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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. As LLMs become integral to AI applications, ethical considerations take center stage.

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A Guide to Mastering Large Language Models

Unite.AI

Large language models (LLMs) have exploded in popularity over the last few years, revolutionizing natural language processing and AI. From chatbots to search engines to creative writing aids, LLMs are powering cutting-edge applications across industries. LLMs utilize embeddings to understand word context.

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Large Language Model Ops (LLM Ops)

Mlearning.ai

Add Responsible AI to LLM’s Add Abuse detection to LLM’s. Prompt Engineering — this is where figuring out what is the right prompt to use for the problem. Develop the LLM application using existing models or train a new model. Add monitoring and auditing code to log prompts and completion.

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Top Artificial Intelligence AI Courses from Google

Marktechpost

Inspect Rich Documents with Gemini Multimodality and Multimodal RAG This course covers using multimodal prompts to extract information from text and visual data and generate video descriptions with Gemini. TensorFlow on Google Cloud This course covers designing TensorFlow input data pipelines and building ML models with TensorFlow and Keras.

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How 20 Minutes empowers journalists and boosts audience engagement with generative AI on Amazon Bedrock

AWS Machine Learning Blog

For several years, we have been actively using machine learning and artificial intelligence (AI) to improve our digital publishing workflow and to deliver a relevant and personalized experience to our readers. This blog post outlines various use cases where we’re using generative AI to address digital publishing challenges.

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MLOps Landscape in 2023: Top Tools and Platforms

The MLOps Blog

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. Can you find experiments and models easily?

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Google’s Dr. Arsanjani on Enterprise Foundation Model Challenges

Snorkel AI

Today we’re going to be talking essentially about how responsible generative-AI-model adoption can happen at the enterprise level, and what are some of the promises and compromises we face. The foundation of large language models started quite some time ago. What are the promises?