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AI Compute

The computing ability required for machines to learn from big data to experience, adjust to new inputs, and perform human-like tasks. Komprise cuts the data preparation time for AI projects by creating virtual data lakes with its Deep Analytics feature.

AI compute refers to the computational resources required for artificial intelligence systems to perform tasks, such as processing data, training machine learning models, and making predictions. These resources can be provided by various hardware and software platforms, including GPUs, TPUs, cloud computing, and edge computing devices. The amount of AI compute needed depends on the complexity of the AI system and the amount of data being processed. Hosting AI compute infrastructure internally can be prohibitively expensive, making the prospect of cloud-based AI more attractive for many organizations.

Unstructured data management solutions and unstructured data workflows are increasingly being used to improve storage efficiencies and speed time to value for AI.

What is unstructured data in AI?

AI needs unstructured data – are you ready?

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AI needs unstructured data

Read the Duquesne University case study to learn more about Komprise Smart Data Workflows and AWS Rekognition for rapid image search across petabytes of data.

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