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🍯 Neural Nectar

Neural Nectar is a series of soft, shareable machine learning experiments made with ml5.js and p5.js. Designed to be poetic, playful, and emotionally expressive, these mini-web experiences explore what it means to interact with gentle intelligence.

Created as part of ongoing research into poetic computing, aesthetic ML, and cute interfaces.


✨ About

Neural Nectar is a “microbrewery” of experiments that make machine learning feel personal and alive. Each sketch is approachable, aesthetically focused, and designed for curiosity, not productivity. From mood-reactive mirrors to gesture-driven visuals, the series invites you to explore machine learning through feelings, play, and presence.


🍬 Experiments

Project Description
🪞 Mood Mirror Analyzes your words and reflects your emotional aura with shimmering color and emoji.
🍑 Nectar Barometer Mic input fills a jar of digital nectar — a mood barometer for your space.
🌸 Pose Petals Your hand (or nose, eyes, elbows etc.) movements bloom into glowing flower trails.
🪼 Blob Light Show testing/in progress Touch a squishy agar blob to spark light — a soft interface for glowing interaction.
🔮 (More coming soon...) Stay tuned for future experiments that bring neural sweetness to your screen.

🛠️ Built With


🌐 How to Run Locally

  1. Clone this repo:

    git clone https://github.com/your-username/neural-nectar.git
    cd neural-nectar
    
  2. Open any project folder inside the neural-nectar/ directory.

  3. Launch a local server (choose one of the following methods):

    Using Python:

    python -m http.server

Or use the "Live Server" extension in VS Code.

  1. Open your browser and go to:

    http://localhost:8000
    

🌸 Aesthetic Philosophy

Neural Nectar embraces softness, slowness, and emotional interaction in computing. It's about gentle intelligence, not artificial dominance. Every sketch is an offering — a quiet ritual between human and machine.


⭐️ Inspiration

  • Poetic Computation – influenced by Taeyoon Choi and the School for Poetic Computation
  • Cute Interfaces – inspired by Tamagotchi, Polly Pocket, and retro-futuristic design
  • Accessible ML – using ml5.js to democratize experimentation and joy

Thanks to the ml5.js community and open-source contributors everywhere 💖

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a series of soft, fun and small machine learning experiments made with ml5.js and p5.js.

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