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They use self-supervised learning algorithms to perform a variety of natural language processing (NLP) tasks in ways that are similar to how humans use language (see Figure 1). Large language models (LLMs) have taken the field of AI by storm.
Whats Next in AI TrackExplore the Cutting-Edge Stay ahead of the curve with insights into the future of AI. AI Engineering TrackBuild Scalable AISystems Learn how to bridge the gap between AI development and software engineering.
1 DataIngestion (e.g., Apache Kafka, Amazon Kinesis) 2 Data Preprocessing (e.g., The next section delves into these architectural patterns, exploring how they are leveraged in machine learning pipelines to streamline dataingestion, processing, model training, and deployment.
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Data Ingestion 
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