Auto-classification Automation Prompt Engineering 
AWS Machine Learning Blog
FEBRUARY 12, 2025
The brand might be willing to absorb the higher costs of using a more powerful and expensive FMs to achieve the highest-quality classifications, because misclassifications could lead to customer dissatisfaction and damage the brands reputation. Consider another use case of generating personalized product descriptions for an ecommerce site.
IBM Journey to AI blog
JULY 10, 2023
However, to achieve this transformation successfully, it is crucial to incorporate a hybrid cloud management platform that prioritizes AI-infused automation. Start with a platform-centric approach Standardization is crucial for organizations looking to automate and modernize.
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AWS Machine Learning Blog
DECEMBER 5, 2023
The insurance provider receives payout claims from the beneficiary’s attorney for different insurance types, such as home, auto, and life insurance. This post illustrates how you can automate and simplify metadata generation using custom models by Amazon Comprehend. Custom classification is a two-step process.
AWS Machine Learning Blog
OCTOBER 6, 2023
For instance, in ecommerce, image-to-text can automate product categorization based on images, enhancing search efficiency and accuracy. CLIP model CLIP is a multi-modal vision and language model, which can be used for image-text similarity and for zero-shot image classification.
AWS Machine Learning Blog
MAY 17, 2024
They’re capable of performing a wide variety of general tasks with a high degree of accuracy based on input prompts. LLMs are specifically focused on language-based tasks such as summarization, text generation, classification, open-ended conversation, and information extraction. Prompt engineering is an iterative process.
AWS Machine Learning Blog
JUNE 20, 2024
Additionally, evaluation can identify potential biases, hallucinations, inconsistencies, or factual errors that may arise from the integration of external sources or from sub-optimal prompt engineering. Evaluating RAG systems at scale requires an automated approach to extract metrics that are quantitative indicators of its reliability.
The MLOps Blog
JUNE 27, 2023
This includes features for hyperparameter tuning, automated model selection, and visualization of model metrics. Automated pipelining and workflow orchestration: Platforms should provide tools for automated pipelining and workflow orchestration, enabling you to define and manage complex ML pipelines.
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