Personally I've had a lot of success working in non software science/engineering labs. I'm currently applying software and AI to biotech (don't worry its not LLMs). I think that is where a lot of the utility of AI is because we 'traditional software' is quickly becoming a solved problem. Its a lot more interesting in my opinion to use software to solve real science and engineering problems that they haven't been applied to, and it typically pays well unless you work directly for a university (in which case you may get defunded because of the current administration and even before the current political situation the pay was lousy)
Afaiu, 95% of "AI" work is collecting data that others don't give away easily. At least in the areas where money at. And only 5% is actual AI. So I'd capitalize on reveng skills in this case.
> Unfairly compensated
First, test this assumption by getting another job offer — even in a role that doesn’t make much use of AI.
get ahead of the wave, stop playing in the beach break. If anyone knows what you are talking about you are already behind.
With the new API for GPT-4o image gen releasing soon, we'll probably see a wave of hype products (ie "generate your own Studio Ghibli-style photo album"). I expect these will die down rather quick, but first mover advantage should still net you some profit here.
data as a business, now everyone needs good data to plug it into their ai.
get in front not stay behind the wave ;)
See, that’s the thing they’re trying to solve with AI. Wages. That’s the trillion dollar problem they’re solving.
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That's like asking how to make money on the internet. The answer is to integrate it into something you already know how to monetize -- an area where you already have expertise.
If you work in software, this would be figuring out how to include AI in the kind of software you make (for the user; RAG) and in your process (agents).