u/Sea_Bass7670

I’m using Obsidian a lot in my master’s thesis. One problem I frequently encounter when taking notes on articles written in different languages is that some concepts with the same meaning obviously have different words in each language. As a result, I end up with repeated or very similar notes.

Should I translate the concepts into a single chosen language and insert them somewhat awkwardly into the texts, translate all the texts, or simply keep separate notes for similar concepts in each language?

Hey everyone,

I’m a master’s student in Creative Media and recently started an AI learning path through IBM SkillsBuild, focusing on language models and computer vision.

The project I’m developing is basically this:

I want to use computer vision to analyze paintings and extract structured information such as:

• dominant colors
• shapes and composition
• presence of figures
• possible themes

Then, the idea is to use a language model to correlate these descriptions and find relationships between different artworks, kind of creating meaningful connections across pieces.

The goal is to build something useful for:

• museums
• galleries
• curators
• and anyone interested in exploring art collections in a smarter way

Where I’d love some input:

• Best approach to extract “theme” (feels very subjective)
• Whether it makes more sense to use pre-trained models like CLIP or train something more specific
• How to deal with cultural bias in artwork analysis
• If anyone has seen similar tools being used in real-world settings

If you work with computer vision, AI + art, or digital curation, I’d really appreciate your thoughts.

Any insight is welcome 🙏

I've been builidng for 5 months an AI agent that tracks and analyze health habits. Now I have one main agent taking care of 2 sheets tools, one for training and one for nutrition and planning to add psychologic tracking and sleeping. At some point I hope to build a score relating all that different category data about your body.