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How to Use Generative AI and LLMs to Improve Search

TechEmpower CTO

Artificial Intelligence (AI), and particularly Large Language Models (LLMs), have significantly transformed the search engine as we’ve known it. With Generative AI and LLMs, new avenues for improving operational efficiency and user satisfaction are emerging every day.

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Build a multi-tenant generative AI environment for your enterprise on AWS

AWS Machine Learning - AI

While organizations continue to discover the powerful applications of generative AI , adoption is often slowed down by team silos and bespoke workflows. To move faster, enterprises need robust operating models and a holistic approach that simplifies the generative AI lifecycle.

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Multi-LLM routing strategies for generative AI applications on AWS

AWS Machine Learning - AI

Organizations are increasingly using multiple large language models (LLMs) when building generative AI applications. The Basic tier would use a smaller, more lightweight LLM well-suited for straightforward tasks, such as performing simple document searches or generating summaries of uncomplicated legal documents.

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Active learning is the future of generative AI: Here’s how to leverage it

TechCrunch

These advancements in generative AI offer further evidence that we’re on the precipice of an AI revolution. However, most of these generative AI models are foundational models: high-capacity, unsupervised learning systems that train on vast amounts of data and take millions of dollars of processing power to do it.

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Accelerate AWS Well-Architected reviews with Generative AI

AWS Machine Learning - AI

In this post, we explore a generative AI solution leveraging Amazon Bedrock to streamline the WAFR process. We demonstrate how to harness the power of LLMs to build an intelligent, scalable system that analyzes architecture documents and generates insightful recommendations based on AWS Well-Architected best practices.

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Principal Financial Group uses QnABot on AWS and Amazon Q Business to enhance workforce productivity with generative AI

AWS Machine Learning - AI

With the QnABot on AWS (QnABot), integrated with Microsoft Azure Entra ID access controls, Principal launched an intelligent self-service solution rooted in generative AI. Generative AI models (for example, Amazon Titan) hosted on Amazon Bedrock were used for query disambiguation and semantic matching for answer lookups and responses.

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Build a video insights and summarization engine using generative AI with Amazon Bedrock

AWS Machine Learning - AI

Furthermore, these notes are usually personal and not stored in a central location, which is a lost opportunity for businesses to learn what does and doesn’t work, as well as how to improve their sales, purchasing, and communication processes. Many commercial generative AI solutions available are expensive and require user-based licenses.