In March, Facebook announced the ability to recognize different types of actions in videos. This is one of many recent examples of powerful and interesting innovations in the area of Artificial Intelligence.
Being able to draw context out of text, images and rich media types will allow Facebook to be more effective in content curation. In other words, animal lovers may start seeing a lot more videos of kittens playing pianos in their feeds. This technology should help Facebook better target their audience, suggest friends and sell more ads.
But the possibilities go far beyond kitten videos.
In addition to delivering more personalized content, AI can lengthen our lives, make our businesses more efficient, and protect our citizens.
We can already see the huge impact of predictive analytics in metropolitan services. For example, the City of Chicago relies on their WindyGrid service to collect and make sense of the millions of pieces of information gathered daily from Chicago’s 15 most crucial departments, including police, transportation, and fire. It’s an ever-changing view of what makes the city tick. Roadwork updates, trash pickup delays, 911 health emergencies, 311 complaints about noise, public tweets about the minutia of the city’s workings, bus locations along their route, traffic light patterns, and much more. WindyGrid analyzes trends across multiple data sources to make predictions about what will happen next.
Now imagine what the City of Chicago could do with AI technology similar to Facebook’s. We move beyond understanding trends to being able to develop solutions that automatically understand and respond to specific events as they’re happening in real-time.
Chicago health officials could know if an elderly citizen is experiencing a health emergency when they are no longer able to call for help. Emergency responders could be notified when an infant is in need health attention before he first cries out. Firemen could be deployed when the first ash ignites, and an intelligent system could recognize the severity of the fire to recommend an appropriate response. Video surveillance could recognize a burglary as it is happening and send alerts to the property authorities. The possibilities are endless.
Building a practical system of this kind hasn’t been easy. Natural language processing, machine learning and reasoning require the processing of high volume, variant data which had overwhelmed traditional data stores. New technologies and new databases allow for associations, patterns, and vectors to be recognized. MongoDB has made the real-world deployment of massive, integrated machine learning systems a practical reality.
But kittens playing pianos are important too.
If you're interested in learning more about how the City of Chicago leveraged real-time analytics for their WindyGrid service, read the customer case study, or come to MongoDB World this June and hear for yourself!