Game development always scared me as one of those studies that you hope your kids don't get interested in. Another one is manual drawing, especially when it is Anime (what are the chances that someone from a small European country is going to excel at such a job?).
> Abandoning the game completely doesn’t seem like a sane option, after all the time I put in.
Addictive games use the above cognitive bias to make you keep coming back, trying to level up by grinding boring quests. "You are not done yet, but the end is in sight!".
As a good game dev, in 3 years, you can: Learn TensorFlow. Publish an AI paper. Beat state of the art on a few datasets.
>in 3 years, you can: Learn TensorFlow. Publish an AI paper. Beat state of the art on a few datasets.
As a low income indie dev without the academic credentials to get past HR gatekeepers for stable full time work, I can't help but feel studying ML is about as wishful as creating a hit game. I have started studying ML this summer, and although I find the NLP applications really interesting since I have a social science background that exposed me to some literary theory and linguistic ideas that overlap with NLP at times, I think making a living wage doing it is just as much of an unrealistic dream as writing some killer app. The jobs all require PhDs, and the data science competitions have literary thousands of people with PhDs and industry experience competing for five figure prizes. When one is poor with no prospects these kind of pipe dreams feel so good to get caught up in as that sweet haze of hope numbs the critical thinking, but in a clear moment it looks like the ML gold rush is exactly the same as every other tech hype. That's not going to stop me from geeking out on PyTorch and trying to wring sentiment out of blocks of text or whatever, but I won't be able to honestly write a blog post about it in a few years asking if I wasted my time. I already know the answer.
Millions of people taking ml courses. Very few get jobs because for every 50 devs you need one data scientist. It's like design but way overhyped. Also from my experiences the ones that get hired are not the best or knowledgeable but the ones with good sales qualities that can continuously bullshit the employer. I'm talking about your average software company not FB/Google.
ML is like painting, writing... it's good to know but not to make a career of it
Likely influenced in part by survivor bias. I don't have a PhD either. You can say I have a more practical than theoretical understanding of dropout.
The way to get past HR gatekeepers is to bypass HR. If you ask an employee: "Hey, I'd really like to work at your company for a while now. Can you share some resources/tips that would help me prepare for function x?" and you don't get useful feedback, you don't want to work there. If you send a data science lead a notebook where you solve a problem that is relevant to their business and you don't get a job interview, you don't want to work there (or need to brush up on your presentation and analytics skills).
Do the fast.ai courses. I promise you there are more profitable jobs available in ML than in indie game dev. Become good at using ML tools and data science (Python) and/or data engineering and data infra (Scala, AWS, Docker).
> Abandoning the game completely doesn’t seem like a sane option, after all the time I put in.
Addictive games use the above cognitive bias to make you keep coming back, trying to level up by grinding boring quests. "You are not done yet, but the end is in sight!".
As a good game dev, in 3 years, you can: Learn TensorFlow. Publish an AI paper. Beat state of the art on a few datasets.