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).
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)
How did you find these places and what kind of knowledge did you need for it? I definitely find very appealing using my software industry knowledge for the advancement of science
I worked for professors for free in undergrad, and then later for money also in undergrad.
Profs are always looking for research assistants. Granted now is the wrong time to try to break into the industry given the NIH cuts. I was able to get a contracting position with university of pittsburgh and a free gig with CMU just by asking and that pays the bills but its not too much money. However if you don't already have publications you may have to wait until this chaos has wound down (honestly even if you do have publications it'll be hard to get paid until the chaos winds down I think I mostly just got very lucky).
You can always get publications by working in a lab for free and have a real job simultaneously but that is a lot of work.
There are also startups that have similar job descriptions. I worked for Signature Diagnostics for a year and a half and it was very bio/science heavy. But the key skill to break in is publications. I personally don't think this is a great metric, but unfortunately it is the metric.
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.
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.
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).
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)
How did you find these places and what kind of knowledge did you need for it? I definitely find very appealing using my software industry knowledge for the advancement of science
I worked for professors for free in undergrad, and then later for money also in undergrad.
Profs are always looking for research assistants. Granted now is the wrong time to try to break into the industry given the NIH cuts. I was able to get a contracting position with university of pittsburgh and a free gig with CMU just by asking and that pays the bills but its not too much money. However if you don't already have publications you may have to wait until this chaos has wound down (honestly even if you do have publications it'll be hard to get paid until the chaos winds down I think I mostly just got very lucky).
You can always get publications by working in a lab for free and have a real job simultaneously but that is a lot of work.
There are also startups that have similar job descriptions. I worked for Signature Diagnostics for a year and a half and it was very bio/science heavy. But the key skill to break in is publications. I personally don't think this is a great metric, but unfortunately it is the metric.
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.
Sounds like you have an inordinate amount of faith in the market to decide what's fair.
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.
/newest has already been flooded with those generators for the past few days. Spammers always seem to move the fastest.
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.