51–60 of 206 posts
Unity has “customer support engineers” iirc. The USA misuses the term endlessly
Well most of corporate america certainly does, but they can just as easily be multinationals so its not really the USA other than they may have registered the entity here.
We've seen this before. Back when Google was a search engine, you'd eventually get a feel for how things worked, and build a vocabulary of "spells" that give the results you want, without using the common words with many overloaded meanings. (Example: Annotation instead of mark up, when trying research the Marking Up of Hyperlinked Texts)
Similar things proved to be true of Stable Diffusion and the image generators. It seems quite reasonable to conclude the same will be true of GPT4 and its kin.
Software engineering is also snake-oil. Yes, software can be engineered, but that's not what the vast majority of so-called software engineers are actually doing at their jobs. The title mostly exists to inflate the importance of a programmer with years of experience under their belt. In reality, most of them couldn't explain to you what engineering itself is, and their job primarily consists of duct-taping and build…
React..? Golang? GUIs?! We stepped too far from The Truth (vim, ghc) and now we are all Oilers.
Prompt engineering feels like a quite appropriate name because there is a lot of experimentation and refinement to find good ways to interact with these models (I.e. good prompts!).
It doesn't perfectly map to "engineering", but it maps pretty well. What else would you call an iterative process of experimentation and refinement?
Think of it more as "prompt-fu", akin to "google-fu"--or how to google. You do have to know how to talk to an LLM, and it will be important. But it's not so much engineering, as we come to think of it in software traditionally. I wouldn't get hung up on the name, but just see it for what it is--a bad name for something we'll need to learn to be effective. It won't go away entirely, but will be mitigated to be less im…
LLMs are very quirky. They need the correct context to produce something good and it’s often surprising what that needed context is. OP just play around with midjourney and you’ll soon realize that it is a very real thing
Prompt Engineer is the new Scrum Master.
It's okay; software engineering isn't real either. (In many countries, the word "engineer" is regulated -- you can't call yourself an engineer without professional qualifications and oversight.) https://en.m.wikipedia.org/wiki/Regulation_and_licensure_in_...
When a building collapses you can’t just reboot it But in software you can simulate and test all you want before connecting it to the real world
I think alchemy is a better word. Anyway, if you're trying things iteratively it becomes more a science. Engineering is more like designing stuff and building them without trying lots of things first.
Engineering takes a first-principled approach, where upon knowing those principles you can then construct abstractly without physically building first.
Software engineering is also snake-oil. Yes, software can be engineered, but that's not what the vast majority of so-called software engineers are actually doing at their jobs. The title mostly exists to inflate the importance of a programmer with years of experience under their belt. In reality, most of them couldn't explain to you what engineering itself is, and their job primarily consists of duct-taping and build…
Most SWE is snake oil, take one look around and you'll see what I mean... React..? Golang? GUIs?! We stepped too far from The Truth (vim, ghc) and now we are all Oilers.
Earlier quoted context omitted.
LLMs are very quirky. They need the correct context to produce something good and it’s often surprising what that needed context is. OP just play around with midjourney and you’ll soon realize that it is a very real thing
100%. People who have not tried to interact with these models don't understand there is actually quite a lot of skill in navigating the latent space.
This is also one of the reasons why the problem of transparency ("but why and how does it work?") is so important in Machine Learning: allowing control.