So now almost all the low hanging fruit programming books have instantly become redundant and off-shored to ChatGPT, and will stay on the shelves to collect dust.
New here comes the race to create prompt engineering books and courses in. 24 hours to sell to other AI bros who think that they are prompting it wrong, not prompting hard enough or the prompting the wrong way.
> here comes the race to create prompt engineering books and courses in. 24 hours to sell to other AI bros who think that they are prompting it wrong, not prompting hard enough or the prompting the wrong way.
That’s already been happening for a couple of months now.
Hilariously some of the AI bros that sell the AI prompting video lessons do not put effort into quality of the material of the videos. Instead they make use of the AI themselves to shovel out low quality garbage, which they then package as expert advice and sell to others.
> New here comes the race to create prompt engineering books
Let's call it "Language [based] Programming", LP for short, as opposed to "prompt engineering" and "programming language". It's programming, in language. Not just prompting, it can be multi-step, involve multiple models and plugins, have branches and loops. And it's not just a new programming language, it's the Language itself.
I feel like there's a difference between prompt engineering, and just plain being good at prompting. Prompt engineering is when you code up stuff in things like langchain and pinecone to query documents or databases the model wasn't trained on. Being good at prompting is not a unique skill, it just takes experience with the model. Whereas engineering a way to prompt the model in way you aren't able to - that is prompt engineering. Or maybe prompt hacking?
OK, now extract this sentiment to the whole of academia. By the time the average syllabus starts being taught at an academic institution, it can be several years out of date, and by the time you finish it, it's already five years out of date.
Takeaway: there's a lot wrong with the existing educational system and how we pass on actionable theory.
I actually no idea how one could teach stuff like Bag of Words naive bayes classifier etc for a whole semester and charge $4000 like most universities- with a straight face
Those kinds of classes aren't for building ML applications but for understanding all the ideas behind ML, even historical ones, for broad theoretical coverage. Parts of current methods were considered "obsolete" for a good 20 years and fads go in and out.
New here comes the race to create prompt engineering books and courses in. 24 hours to sell to other AI bros who think that they are prompting it wrong, not prompting hard enough or the prompting the wrong way.