I think the entire field of AI (not just the generative AI subset) should've been called "simulated intelligence" or something like that. It points to the goal of the field (i.e. to achieve something similar to intelligence) without the implicit claim that any of the contributions achieve true intelligence.
I didn't shove it that deep. I just tried to clean just inside my ear, which was enough to shove some ear wax further up my ear and clog it. I now know (and frequently lecture my wife) that qtips should only be used on the outside of the ear.
I inadvertently clogged one of my ears with a Qtip, effectively making me deaf in that ear. I tried to wait it out, but I eventually started to get a headache. Went to the clinic, and they flushed my ear out. I don't use Qtips anymore.
Yeah, I will not pretend that I did not have fun with it. However, by the end of it I had not desire for more of it. As a result, I haven't played any of the sequels.
I find it kind of funny that Spider-Man is held up as some sort of golden standard to adhere to in all of this. Spider-Man is also very average game imo. The gameplay is not very compelling, and it's no surprise that Insomniac's approach would overstay its welcome after a couple of games. Doubly so when you move from Spider-Man, a character with a more diverse moveset and inherent better traversal abilities, to Wolverine.
Bright white gravy is probably garbage from a packet. A gravy made with quality, flavorful sausage will always add a bit of color.
I always thought it was because they essentially pioneered the "rock music for commercials" genre
I honestly think trying to define programming as art is just an attempt to unnecessarily elevate it. Programming is utilitarian. It is meant for a specific practical purpose. It does not reveal a shared human experience the way a movie, book, or game does. I have no need to convince myself, a professional software engineer of this because I am perfectly happy accepting that what I do is useful and do not need to try to put myself in a category with artists.
All the author is saying is that people enjoy programming. I also enjoy eating. Is that an art? I even have my own "eating style" in that I like to eat food in specific order, combine two items into one bite, the way I build a bite, etc. But I'd never try to elevate it because I'm a normal person who doesn't waste brainpower trying to make myself feel special.
I simply chose my field based on what I knew I enjoyed. I already had a job with working in systems, and I had HPC/FPGA experience from undergrad. Basically, I choose topics that I had at least a basic understanding and desired to expand into mastery.
I will be honest and say I don't think you've really thought this through. I would really weigh the pros and cons of the degree. Think about what you'd do instead of pursuing a degree. Identify a specific job you would want after you get your degree. If you only want to teach, you could be an instructor at a University, but the pay will not be good. If you want to do research, doing reaearch at a university level will require a PhD. Research centers will hire MS holders, but as engineers rather than researchers. If you want an industry job, make sure you actually need the degree you are thinking of getting.
For 99% of people, carrying on with the degree they have is the better choice. In your case I'd either make sure you consider the above or only pursue a master's if you truly cannot get the job you want with self-teaching.
I don't mean python and SQL. Anyone with a decent software background can pick that stuff up. As an example, my background is in high performance computing, networking, systems, and FPGAs. All of these are fields (well, maybe not FPGAs) that ML/AI rely heavily on, but if AI/ML disappeared tomorrow they'd still be incredibly relevant. Another approach is to study a domain science and apply AI/ML. For example, high energy physics leverages AI/ML, at least in research.
TBH, "wanting a good job" is a very generic response that needs more context. Are you moving from somewhere other than software? If you already have a software background, you might be better of self-teaching. If you are actually interested in research/teaching, that needs to be thought through very thoroughly. I say this as someone who just finished their PhD in CS, just to give context as to why I am being particularly intense on this point.
I would not enter AI/ML for one simple reason: it is oversaturated. Everyone and their brother is in tgis field, and even those outside of it still study it and us it. Unfortunately the way to stand out within AI/ML field is to have a very good mathematics/statistics foundation and really understand the theory behind it. You would be better served by getting skills in another field that AI/ML relies on or where AI/ML can be applier.
BTW, you should also state what you plan on doing with your degree. There is no point in getting a degree if there isn't a concrete benefit to doing so.
I have put on that much muscle. I just refuse to buy any kool-aid that's being sold to me. Maybe they should bring proof instead of spreading trends blindly?