Meta AI Blog - 10 Years of FAIR

Ten years of FAIR: Advancing the state-of-the-art through open research 
 
 
 
 
 
 
 
 
 
 
 
 

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 FEATURED Research Celebrating 10 years of FAIR: A decade of advancing the state-of-the-art through open research 

 November 30, 2023 Today we’re celebrating the 10-year anniversary of Meta’s Fundamental AI Research (FAIR) team—a decade of advancing the state of the art in AI through open research. During the past 10 years, the field of AI has undergone a profound transformation, and through it all, FAIR has been a source of many AI research breakthroughs, as well as a beacon for doing research in an open and responsible way.

 It’s FAIR’s dedication to responsibility, openness, and excellence that first drew me here six years ago. Like many others, I was won over by the promise of working with the best researchers in the world amid a culture of respect and integrity and with an ambition to do AI research that would transform the world for the better. I never looked back. Of course, I wasn’t the first one here—quite a few minds at Meta preceded me.

 The past decade

 The launch of FAIR dates back to late 2013. In those days, as today, the competition for AI talent was fierce. And Mark Zuckerberg himself made the trip to the NeurIPS conference to convince researchers to join this new research organization. Partnering with VP and Chief AI Scientist Yann LeCun, they assembled a team of some of the most talented researchers in the nascent field of deep learning. Over the years, hundreds of brilliant minds, conducting bleeding-edge research with far reaching impact, have joined the effort and enabled us to make progress on many of the hardest problems in AI.

 It’s fascinating to see what a decade of progress looks like. Consider, for example, what’s happened in the world of object detection. It was only a little over 10 years ago that neural networks were able to recognize thousands of objects in images for the first time with AlexNet. Faster R-CNN brought us real-time object detection in 2015, followed by object instance segmentation with Mask R-CNN in 2017 and a unified architecture for instance and semantic segmentation with Panoptic Feature Pyramid Networks (FPN) in 2019. In the span of just seven years, FAIR contributed to tremendous progress on one of the most fundamental problems in AI. And in 2023, we can literally Segment Anything . Each of these moments directly resulted in a step change across several downstream applications and products created by our colleagues at Meta, as well as people around the world.

 We have seen similar trajectories across many other problems in AI. Another great example is the last five years of our work on machine translation, where we were among the first to pioneer techniques for unsupervised machine translation , which allowed us to introduce a model for translation across 100 languages without relying on English. This led directly to ou

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