Mark Zuckerberg’s Jarvis: An Alexa That Learns Your Musical Tastes
Mark Zuckerberg’s ambitious 2016 personal project involved building a connected AI assistant, Jarvis, to automate various tasks at home. Jarvis, a blend of Python, PHP, and Objective C, utilizes machine learning techniques, including language processing, speech recognition, and facial recognition.
While Jarvis shares similarities with Amazon’s Echo, Zuckerberg went beyond simply using an existing service; he coded Jarvis from scratch. This project required him to integrate a variety of connected devices, including Sonos, Spotify, a Samsung TV, a Crestron smart home and lighting system, and a Nest cam.
One of Jarvis’s standout features is its ability to learn and adapt to the user’s musical tastes. By analyzing previously played music, Jarvis can select suitable tracks, even responding to requests like “play something light” to adjust the mood. The system also tracks the user’s partner’s preferences separately, allowing for personalized music experiences.
Zuckerberg also built a Facebook Messenger bot to interact with Jarvis via text, finding it preferable to voice commands, as he didn’t want to disturb others.
Zuckerberg learned from this project that while AI has made impressive strides in specific areas, it’s still a long way from general AI capability. He spent roughly 100 hours developing Jarvis, achieving a powerful system with potential for future home automation applications, even hinting at a potential Facebook product based on it.
