See where AI fits into making a visual novel and a protein-research workflow, and what each project delivers.
Using AI to build a project does not mean the finished product runs AI. The visual-novel creator describes help with art and writing; Extremolith has an event description and a public repository. Neither case alone tells us how well the finished work performs.
2 featured examples · 61 related projects
Compare the inputs and outputs
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Based on the sources below, not a ranking of results.
Use Claude to help build a data and model workflow for protein research.
How it works
Combine GTDB protein and environmental data with GenomeSPOT predictions.
Filter secreted proteins and split the training data.
Process the data using the repository commands; the event description also covers training and generation.
What you get
Environment-labeled data tables, protein sequence files and a page showing a fixed, precomputed laccase result.
The page does not perform live inference from user input. We did not run the code, train a model or carry out biological experiments, so this is not a performance test.
Training Data Microgames is a timed minigame collection with a parody premise about AI collecting training data. The submission describes successive tasks such as clicking, drawing, arithmetic, spelling, swiping and skipping ads under a countdown.