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.
Text-to-Speech (TTS) technology is an artificial intelligence application that enables written words to be converted into human voices.
Physical artificial intelligence is explained as artificial intelligence systems that can interact with physical objects found in the real world, perceive their environment, and give adaptive responses to this environment.
Especially in machine learning and natural language processing (NLP) projects, data is often represented as numerical vectors. At this point, traditional databases may be insufficient to manage vector-based data. This is where Vector Database (Vector DB) comes into play.
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