Tensorflow(@CVision)

خانه ی #هوشمند مارک #زاکربرگ بنیان گذار فیس بوک که از متدهای نوین هوش مصنوعی نظیر بازشناسی شئ، بازشناسی چهره، بازشناسی گفتار، پردازش زبان‌های طبیعی و ... بهره برده است.
زاکربرگ از انگیزه ی خود برای این کار و گام های انجام کارش می‌نویسد:

https://www.facebook.com/notes/mark-zuckerberg/building-jarvis/10154361492931634/

چالش شخصی من برای سال 2016 ساخت یک هوش مصنوعی ساده برای خانه ام بوده - مثل جارویس در فیلم مرد آهنین...

Building Jarvis:
- Getting Started: Connecting the Home
- #Natural_Language
- #Vision and #Face_Recognition
- Messenger Bot
- Voice and #Speech_Recognition
- Facebook Engineering Environment

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Vision and Face Recognition:
About one-third of the human #brain is dedicated to vision, and there are many important #AI problems related to understanding what is happening in images and videos. These problems include #tracking (eg is Max awake and moving around in her crib?), #object_recognition (eg is that Beast or a rug in that room?), and face recognition (eg who is at the door?).
Face recognition is a particularly difficult version of object recognition because most people look relatively similar compared to telling apart two random objects — for example, a sandwich and a house. But Facebook has gotten very good at face recognition for identifying when your friends are in your photos. That expertise is also useful when your friends are at your door and your AI needs to determine whether to let them in.
To do this, I installed a few cameras at my door that can capture images from all angles. AI systems today cannot identify people from the back of their heads, so having a few angles ensures we see the person's face. I built a simple server that continuously watches the cameras and runs a two step process: first, it runs face detection to see if any person has come into view, and second, if it finds a face, then it runs face recognition to identify who the person is. Once it identifies the person, it checks a list to confirm I'm expecting that person, and if I am then it will let them in and tell me they're here.
This type of visual AI system is useful for a number of things, including knowing when Max is awake so it can start playing music or a Mandarin lesson, or solving the context problem of knowing which room in the house we're in so the AI can correctly respond to context-free requests like "turn the lights on" without providing a location. Like most aspects of this AI, vision is most useful when it informs a broader model of the world, connected with other abilities like knowing who your friends are and how to open the door when they're here. The more context the system has, the smarter is gets overall.

#mark_zuckerberg #smart_home

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