Three Models, Zero API Calls: Real-Time Meeting Intelligence on Apple Silicon
📰 Dev.to AI
Learn how to run real-time meeting intelligence on Apple Silicon with zero API calls using three models
Action Steps
- Build a sentence-embedding model for topic segmentation
- Configure the Neural Engine for on-device processing
- Test the Live Topic Timeline feature for real-time meeting analysis
- Integrate the CoreML model with the meeting intelligence tool
- Optimize the model for low-latency processing on Apple Silicon
Who Needs to Know This
This benefits developers and product managers working on AI-powered meeting intelligence tools, as it showcases a novel approach to on-device processing
Key Insight
💡 On-device processing with the Neural Engine enables real-time meeting analysis without relying on API calls
Share This
🚀 Run meeting intelligence entirely on-device with zero API calls! 🤖
Key Takeaways
Learn how to run real-time meeting intelligence on Apple Silicon with zero API calls using three models
Full Article
Originally published at thunderkitty.app/learn Thunder Kitty's Labs features run topic segmentation and agenda tracking live, entirely on-device — and getting a sentence-embedding model onto the Neural Engine took seven attempts and a fight with a silent CoreML bug. Thunder Kitty 1.9.0 adds a Labs section in Settings with two experimental features: a Live Topic Timeline that segments a meeting into topics as you record, and Live
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