After completing his doctorate, Corrado joined
IBM's
T. J. Watson Research Center, where he focused on
neuromorphic computing and large-scale
neural network simulations. A major early achievement came in 2012 when the team built a
neural network using 16,000 processors that learned to autonomously identify cats from unlabeled
YouTube video stills. At Google, Corrado has been instrumental in integrating AI into consumer products. He helped lead the development of
RankBrain, a machine learning system launched in 2015 to improve
Google Search results, which Corrado identified as the third most important ranking signal. He also guided the creation of Smart Reply, which uses neural networks to generate automated email responses in
Gmail. Corrado was also involved in the development and open-sourcing of key Google technologies, including the
TensorFlow machine learning framework and
word2vec, an influential algorithm for creating
word embeddings. In the late 2010s, Corrado shifted his focus to the application of artificial intelligence in
medicine, eventually becoming Head of Health AI at Google Research in 2016. In this role, he led research into using AI for
medical diagnostics, particularly in
medical imaging, predicting clinical outcomes, and analyzing
genomic and sensor data. Under his leadership, the Health AI team developed several notable projects. These include the
Automated Retinal Disease Assessment (ARDA), a tool designed for detecting diabetic retinopathy, and the Med-PaLM series of medical
large language models. while its successor, Med-PaLM 2, achieved 86.5% accuracy on the MedQA benchmark. Another multimodal model, Med-Gemini, reached 91.1% accuracy on the same benchmark. ==Selected publications==