A recent press release states, “BlueData, provider of the leading Big-Data-as-a-Service (BDaaS) software platform, today announced 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 the software and professional services to deploy containerized multi-node sandbox environments for exploratory use cases with TensorFlow and other ML / DL tools. The promise of AI has been around for several decades, but it was only recently that AI started to become more widely adopted in the enterprise. Now AI is being explored and implemented for digital transformation initiatives in nearly every industry – leveraging innovative new open source tools and algorithms for ML / DL, the immense volumes of data available, and advances in high-performance data processing infrastructure.”

The release continues, “In fact, AI and ML / DL have moved into the mainstream with a broad range of data-driven enterprise applications: 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, often used together with technologies like Python and GPUs to create an end-to-end pipeline from data preparation to modeling, scoring, and inference. However, 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.”

Read more at BlueData.

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