A thought that stayed with me after studying privacy attacks in my AI ethics course:
> Open-weight models are not just trying to catch up with closed models.
> They also face a different threat model; once people can run them locally, fine-tune them, or modify them, evaluation becomes harder.
As someone excited about contributing to open-source LLMs, I think capability alone is not enough. We also need to ask how well these models hold up under open access.
I did not expect one book to carry me through this much of the semester, but Hands-On Large Language Models genuinely helped ๐ญ
It gave me enough foundation to compete in an NLP shared task, understand LLM papers better, and even prepare a lecture presentation for my data mining course ๐ฅน
Update: Less chaos did not happen ๐
But the semester had its moments:
- 2nd place in an Arabic NLP competition
- one paper accepted, another still under review for 2 months ... :)
- my first Arduino project with questionable cable management
- aquascaping experiments
- my cat fighting FIP like a little warrior (3 months and still strong ๐ค๐)
Finals are done, and next semester is the master's project ๐ฑ
[Day 24 of LLM Grind] ๐ค
~ 3 hours of coding
> Deep dive into Arabic text normalization, handling diacritics, elongations, emojis, and noise.
> Explored feature fusion
Planning a multi-feature setup (text + metadata) for improved classification.
Day 23 of LLM Grind โจ
Lazy day today, not feeling 100%, so I kept it light.
~2 hours of chill studying
> Completed a Kaggle certificate in AI Ethics โ ๏ธ
Not every day has to be intense.
Consistency > intensity ๐.
"What's reality? I don't know. When my bird was looking at my computer monitor I thought, 'That bird has no idea what he's looking at.' And yet what does the bird do? Does he panic? No, he can't really panic, he just does the best he can. Is he able to live in a world where he's so ignorant? Well, he doesn't really have a choice. The bird is okay even though he doesn't understand the world. You're that bird looking at the monitor, and you're thinking to yourself, 'I can figure this out.' Maybe you have some bird ideas. Maybe that's the best you can do." ~ Terry Davis
Day 23 of LLM Grind โจ
Lazy day today, not feeling 100%, so I kept it light.
~2 hours of chill studying
> Completed a Kaggle certificate in AI Ethics โ ๏ธ
Not every day has to be intense.
Consistency > intensity ๐.
Day 22 of LLM Grind
~ 4 hours study session
> Changed my visualization library from seaborn to plotly ๐ค all because I needed to plot emojis!
> Did minor text preprocessing (not sure how to go about tbh)
Trends observed in dataset:
- Most polite posts are coming from YouTube.
- Most impolite posts are directed at companies.
- Top 5 emojis used in polite posts: [โค๏ธ, ๐ค, ๐,๐น,๐ฉถ]
- Top 5 emojis used in impolite posts: [๐,๐,๐,๐ฅ,๐ญ]
- There are not that many posts with emojis but most posts with emojis are polite.
- Posts contains links and tags.
- Posts that do contain links are mostly neutral or polite, a small portion is impolite.
Day 22 of LLM Grind
~ 4 hours study session
> Changed my visualization library from seaborn to plotly ๐ค all because I needed to plot emojis!
> Did minor text preprocessing (not sure how to go about tbh)
Trends observed in dataset:
- Most polite posts are coming from YouTube.
- Most impolite posts are directed at companies.
- Top 5 emojis used in polite posts: [โค๏ธ, ๐ค, ๐,๐น,๐ฉถ]
- Top 5 emojis used in impolite posts: [๐,๐,๐,๐ฅ,๐ญ]
- There are not that many posts with emojis but most posts with emojis are polite.
- Posts contains links and tags.
- Posts that do contain links are mostly neutral or polite, a small portion is impolite.
[Day 21 of LLM Grind]
- Spent ~8 hours today working on Arabic politeness classification of social media posts ๐งช
- Did some dataset exploration and modeling choices.
#NLP#LLM#BuildInPublic