Presentation: Machine Intelligence at Google Scale

Track: The Practice & Frontiers of AI

Location: Mountbatten, 6th flr.

Duration: 2:55pm - 3:45pm

Day of week: Tuesday

Level: Advanced

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The biggest challenge of Deep Learning technology is the scalability. As long as using single GPU server, you have to wait for hours or days to get the result of your work. This doesn't scale for production service, so you need distributed training on the cloud eventually, or take advantage of pre-trained models. Google has been building infrastructure for training the large scale neural network on the cloud for years, and started to share the technology with external developers. In this session, we present pre-trained ML services such as Cloud Vision API and Speech API that works without any training. In addition, we introduce Cloud AutoML, which helps customizing our pre-trained models with your data. Also, we look at how TensorFlow and Cloud Machine Learning can accelerate custom model training with Google's distributed training infrastructure.

Speaker: Guillaume Laforge

Developer Advocate at Google Cloud and PMC Chair for Apache Groovy

Guillaume Laforge is Developer Advocate for Google Cloud Platform, during the day, often talking about serverless technologies, conversational interfaces, or machine learning APIs. And at night, he wears his Apache Groovy cap, a popular alternative language for the Java Virtual Machine.

Find Guillaume Laforge at

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