This content originally appeared on DEV Community and was authored by Peace Thabiwa
The Problem
AI understands language but not emotional continuity.
You can train a model to detect “sad” or “happy,” but not how sadness moves into acceptance.
💥 The BINFLOW Solution
EmotionFlow encodes emotions as flow vectors through time.
Each feeling evolves across the six BINFLOW phases, forming a temporal fingerprint unique to each person.
⚙️ MVP Markup
from binflow import EmotionEncoder
emotion = EmotionEncoder()
emotion.record("sadness")
emotion.transition("acceptance")
emotion.output_flowmap()
🌍 Real-World Impact
We’re not predicting emotion — we’re tracing its motion.
Perfect for therapy AI, film scoring, and empathy-driven systems.
By Peace Thabiwa 🇧🇼 — SAGEWORKS_AI | The BINFLOW Initiative
This content originally appeared on DEV Community and was authored by Peace Thabiwa
Peace Thabiwa | Sciencx (2025-10-26T02:38:41+00:00) EmotionFlow: Encoding Feelings into Data. Retrieved from https://www.scien.cx/2025/10/26/emotionflow-encoding-feelings-into-data/
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