UPDATED 17:48 EDT / MARCH 11 2015

Scalable machine learning for smarter Big Data predictions | #BigDataSV

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Machine learning helps enterprises use all of their data for better real-time predictions, improved decision-making processes and analyzing patterns. SriSatish Ambati, the CEO of H2O.ai (formerly 0xdata, Inc.) stopped by theCUBE during SiliconANGLE’s BigDataSV meet up with co-hosts John Furrier and Jeff Kelly to discuss how machine learning enables users to get more value from their existing data and easily create smarter business models.

The machine learning product of H2O is an open source, parallel processing system that is developed for high performance and scalability. With this system H2O hopes to woo data scientists and businesses with a powerful yet easy to use data analysis platform.

According to Ambati, machine learning is the new SQL. In the past, SQL defined data in the form of databases, but machine learning is driving better data-driven predictions. He mentioned scenarios such as fraud prevention, pattern recognition and faster predictive analytics as all part of the machine learning tool set.

“People have built static internet, they have built data driven internet, and they now want to build smarter internet using the machine learning,” Ambati said. “Now we have a three way mix between data, Internet of Things and intelligence,” he continued.

 

Big Data in business: Operations and beyond

 

When asked about Big Data’s role in operational efficiency, Ambati said it’s now more important than ever. Systems are collecting lots of data and often these traditional dashboards are seen as the steering factors for the organization, as strategic decisions are made on the basis of the information provided.

He then added deep learning is another big trend for businesses. H2O has worked on sophisticated machine learning algorithms and not just simple algorithms to run logistic regression, boosting machine that helps companies predict data with ease, speed and more accuracy.

With the scoring engine that H2O developed, Ambati said apps are built that can now dynamically change based on incoming data. “The scoring engine is nano second fast and with this you can do hundreds of predictive models.”

Commenting on how H2O is helping developers, Ambati said his company is working to add more algorithms. It is now offering H2O as a real-time machine learning service that can be used on a smartphone app or web app that learn continually as it receives more data. Thus giving developers access to smarter predictive insights for said data.

Watch the full interview below, and be sure to check out even more of SiliconANGLE and theCUBE’s full coverage of BigDataSV.


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