>> Crypto, ML, Data, Quantum Computing > I think the key is to focus and prioritize I think prioritizing is the key. Part of that is figuring out What is pa

>> Crypto, ML, Data, Quantum Computing > I think the key is to focus and prioritize I think prioritizing is the key. Part of that is figuring out What is past its prime (Cobol on punch cards), or never really had its day in the sun at all. What is dull but you can make money with, which will probably be around in some form five years from now too (backend programming of micro-services with a popular JVM language) What exciting things are coming into being now which might have some jobs or interesting applications now, or perhaps a lot more in a few years (training and using deep learning models). Crypto nowadays is mostly a scam which began unwinding over a year ago. Probably best to ignore it, its day is past. Quantum computing is interesting but it's such early days that you can put off reading about it this year if you're overwhelmed. ML and big data have had a lot of interesting applications this year. GPT, Stable Diffusion, DALL-E. I can do some pretty cool things on my workstation with Stable Diffusion that was not able to do five months ago. If you have time to look into something new this would be it. As I said, there's modern but dull and not much new innovation things, which there is steady work and money in like React front end programming, or JVM Microservice backend programming, or whatever. There are also things like deep learning which are going from innovation to innovation, which is exciting and may open up a whole new field (Stability AI just got $100 million in funding, although things are so new, they only started putting their hiring team together last month - they're mainly recruiting recruiters right now).