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Evolving Trends in Prompt Engineering for Large Language Models (LLMs) with Built-in Responsible AI…

ODSC - Open Data Science

Evolving Trends in Prompt Engineering for Large Language Models (LLMs) with Built-in Responsible AI Practices Editor’s note: Jayachandran Ramachandran and Rohit Sroch are speakers for ODSC APAC this August 22–23. Various prompting techniques, such as Zero/Few Shot, Chain-of-Thought (CoT)/Self-Consistency, ReAct, etc.

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Evaluate the reliability of Retrieval Augmented Generation applications using Amazon Bedrock

AWS Machine Learning Blog

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. In this case, the model choice needs to be revisited or further prompt engineering needs to be done.

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MLOps Landscape in 2023: Top Tools and Platforms

The MLOps Blog

The platform also offers features for hyperparameter optimization, automating model training workflows, model management, prompt engineering, and no-code ML app development. Can you see the complete model lineage with data/models/experiments used downstream? Is it fast and reliable enough for your workflow?

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Future of Data-Centric AI day 1: LLMs changed the world

Snorkel AI

The session highlighted the “last mile” problem in AI applications and emphasized the importance of data-centric approaches in achieving production-level accuracy. In particular, he highlighted his company’s Demonstrate-Search-Predict framework which abstracts away aspects of using foundation models, such as prompt engineering.

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Future of Data-Centric AI day 1: LLMs changed the world

Snorkel AI

The session highlighted the “last mile” problem in AI applications and emphasized the importance of data-centric approaches in achieving production-level accuracy. In particular, he highlighted his company’s Demonstrate-Search-Predict framework which abstracts away aspects of using foundation models, such as prompt engineering.

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Google’s Dr. Arsanjani on Enterprise Foundation Model Challenges

Snorkel AI

Others, toward language completion and further downstream tasks. In media and gaming: designing game storylines, scripts, auto-generated blogs, articles and tweets, and grammar corrections and text formatting. Then comes prompt engineering. Prompt engineering cannot be thought of as a very simple matter.

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Google’s Arsanjani on Enterprise Foundation Model Challenges

Snorkel AI

Others, toward language completion and further downstream tasks. In media and gaming: designing game storylines, scripts, auto-generated blogs, articles and tweets, and grammar corrections and text formatting. Then comes prompt engineering. Prompt engineering cannot be thought of as a very simple matter.