IACAP-2024</a> has related thoughts. (Scroll down until you
get to the link for the actual paper.)</div>
</div>
</blockquote>
<p>Russ -</p>
<p>I am interested in reading your abstract/paper...<u><br>
</u></p>
<p>I signed up for an IACAP account but the link you provided seems
to be dead?</p>
<p>- Steve<u><br>
</u></p>
</div>
-. --- - / ...- .- .-.. .. -.. / -- --- .-. ... . / -.-. --- -.. .<br>
FRIAM Applied Complexity Group listserv<br>
Fridays 9a-12p Friday St. Johns Cafe / Thursdays 9a-12p Zoom <a rel="noreferrer" href="https://bit.ly/virtualfriam">https://bit.ly/virtualfriam</a><br>
to (un)subscribe <a rel="noreferrer" href="http://redfish.com/mailman/listinfo/friam_redfish.com">http://redfish.com/mailman/listinfo/friam_redfish.com</a><br>
FRIAM-COMIC <a rel="noreferrer" href="http://friam-comic.blogspot.com/">http://friam-comic.blogspot.com/</a><br>
archives: 5/2017 thru present <a rel="noreferrer" href="https://redfish.com/pipermail/friam_redfish.com/">https://redfish.com/pipermail/friam_redfish.com/</a><br>
1/2003 thru 6/2021 <a rel="noreferrer" href="http://friam.383.s1.nabble.com/">http://friam.383.s1.nabble.com/</a><br>
</blockquote></div>
</body></html>