In a recent blog post, Google announced TensorFlow Enterprise, a cloud-based TensorFlow machine learning service that includes enterprise-grade support and managed services.
TensorFlow is an open-source artificial intelligence framework for machine learning, deep learning and other statistical and predictive analytics workloads. Google has now launched an enterprise version as a beta with a strong leaning towards providing enterprise-grade support. Craig Wiley, director product management, Cloud AI Platform, stated in the blog post:
The pace of AI and software versions is evolving rapidly, but many customers have told us they are heavily invested in a previous version of TensorFlow. That is why TensorFlow Enterprise includes long-term version support. For certain versions of TensorFlow, we will provide security patches and select bug fixes for up to three years. These versions will be supported on Google Cloud, and all patches and bug fixes will be available in the mainline TensorFlow code repository.
In addition to the statement of Wiley, Holger Mueller, principal analyst and vice president at Constellation Research Inc., told InfoQ:
Enterprises want platform stability for their AI solutions to reap scalable business benefits. With the extended support of three years, Google caters to that requirement - further cementing the lead of Tensorflow across AI platforms.
The public cloud provider positions TensorFlow Enterprise as a service to help data scientists with a way to accelerate the creation of machine learning and deep learning models on their cloud. Furthermore, these models can be tested and run at scale in the Google Cloud as TensorFlow Enterprise includes Deep Learning VMs (GA) and Deep Learning Containers (Beta). Both products are compatibility-tested and performance optimized for Google’s wide range of NVIDIA GPUs and custom-designed AI processor, the Cloud TPU.
Jeff Collins, VP engineering - monetization, unity technologies, said in the announcement blog:
Through the power of Google Cloud’s TensorFlow Enterprise, we can quickly test, build and scale our Machine Learning models at massive scale, allowing us to serve up the most relevant ads and drive revenue for game developers.
Besides scalability, TensorFlow Enterprise also offers customers access to a range of Google Cloud’s managed services, such as Google Kubernetes Engine (GKE) and the Google AI Platform. Moreover, as Wiley states in the blog post:
Whatever stage of development you’re in, from development to deployment, Google Cloud offers an end-to-end workflow on TensorFlow.
TensorFlow enterprise is now available for customers to use. They can try out the service through a code lab, or leverage the how-to-guides, and more details about the service itself are available on the documentation website.
Lastly, Google has an additional offering of TensorFlow Enterprise with the so-called white-glove service, which includes engineer-to-engineer support, and the promise that TensorFlow Enterprise ties into other Google Cloud managed services such as the AI Platform and Kubernetes Engine. Other than the white-glove service, the TensorFlow Enterprise comes at no cost.
