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Moving From Best Practices to Next Practices

CCNG

For decades, organizations have clung to the comfort of best practices, those tried-and-true methods that promise safe results. In a world thats constantly evolving, best is usually just a nicer way of saying barely keeping up. Why Best Practices Dont Cut It Anymore Best practices are like comfort food.

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Image and video prompt engineering for Amazon Nova Canvas and Amazon Nova Reel

AWS Machine Learning

This post dives deep into prompt engineering for both Nova Canvas and Nova Reel. When writing a video generation prompt for Nova Reel, be mindful of the following requirements and best practices: Prompts must be no longer than 512 characters. Specify what you want to include rather than what to exclude.

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Best practices for Amazon SageMaker HyperPod task governance

AWS Machine Learning

In this post, we provide best practices to maximize the value of SageMaker HyperPod task governance and make the administration and data science experiences seamless. As a best practice, set the fair-share weight higher for teams that will require access to capacity sooner than other teams.

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Generating value from enterprise data: Best practices for Text2SQL and generative AI

AWS Machine Learning

In this post, we provide an introduction to text to SQL (Text2SQL) and explore use cases, challenges, design patterns, and best practices. Effective prompt engineering is key to developing natural language to SQL systems. Prompt engineering – The model is trained to complete prompts designed to prompt the target SQL syntax.

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Best practices for prompt engineering with Meta Llama 3 for Text-to-SQL use cases

AWS Machine Learning

In this post, we provide an overview of the Meta Llama 3 models available on AWS at the time of writing, and share best practices on developing Text-to-SQL use cases using Meta Llama 3 models. All the code used in this post is publicly available in the accompanying Github repository.

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Best practices to build generative AI applications on AWS

AWS Machine Learning

We provide an overview of key generative AI approaches, including prompt engineering, Retrieval Augmented Generation (RAG), and model customization. Building large language models (LLMs) from scratch or customizing pre-trained models requires substantial compute resources, expert data scientists, and months of engineering work.

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Struggling With How to Generate Leads? Use These Best Practices

Quality Contact Solutions

That’s why we’ve compiled four best practices to help you meet your sales goals and keep your team busy. Our next lead generation best practice is customer service. Our next best practice in how to generate leads is to focus on your website. Case Study: B2B Lead Generation & Cold Calling.