I don't understand my brain when it comes to programming...

I know how to build complex modding systems and RPG mechanics that self balance themselves in games... Yet I don't know how to make a platformer (pretty much where everyone begins)...

And the most recent thing is I can't seem to grasp interpreters and put it into code yet in 4 hours at work when I was working the register I worked out how to build a virtual machine with its own custom vCPU architecture to use in my game engines terminal...

Anyone else have shit like this? I can't be the only one on this...

Fucking elastic appsearch, too many requests per seconds and it dies. It doesn't go slow first, it just dies. No warning just a timeout that lasts until a manual restart in elastic cloud console. Besides being apparently the shittiest product in the elastic stack, it's also the worst documented. And yes I just scaled it up but not being able to handle indexing 100 documents per second with 8 vcpu and 8 gb memory is a shame.

all QBASIC tutorials:

"your scrollers need something to scroll from, so always hold a screen mirror in an array, draw to that and blit it to the screen"

but like

i can scroll anything on screen in Mode 13 with PEEK/POKE. In like... 7 lines? Probably 5 if I fuck with it some?

it's even fast enough to only take 3 frames to scroll one pixel on a 2GHz vCPU!

I have one question to everyone:

I am basically a full stack developer who works with cloud technologies for platform development. For past 5-6 months I am working on product which uses machine learning algorithms to generate metadata from video.

One of the algorithm uses tensorflow to predict locale from an image. It takes an image of size ~500 kb and takes around 15 sec to predict the 5 possible locale from a pre-trained model. Now when I send more than 100 r ki requests to the code concurrently, it stops working and tensor flow throws some error. I am using a 32 core vcpu with 120 GB ram. When I ask the decision scientists from my team they say that the processing is high. A lot of calculation is happening behind the scene. It requires GPU.

As far as I understand, GPU make sense while training but while prediction or testing I do not think we will need such heavy infra. Please help me understand if I am wrong.

PS : all the decision scientists in the team basically dumb fucks, and they always have one answer use GPU.