Tensorflow Conducts Developer’s Meetup at Wavelabs
Discusses the upcoming technologies and the problems the developers, AI engineers and researchers are seeking to solve, and the challenges they are facing in solving them
Mike Liang, Product Manager at Google, Tensorflow, met the city’s developers, AI engineers and researchers to discuss the types of opportunities, and problems the developers are excited about and want to solve. He also dwelled into the challenges they might face while trying to solve them.
Mike shared a bunch of use cases addressing real world problems which Google is trying to solve, such as protecting rainforests in Amazon, helping farmers in Africa, predicting floods in India and more.
Released first in November 2015, this open standard software has matured to be a comprehensive Machine Learning toolkit rather than a framework. Many companies across the world are using Tensorflow to power their ML platforms and solutions. Mike discussed all the new features that TensorFlow is looking to add, and the design that went into building them. He discussed various training and deployment architectures available with TensorFlow. He postulated industry thumb rules in building training workflows and the support Tensorflow provides for various physical devices like servers, edge devices and JavaScript based devices.
He also demonstrated how Tensorflow enables developers and data scientists to do cutting edge research using cloud AutoML. And provided insights into the new Tensorflow 2.0 alpha and its key features. He gave a comprehensive view into various Tensorflow based frameworks like TF lite, TF Ranking, TFX(Extended), TF Federated, TF.JS etc. and their industry reach, and how they are easy, powerful and scalable. Mike demonstrated how the simplified APIs focus on Keras and its eager execution. They are powerful enough to handle cutting-edge research and can be deployed anywhere.
Mike talked at length about Tensorflow’s ongoing collaboration with Wavelabs. And spend time with the advanced engineers and researchers, talking about how best Tensorflow and other tools and resources can be leveraged to build innovative solutions to real-world problems.