AI Analyzed My Bookshelf to Give Me Personalized Recommendations
I took a video of my bookshelf and got AI to create a list of custom book recommendations for me.
This was a multi-stage project, but I’m really happy with the results. I’ll cover how I got there in detail, but here’s the cliff’s notes:
- Have Google Gemini identify the books on the shelf using the video
- Have Gemini clean the data that it just created
- Ask Gemini to give me recommendations based off the cleaned data
1. Identifying books
I passed Google Gemini the video of my bookshelf and tasked it to identify the books and output it in a machine-friendly format(JSON)
It did way better than I expected.
2. Cleaning the data
I then fed it back into Gemini to clean the data a bit.
Mostly, it removed duplicates and titles that wouldn’t make much sense. In this specific run, this step was a bit superfluous, but it depends a lot on how bad the identification went.
3. Getting the results
Lastly, I fed the cleaned data back into Gemini and had it give me good recommendations based on what it saw.
It did a good job! A lot of these I have already read and just don’t have on my shelf, including more obscure ones like The Goblin Emperor, so it did a good job of figuring out my taste.
I want to hook this up to some sort of semantic index or something so that it can get descriptions for the books themselves, but that will have to come in a future version. Follow me on Twitter and LinkedIn for more demos like this!
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