Remove Data Drift Remove Data Quality Remove LLM
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RAG vs Fine-Tuning for Enterprise LLMs

Towards AI

legal document review) It excels in tasks that require specialised terminologies or brand-specific responses but needs a lot of computational resources and may become obsolete with new data. For instance, a medical LLM fine-tuned on clinical notes can make more accurate recommendations because it understands niche medical terminology.

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The Sequence Pulse: The Architecture Powering Data Drift Detection at Uber

TheSequence

Created Using Midjourney In case you missed yesterday’s newsletter due to July the 4th holiday, we discussed the universe of in-context retrieval augmented LLMs or techniques that allow to expand the LLM knowledge without altering its core architecutre. Like any large tech company, data is the backbone of the Uber platform.

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MLOps Landscape in 2023: Top Tools and Platforms

The MLOps Blog

Data quality control: Robust dataset labeling and annotation tools incorporate quality control mechanisms such as inter-annotator agreement analysis, review workflows, and data validation checks to ensure the accuracy and reliability of annotations. Data monitoring tools help monitor the quality of the data.