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Agentic AI allows multiple role agents work together to achieve specific tasks.
Workflows are automated with human in loop to ensure the task performance and security level.
LSTM (Long Short Term Memory) model captures both short and long term patterns, which is outperforming models for time series forecast.
With MLflow to monitor the model performance, it guarantees sustainable performance result.
Adding new fuel to LLM to formulate your desired response.
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Building an information retrieval system gives you better control over LLM to formulates a proper response.
RAG architecture allows you to constrain LLM to specific domain data sourced from vectorized documents and images, and videos using embedding models.
Small language models (SLMs) such as Phi3, Llama are capable of processing, understanding and generating natural language content like LLMs, but in smaller scale and scope.
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SLMs are compact, efficient and affordable as they require less memory and computational power.
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It is perfect for resource-constrained environments such as AI inference model generation.
