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Oracle Artificial Intelligence Blog

H2O.ai Driverless AI Cruises on Oracle Cloud Infrastructure GPUs

Ben Lackey
Director, Data and AI Partnerships
This is a syndicated post, view the original post here

One of the things I'm most excited about at Oracle Cloud Infrastructure is the opportunity to do cool things with our partners in the artificial intelligence (AI)/machine learning (ML) ecosystem. H2O.ai is doing some really innovative things in the ML space that can help power these sorts of use cases and more. Their open source ML libraries have become the de facto standard in the industry, providing a simple way to run a variety of ML methods, from logistic regressions and GBT to an AutoML capability that tunes the model automatically.

H2O.ai has continued to build on this functionality with GPU support with what I think might be the best-named product of all time, Sparkling Water. (Yes, it's H2O running on Spark. Get it?). The latest H2O.ai product is Driverless AI. The name is perhaps a bit misleading. Driverless AI isn't related to driverless cars. Instead, it's an ML platform that provides a GUI on top of the H2O ML libraries that we already know. The GUI provides support for a significant chunk of the ML lifecycle:

  • Data loading
  • Visualization
  • Feature engineering
  • Model creation
  • Model evaluation
  • Deployment for scoring

Software to do all this simply wasn't available five years ago. Instead, a highly skilled person would have had to put everything together by hand over a period of weeks or months. There are still some gaps. For example, data wrangling is still a mess even with the time series support and automatic feature generation abilities of Driverless AI. That said, building accurate ML models has never been easier.

So, what does this all have to do with Oracle Cloud Infrastructure?

We're building data centers all over the world, and they're being populated with some nifty hardware, including cutting-edge GPU boxes. The new BM.GPU3.8 is the top of that range with 8 NVIDIA Volta cards. This is the perfect machine to handle the compute demands of DAI, and we're pricing them to be significantly less expensive than any competing platform.

terraform apply

For our provisioning plane, Oracle Cloud Infrastructure has made an open choice. Rather than building a proprietary technology such as Amazon Web Services CloudFormation, we've chosen to adopt the open source industry standard of Terraform. We've joined the Cloud Native Computing Foundation (CNCF) as a Platinum member and contributed our Terraform provider to the open source project.

We've partnered with H2O.ai to write some Terraform modules that deploy H2O.ai Driverless AI on Oracle Cloud Infrastructure. The first module deploys on GPU machines. I worked with our team to record this video that demonstrates how to use the module. It also includes a very basic demo.


 

This is just the beginning of our partnership with H2O.ai. We're working on several activities with them:

  • Oguz Pastirmaci from the Oracle Cloud Infrastructure data and AI team is working to enhance the Terraform module. Building a model is fast with 8 GPUs. It's going to be a lot faster with a whole cluster of those machines humming in parallel.
  • We're discussing how we might be able to simplify deployment even further, providing a more integrated experience with a higher-level interface.
  • We'll be at H2O World San Francisco 2019 on Feb. 4-5. Although the event won't have booths, a number of us should be wandering around the conference. Say hi!

If you're interested in learning more about H2O.ai on Oracle Cloud Infrastructure or about our AI/ML partnerships in general, reach out to me at ben.lackey@oracle.com. You can also follow me on Twitter @benofben.

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