Dell Products Inc.

Dell & Products L.p.

Xin Ma

George Currie

Jeffery White

Said Tabet

William Jeffery White

Embodiments of systems and methods for unsupervised data characterization utilizing drift are described. In some embodiments, an Information Handling System (IHS) may include a processor and a memory coupled to the processor, the memory having program instructions stored thereon that, upon execution, cause the IHS to: provide input data to an Artificial Intelligence (AI) or Machine Learning (ML) drift detector, where the AI/ML drift detector is associated with a characteristic undetectable in the input data; and receive a drift confidence score from the AI/ML drift detector.

Unsupervised data characterization utilizing drift

The disclosure describes an enhanced distributed retrieval augmented generation (RAG) system. The enhanced distributed RAG system provides RAG data to a local small foundation system to form prompts. The enhanced distributed RAG system creates local query optimized representations (QORs) that are matched with queries sent to the local small foundation system to create prompts. The enhanced distributed RAG system is located on one edge site and is connected to the global federated RAG module. The global federated RAG system is connected to other enhanced distributed RAG systems in other edge sites. QORs can be distributed across the enhanced distributed RAG systems and the global federated RAG module by promoting local QORs to global QORs and vice versa.

Enhanced distributed retrieval augmented generation system

Embodiments of systems and methods for enhanced drift remediation with causal methods and online model modification are described. In some embodiments, an Information Handling System (IHS) may include a processor and a memory coupled to the processor, the memory having program instructions stored thereon that, upon execution, cause the IHS to: detect drift in an Artificial Intelligence (AI) or Machine Learning (ML) model configured to make a prediction or a causal reasoning graphical or structural inference based upon input data, identify a root cause of the drift, and tag the input data with an indication of the root cause.

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Pflugerville, TX, United States of America

Xin Ma