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As with all 4 of our focus areas, data is fundamental to Applied AI, enabling key insights through the application of advanced machine learning algorithms in areas such as data mining, data integration, graph analytics, data science, and data management.

With the rapid increase in artificial intelligence technologies in many science and engineering domains such as computer vision, language understanding, and recommender systems, HPC applications are beginning to adopt AI for a variety of scientific problems including weather & climate studies, high-energy physics, bioinformatics, and computational chemistry.

From sensors and IoT devices to edge processing and cloud management and storage, disparate systems (including both hardware and software) must interoperate seamlessly to solve highly complex tasks within tolerable limits like latency, bandwidth and power while delivering rich experiences for users.

Heterogeneous computing hardware will play an important role in next-gen mission critical systems. Combining Data, SciML and Software together, hardware needs to evolve to support fast changing demands in industry, including areas such as hardware acceleration, 5G platforms, reconfigurable computing and SoC.