Data Integration DevOps Prompt Engineering 
IBM Journey to AI blog
JANUARY 15, 2024
For example, generative AI as a prompt engine will improve efficiency by dramatically reducing the time humans take to create outlines, come up with ideas and learn important information. Low-code helps the DevOps team by simplifying some aspects of coding and no-code can introduce non-developers into the development process.
AWS Machine Learning Blog
MAY 1, 2024
It allows you to retrieve data from sources beyond the foundation model, enhancing prompts by integrating contextually relevant retrieved data. You can use prompt engineering to prevent hallucination and make sure that the answer is grounded in the source documentations.
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Heartbeat
MARCH 19, 2024
Like machine learning operations, LLMOps involves efforts from several contributors, like prompt engineers, data scientists, DevOps engineers, business analysts, and IT operations. Several factors to consider include model output quality, response speed, level of data integrity, and resource and cost constraints.
The MLOps Blog
JUNE 27, 2023
W&B (Weights & Biases) W&B is a machine learning platform for your data science teams to track experiments, version and iterate on datasets, evaluate model performance, reproduce models, visualize results, spot regressions, and share findings with colleagues. Easy collaboration, annotator management, and QA workflows.
AWS Machine Learning Blog
NOVEMBER 27, 2024
With the Amazon Bedrock serverless experience, you can get started quickly, privately customize FMs with your own data, integrate and deploy them into your application using Amazon Web Services (AWS) tools without having to manage any infrastructure.
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