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In the presentation titled "Micro Talk: Your Face in 10 minutes... with MacRuby!" delivered by Haris Amin at GoRuCo 2012, the speaker explores how to build a face detection and recognition application using Ruby and MacRuby in a brief timeframe.

Key points discussed during the talk include:  
- **Introduction and Background**: Haris introduces himself and his involvement in various projects at Daily Burn, highlighting the use of his app that integrates face detection with social media.  
- **Project Overview**: He outlines the collaboration with an iOS developer where he focuses on the backend using Ruby, reflecting on his excitement for desktop applications, particularly using MacRuby.  
- **MacRuby Framework**: An explanation of MacRuby as an implementation of Ruby for creating macOS applications, including its initial development and compatibility with Ruby 1.9.  
- **Setting up the Application**: Haris discusses how to start with a main Ruby file (`main.rb`), including setup for AVFoundation framework to handle audio-video tasks necessary for face detection.  
- **Capture Session Initialization**: Steps to initialize the capture session and configure the device for video capture, outlining common pitfalls with API conventions (camel case methods).  
- **Face Detection Implementation**: Explanation of how to implement face detection using Core Image, detailing how face features are captured and processed in real time.  
- **Face Recognition Challenges**: Difficulties faced with Ruby’s limited libraries for efficient linear algebra operations for face recognition, and a reference to the use of Face.com API to integrate face recognition capabilities.  
- **Live Demonstration**: Haris performs a live demo of the application, showcasing the whimsical features he added for visual fun while noting the environmental challenges affecting detection accuracy.  
- **Conclusion**: He emphasizes the value of combining different programming languages and encourages developers to embrace a polyglot approach rather than getting confined to a single language.

Overall, the presentation serves as a quick guide to building a face detection and recognition app while promoting the use of Ruby within desktop application development, using Apple's APIs effectively.

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