From: mds@bogus.nodomain.nowhere   
      
   Nearly 40 years ago, the MIT press published Parallel Distributed   
   Processing, Vol. 1 & 2, by Rumelhart, McClelland et al. I read those   
   as well as similar material published at MIT in the early 90s, wrote   
   some functional toy code (on an Osborne I).   
      
   But I haven't kept up.   
      
   Can someone suggest books at more or less the same level of   
   technicality that that I might look at to catch up a bit on how neural   
   nets are now constructed, trained, connected etc. to produce what is   
   being called "large language models"?   
      
   The net is of course rife, indeed inundated, with stuff on the topic.   
   But the vast bulk of it falls into one of two categories. One category   
   is mass media news and pop science reporting, intended to provoke "Oh,   
   gee whiz" by the average person or at best a vague notion of the   
   subject for for the literate but non-technical.  The other category   
   is material intended for someone who has read all the technical   
   literature for the last 40 years or at least has obtained a master's   
   degree in AI computing/theory in the last decade.  In the latter case,   
   just the terminology is a barrier.   
      
   I'm now an old guy.  I'm not going to completely beat up all the math   
   that has evolved since PDP but I'd like to get a more or less   
   caught-up handle on how this stuff works internally.   
      
   Any suggestions?   
      
   [ Yes, I had a look at some of the AI newsgroups.  Moribund or   
   highjacked by politics.]   
      
      
   --   
   Mike Spencer                  Nova Scotia, Canada   
      
   --- SoupGate-Win32 v1.05   
    * Origin: you cannot sedate... all the things you hate (1:229/2)