Data gravity occurs when the volume of data in a warehouse increases and the number of uses also increases. In some cases, copying or moving data can be troublesome and expensive. Therefore, data tends to pull services, applications and other data into its warehouse. Primary examples of data gravity are data warehouses and data lakes. Data in these systems is inert. Scalable volumes of data often break existing infrastructure and processes, requiring risky and expensive fixes. Therefore, the best practice is to move design processing to data, not the other way around.
Multimodal AI (Multimode Artificial Intelligence) is a field of artificial intelligence technology that seeks to emulate this human experience.
Cloud-Native Data Platforms are data management platforms designed and optimized to work directly in cloud environments. These platforms take full advantage of the flexibility, scalability, and cost advantages of the cloud unlike traditional data infrastructures.
Pre-training refers to pre-training a model on large data sets and then fine-tuning it to perform a specific task. This technique is widely used, especially in areas such as natural language processing (NLP) and image processing.
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