thats a fantastic strategy thank you, and thanks to all the other helpful posters as well here. do you have any tips for how to choose the base yolo model? or just any generic one will do?
does this mean im actually able to try object detection in opencv now? i mean i know basic image processing techniques, and i know "in theory" how ML works but ive never really seen a case where i can just say "heres an image now detect all the apples". theres always 1. find a model that has the knowledge, 2. hook it up to an inference engine, 3. do something useful. i always get stuck at 1.
this is so true, its hard to make a decision when that actually means you're losing a bunch of other possibilities. so no-decision becomes a decision and then you're left with nothing.
Agree with you there. What you are working on and the commenter below talking about surgery, they are all valid counter examples where the degree of expertise is quite extreme. But most people are not living on the edge of domain expertise. Im guessing 80% of the domain knowledge out there is up for grabs. For example: I dont have to go get a job at a security software company to figure out how security camera systems work and the principles involved, I can ask probing questions of an LLM and get most of it. The domain knowledge is embedded in the model.
This article is wrong. LLM's encode all the domain knowledge you could possibly want. As a software dev I can query an LLM, become a domain expert in a short amount of time, and then code up a solution. If people think their niche is safe from automation, think again. Even the people who think theyre the masterminds at the top.
Edit: Yes "expert" was too strong a word. Proficient would be better. A lot of the barrier to entry in a field is just not understanding the domain.
So youre saying the metaprogramming facilities of C++ allow the compiler to better optimise high level human readable code more effectively than C. Thats a fair point and one I'd never even thought of before, I always thought C was faster because of things like v-tables and all that stuff.
Even if it landed perfectly how is it going to be rapidly reusable with all those tiles breaking and needing repair? Then if that problem was magically engineered-away through some sort of materials science breakthrough, it still makes more sense to me to keep your big ships in a space staging area and your smaller ones as atmospheric gophers.
The videos are great!, but the rest of it is never going to work lol, just never. Even without a rethink about how to get heavy payloads to another planet this is still good entertainment.
Any why would I want to work as a prompt engineer? or with AI tech at all? when I trained as a software developer using my brain to solve problems with data structures and algorithms, not prompts. I outright refuse to do such a thing.
Its not worrying for me. This is what I expect from ad companies so I walk in prepared. What I'm more interested in is how we are going to take this new technology and give it back to people without trying to rip into them, for free. We need a Stallman / Linus of AI.
there is a large incentive for computer programmers to build themselves up in importance. higher wages, better love lives, more status. but most software is pretty mundane and straight forward, or at least should be. fancy architectures rarely pay off and the best solutions are sometimes the most obvious. although i could be suffering from that phenomenon that people in maths have where they struggle to understand then once they grasp it they feel dumb like "ofc i should have known that!"
And people respect certifications, if the trust in those pieces of paper disappears, then like you said, the trust in people with those certs disappears too. I used to think it was just about the knowledge but its not.