BlueData, provider of a big-data-as-a-service (BDaaS) software platform, has launched a new solution to accelerate deployment of artificial intelligence (AI), machine learning (ML), and deep learning (DL) applications in the enterprise. The BlueData AI/ML Accelerator solution includes software and professional services to deploy containerized multi-node sandbox environments for exploratory use cases with TensorFlow and other ML/DL tools.
According to BlueData, AI and ML/DL have moved into the mainstream with a broad range of data-driven enterprise applications such as credit card fraud detection, stock market prediction for financial trading, credit risk modeling for insurance, genomics and precision medicine, disease detection and diagnosis, natural language processing (NLP) for customer service, autonomous driving and connected car IoT use cases, and more.
One of the most popular ML/DL tools is TensorFlow, which is often used with technologies such as Python and GPUs to create an end-to-end pipeline from data preparation to modeling, scoring, and inference. However, the company notes, there are many other open source and commercial tools that may be used depending on the use case. Data scientists and developers want to evaluate and work with a variety of ML/DL tools, and they need rapid prototyping to compare different libraries and techniques. In most large organizations, they also need to comply with enterprise security, network, storage, user authentication, and access policies.
These users often start with a single-node environment but the technologies involved can be difficult to implement in multi-node distributed environments for large-scale enterprise use cases and many enterprises lack the skills to deploy and configure these tools with their existing data infrastructure and systems.
The potential value and impact of AI and ML is transformational, but it’s difficult to implement and configure these tools for large-scale distributed applications, said Kumar Sreekanti, co-founder and CEO of BlueData. The new solution provides data science teams with on-demand access to multi-node sandbox environments for exploring AI and ML use cases, without the operational overhead and deployment complexity, he added.
The BlueData AI/ML Accelerator provides a turnkey solution to enable rapid deployment of containerized multi-node sandbox environments for AI/MLDL use cases, using the BlueData EPIC software platform; and ready-to-run Docker images of popular ML/DL tools (including TensorFlow, SparkMLlib, H2O, Caffe2, Anaconda, and BigDL) for use in large-scale distributed computing environments.
The accelerator also enables the ability to spin up new ML/DL environments in a matter of minutes via self-service, with REST APIs or a few mouse clicks in a web UI; and secure integration with distributed file systems including HDFS, NFS, and S3 for storing data and ML/DL models; and automated and reproducible provisioning, enabling on-demand creation of identical ML/DL environments and reproducible results.
The new solution is designed for out-of-the-box deployments with open source technologies, including TensorFlow, SparkMLlib, H2O, Caffe2, Anaconda, and BigDL. However, the company says, it can be easily configured and extended for use with other ML/DL technologies—including both open source tools as well as commercial applications. And while initial implementations may focus on prototypes and pre-production environments, the BlueData solution is extensible to large-scale AI/ML/DL production deployments.
The BlueData AI/ML Accelerator includes a one-year subscription for BlueData EPIC software along with professional services, training, and support.
More information is available from www.bluedata.com.