One of our most significant innovations is the adoption of the Mixture of Experts (MoE) architecture. Traditionally, neural models use a single network to process all types of data. However, MoE breaks away from this pattern by adopting a modular and specialized approach.
This system comprises a series of “experts,” each designed to handle specific types of data or tasks. An access network supervises and directs input data to the most qualified expert. This not only significantly enhances the accuracy and quality of responses but also optimizes processing times and computational resource usage.
One of our most significant innovations is the adoption of the Mixture of Experts (MoE) architecture. Traditionally, neural models use a single network to process all types of data. However, MoE breaks away from this pattern by adopting a modular and specialized approach.
This system comprises a series of “experts,” each designed to handle specific types of data or tasks. An access network supervises and directs input data to the most qualified expert. This not only significantly enhances the accuracy and quality of responses but also optimizes processing times and computational resource usage.
The sophisticated RAG techniques employed by MAIA facilitate a refined process of optimizing outputs by leveraging external data sources. This approach enables the Ufind application, for instance, to access information sources using tools known as ‘bricks’, sophisticated data collection instruments that delve into the depths of the web, as well as other customized sources like private databases or simple private files.
Furthermore, this technique harnesses a valuable neural network, neural ID, to gather and correlate all user preferences and behaviors.
The sophisticated RAG techniques employed by MAIA facilitate a refined process of optimizing outputs by leveraging external data sources. This approach enables the Ufind application, for instance, to access information sources using tools known as ‘bricks’, sophisticated data collection instruments that delve into the depths of the web, as well as other customized sources like private databases or simple private files.
Furthermore, this technique harnesses a valuable neural network, neural ID, to gather and correlate all user preferences and behaviors.
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