- H2O.ai announced the availability of its full suite of AI platforms in the Microsoft Azure Marketplace. Microsoft Azure customers will now have access to all the open source artificial intelligence (AI) vendor’s AI products including the automatic machine learning program H2O Sparkling Water, and H2O Driverless AI.
Healthcare organizations using Microsoft Azure deployments can now take advantage of AI without changing their cloud environment.
Sparkling Water is an open source machine learning solution that works with Spark 2.0, sparklyr, and PySpark. The solution allows users to combine the fast, scalable machine learning algorithms with the capabilities of Spark.
Sparkling Water provides a machine learning platform for developers so users can drive computation from Scala/R/Python and utilize the H2O Flow UI.
H2O Driverless AI provides a platform for data scientists to work on projects faster using automation powered by graphics processing units (GPUs). The computing power GPUs offer can significantly reduce the time it takes to complete high level computing projects by weeks or even months.
ArmadaHealth uses H2O on Microsoft Azure to help their patients find the right physician quickly.
“At ArmadaHealth, we understand that searching for the right doctor or specialist can be daunting. Our goal is to ensure we bring the best data science, analytics and clinical intelligence to provide precise navigational assistance for patients seeking care,” said Bharath Sudharsan, director of Data Science and Innovation at ArmadaHealth. “H2O Driverless AI and Microsoft Azure really give us the edge in terms of feature engineering – the core of any machine learning project.”
Last year, H2O first introduced its platform to Microsoft Azure making Sparkling Water available on a HDInsight cluster along with other Azure services.
H2O.ai’s solution now operates with Azure HDInsight, which is a fully managed cloud Hadoop offering that optimizes open source analytical clusters for Spark Hive, MapReduce, HBase, Storm, Kafka, and R Server.
Microsoft Azure isn’t the first major vendor H2O has partnered with over the past few years. Last May, H2O partnered with IBM to offer its their AI platform, GPU-powered machine learning, and deep learning on IBM’s Power Systems Platform.
H2O’s GPU optimized machine learning and deep learning AI software takes advantage of IBM’s POWER architecture to offer organizations a fully supported AI solution. IBM customers can also run H2O algorithms through the IBM Data Science Experience platform to manage and collaborate on data science projects.
“H2O’s interpretable algorithms democratize the monetization of data with AI. IBM Power Systems provides a resilient and highly available computing platform for H2O.AI customers,” H2O.ai CEO and Co-Founder Sri Ambati said in a statement. “We are excited to partner with the IBM team to amplify the transformation of the enterprise with AI.”
GPU adoption is expanding in healthcare data analytics because machine learning workloads are outgrowing traditional CPUs. The GOAI formed to migrate workloads to GPUs and to establish a common standard so organizations can benefit from the power of end-to-end GPU computing.
A common GPU standard will enable intercommunication between data applications and enhance workflow by removing latency. It will also decrease the complexity of data flows between core analytical applications.
451 Research Senior Analyst of Data Platforms and Analytics Jim Curtis recently commented on GPUs in relation to an advanced database analytics collaboration between Fuzzy Logix and Kinetica.
“Leveraging GPUs for analytical workloads is on the rise, particularly among financial services, healthcare and retail organizations that often deal in extremely large data volumes with high scaling and real-time processing requirements,” said Curtis.
The new tool will extend Kinetica’s in-database analytic capabilities by hundreds of additional GPU accelerated machine learning and predictive analytics algorithms from Fuzzy Logix. The analytic functions will be able to utilize Kinetica’s distributed GPU pipeline through its User Defined Functions (UDFs).
IBM, Microsoft and other major vendors predict that AI will be behind a majority of enterprise decisions within the next 5 years. This prediction is why many major vendors are seeking out AI companies to partner with. Introducing open source AI platforms and the computing power to support AI platforms will help organizations already using IBM or Microsoft Azure to integrate AI into their IT infrastructure much more quickly.