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I have used neural networks for engineering problems since the 1980s. I say this as context for my opinion: I cringe at most applications of LLMs that attempt m

I have used neural networks for engineering problems since the 1980s. I say this as context for my opinion: I cringe at most applications of LLMs that attempt mostly autonomous behavior, but I love using LLMs as ‘side kicks’ as I work. If I have a bug in my code, I will add a few printout statements where I think my misunderstanding of my code is, show an LLM my code and output, explain the error: I very often get useful feedback. I also like practical tools like NotebookLM where I can pose some questions, upload PDFs, and get a summary based in what my questions. My point is: my brain and experience are often augmented in efficient ways by LLMs. So far I have addressed practical aspects of LLMs. I am retired so I can spend time on non practical things: currently I am trying to learn how to effectively use code generated by gemini 2.0 flash at runtime; the gemini SDK supports this fairly well so I am just trying to understand what is possible (before this I spent two months experimenting with writing my own tools/functions in Common Lisp and Python.) I “wasted” close to two decades of my professional life on old fashioned symbolic AI (but I was well paid for the work) but I am interested in probabilistic approaches, such as in a book I bought yesterday “Causal AI” that was just published. Lastly, I think some of the recent open source implementations of new ideas from China are worth carefully studying.

hangonhn 2y ago
I'll add this in case it's helpful to anyone else: LLMs are really good at regex and undoing various encodings/escaping, especially nested ones. I would go so far to say that it's better than a human at the latter. I once spend over an hour trying to unescape JSON containing UTF8 values that's been escaped prior to being written to AWS's Cloudwatch Logs for MySQL audit logs. It was a horrific level of pain until I just asked ChatGPT to do it and it figured out all the series of escapes and encoding immediately and gave me the step to reverse them all. LLM as a sidekick has saved me so much time. I don't really use it to generate code but for some odd tasks or API look up, it's a huge time saver.
- arrakark 2y ago
  > LLMs are really good at regex Maybe that's changed recently, but I have struggled to get all but the most basic regex working from GPT-4o-mini

hangonhn 2y ago

I'll add this in case it's helpful to anyone else: LLMs are really good at regex and undoing various encodings/escaping, especially nested ones. I would go so far to say that it's better than a human at the latter. I once spend over an hour trying to unescape JSON containing UTF8 values that's been escaped prior to being written to AWS's Cloudwatch Logs for MySQL audit logs. It was a horrific level of pain until I just asked ChatGPT to do it and it figured out all the series of escapes and encoding immediately and gave me the step to reverse them all. LLM as a sidekick has saved me so much time. I don't really use it to generate code but for some odd tasks or API look up, it's a huge time saver.

arrakark 2y ago
> LLMs are really good at regex Maybe that's changed recently, but I have struggled to get all but the most basic regex working from GPT-4o-mini