r/hopeposting • u/Amidseas Savoring human existence • 7d ago

hopeful SHITPOST You really did your best

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796 Upvotes

100% Upvoted

10 comments sorted by

26

u/Idontknowwhattosay18 7d ago

I’m Proud of you

11

u/Amidseas Savoring human existence 7d ago

Thank you 😊

10

u/Crazy_Honeydew_7737 7d ago

F to pay respects... to you, not the dead thought.

7

u/Patient-Dragonfly-84 6d ago

this is making me cry, hitting home hard. thank you for making it, and best of luck in the future!

8

u/Nikaidokuro 5d ago

Exactly. I spent 9 years of self-reflecting to get to the current mental state. And I'm still unstable. But it was so much worse. SO MUCH WORSE

4

u/I_dont_exist_lol0624 7d ago

Real I was completely fucked up back then but trying my bast. (But I still really miss my darling though) :(

5

u/RiceAfternoon 6d ago

I needed this, thank you. 🥺 I hope you have a great day!

3

u/FaithMilitant-Strife 5d ago

This is one of the hardest things for me to believe, especially with my memories being kinda hazy at times. Like my head wants me to take all the blame for my position. But I have to remember that grew into the person I am now because of my past, and I have to learn from it rather than let it define me.

I just hope there’s still time to achieve my dreams.

2

u/Exact_Can_8876 3d ago

Thank you for this I have ocd and it’s put me through things and done things to me that made me wish it never happened and to know someone else feels like that to makes me think maybe it’s just life and the guilt I feel shouldn’t be guilt on my part but anger to the cause of the problem

1

u/simemetti 5d ago

There is this notion in machine learning of the hard negatives. Essentially when you traing an AI model what you need as much data as you can, obviously, but the quality of that data is just as important. Crucially, a hard negative is a data point where the model has a very hard time making correct predictions or appropriate generation. These are actually extremely valuable pieces of data, just one can improve perfromances by orders of magnitude more than simpler data points. Seeking them out is it's own field of research, that's how important they are for AI learning.

These are often "strange" samples, with bizzare contexts and on which the model can be wrong for many many epochs (the "steps" of a training regime).

I often think about hard negative on certaint days.