Case Study: Carnegie Mellon University advances socially aware AI research with Google for Education Google Cloud Machine Learning

Carnegie Mellon University powers socially aware AI with Google for Education in a 4-day conference trial

Carnegie Mellon University's Articulab team faced the challenge of developing robotic assistants that could truly collaborate with humans by building relationships and understanding social cues, rather than just performing tasks impersonally. To study these interactions and train their agents with social awareness, they turned to Google for Education and utilized Google Cloud's Machine Learning Engine.

Using Google Cloud's tools, including Compute Engine with GPU instances and TensorFlow, the Articulab built SARA, a socially aware robot assistant. The solution successfully processed data from over 250 interactions at the World Economic Forum, with a key finding that high rapport directly correlated to improved task performance and recommendation acceptance. Google for Education enabled the team to accelerate their AI research and expand these socially intelligent applications into new domains like education.

Carnegie Mellon University