Comment by jug
2 years ago
I like this take. It has many clear applications already and LLM's are still only in their infancy. I both criticize and use ChatGPT at work. It has flaws and it has advantages. That it's bullshit or "ELIZA" is a short-sighted view that overvalues the importance of AGI and misses what we're already getting.
But yes indeed, there are many, many AI products launched during this era of rapid progress. Even kind of shoddy products can be monetized if they provide value over what we had before. I think the crowded market and all the bullshit and all the awesome, all at once, is a sign of very rapid progress in this space. It will probably not always be like this and who knows what we are approaching.
How are you using it at work?
I've used it to proof emails for grammar, and it's done ok.
I'll also throw random programming questions into it, and it's been hit and miss. SO is probably still faster, and I like seeing the discussion. The problem with chatGPT right now is it gives an answer like it's certainty when it's often wrong.
I can see the benefits of this interaction model (basically summarizing all the things from a search into what feels like a person talking back), but I don't see change the world level hype at the moment.
I also wonder if LLMs will get worse over time through propagation error as content is generated by other LLMs.
I’m not the person you replied to but I’ve been using OpenAI’s API a lot for work. Some examples:
- Embedding free text data on safety observations, clustering them together, using text completion to automatically label the clusters, and identifying trends
- Embedding free text data on equipment failures. Some of our equipment failures have been classified manually by humans into various categories. I use the embeddings to train a model to predict those categories for uncategorized failures.
- Analyzing employee development goals and locating common themes. Then using this to identify where there are gaps we can fill in training offerings.