When I search this topic online, I always find either wrong information or advertising lies. So what is actually something that LLMs can do very well, as in being actually useful and not just outputing a nonsensical word salad that sounds coherent.
Results
So basically from what I’ve read, most people use it for natural language processing problems.
Example: turn this infodump into a bullet point list, or turn this bullet point list into a coherent text, help me with rephrasing this text, word association, etc.
Other people use it for simple questions that it can answer with a database of verified sources.
Thanks guys.
I find they’re pretty good at some coding tasks. For example, it’s very easy to make a reasonable UI given a sample JSON payload you might get from an endpoint. They’re good at doing stuff like crafting farily complex SQL queries or making shell scripts. As long as the task is reasonably focused, they tend to get it right a lot of the time. I find they’re also useful for discovering language features working with languages I’m not as familiar with. I also find LLMs are great at translation and transcribing images. They’re also useful for summaries and finding information within documents, including codebases. I’ve found it makes it a lot easier to search through papers where you might want to find relationships between concepts or definitions for things. They’re also good at subtitle generation and well as doing text to speech tasks. Another task I find they’re great at is proofreading and providing suggestions for phrasing. They can also make a good sounding board. If there’s a topic you understand, and you just want to bounce ideas off, it’s great to be able to talk through that with a LLM. Often the output it produces can stimulate a new idea in my head. I also use LLM as a tutor when I practice Chinese, they’re great for doing free form conversational practice when learning a new language. These are a just a few areas I use LLMs in on nearly daily basis now.
I use LLMs to generate unit tests, among other things that are pretty much already described here. It helps me discover edge cases I haven’t considered before, regardless if the generated unit tests themselves pass correctly or not.
Oh yeah that’s a good use case as well, it’s a kind of a low risk and tedious task where these things excel at.