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Generative AI models have transformed technology by enabling applications like chatbots and content generation. However, they often face limitations such as knowledge cutoffs—where models lack awareness of recent events—and hallucinations, where models confidently provide incorrect information. These issues can hinder the effectiveness of AI in real-world applications. Retrieval-Augmented Generation (RAG) offers a solution by enhancing […]

Agents for Amazon Bedrock are transforming the way developers build AI applications by enabling them to execute multi-step business tasks using natural language. This innovation allows AI to not only understand requests but also take action, bridging the gap between comprehension and execution. What Are Agents for Amazon Bedrock? Agents are a powerful feature within

Efficient log analysis is essential for maintaining security and operational excellence in cloud environments. AWS CloudTrail Lake, a managed data lake for activity logs, has introduced two AI-powered features that simplify and enhance this process: Natural Language Query Generation and Query Result Summarization. AI-Powered Natural Language Query Generation This feature allows users to interact with

Generative AI has revolutionized the way we interact with technology, enabling applications to produce human-like text, images, and even code. However, leveraging generative AI for practical, real-world applications often requires integrating proprietary data and ensuring efficient data retrieval. In this blog post, we’ll explore how Amazon Bedrock and PostgreSQL with the PGVector extension can be

If you’re exploring artificial intelligence and machine learning on AWS, you’re likely familiar with two prominent tools: Amazon Bedrock and Amazon SageMaker. While both offer robust capabilities, each is tailored for distinct needs and stages in the AI development lifecycle. Here’s a guide to understanding the differences between Bedrock and SageMaker and when to use

Generative AI has revolutionized the way we interact with technology, enabling more natural and intuitive experiences. Yet, while large language models (LLMs) excel at understanding and generating human-like text, they often lack the ability to take direct action on our behalf. This is where Agents for Amazon Bedrock come into play, bridging the gap between

Why AWS Fundamentals Matter More Than Service Changes Given the way Amazon Web Services (AWS) has been continuously innovating, it’s easy to feel overwhelmed by the constant stream of new services, features, and updates. However, there’s a fundamental truth that experienced cloud architects and engineers understand: mastering the core concepts of AWS is far more

Alright, let’s talk about a little thing called screen sharing. Amazon Connect just rolled it out, and it’s about to make every customer service interaction a whole lot smoother. If you’ve ever been stuck on a support call trying to explain what’s happening on your screen, you know how quickly things can go sideways. Now?

In the last couple of years, generative AI has emerged as a powerful tool that spans industries and use cases. Yet, while these models are exceptional at generating responses, they typically fall short when it comes to taking direct actions on behalf of users. This is where agents for Amazon Bedrock step in, transforming large

Managing code for Google Apps Script can be a hassle, especially if you want version control. Luckily, you can use CLASP (Command Line Apps Script) to develop scripts locally and sync them with your Google Apps Script projects. In this guide, we’ll cover how to: 1. Installing Prerequisites Install Node.js and NPM Install CLASP globally using NPM: