Technical How-to

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Build a Multi-Agent System with LangGraph and Mistral on AWS

Amazon Bedrock, Amazon Machine Learning, Foundation models, Generative AI, Technical How-to /

Agents are revolutionizing the landscape of generative AI, serving as the bridge between large language models (LLMs) and real-world applications. These intelligent, autonomous systems are poised to become the cornerstone of AI adoption across industries, heralding a new era of human-AI collaboration and problem-solving. By using the power of LLMs and combining them with specialized […]

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Build a multimodal social media content generator using Amazon Bedrock

Amazon Bedrock, Content Production, Generative AI, Technical How-to /

In today’s digital age, social media has revolutionized the way brands interact with their consumers, creating a need for dynamic and engaging content that resonates with their target audience. There’s growing competition for consumer attention in this space; content creators and influencers face constant challenges to produce new, engaging, and brand-consistent content. The challenges come

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Build an ecommerce product recommendation chatbot with Amazon Bedrock Agents

AI/ML, Amazon Bedrock, Artificial Intelligence, Generative AI, Industries, Intermediate (200), Retail, Technical How-to /

Many ecommerce applications want to provide their users with a human-like chatbot that guides them to choose the best product as a gift for their loved ones or friends. To enhance the customer experience, the chatbot need to engage in a natural, conversational manner to understand the user’s preferences and requirements, such as the recipient’s

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Build generative AI chatbots using prompt engineering with Amazon Redshift and Amazon Bedrock

Advanced (300), Amazon Bedrock, Amazon Redshift, Generative AI, Technical How-to /

With the advent of generative AI solutions, organizations are finding different ways to apply these technologies to gain edge over their competitors. Intelligent applications, powered by advanced foundation models (FMs) trained on huge datasets, can now understand natural language, interpret meaning and intent, and generate contextually relevant and human-like responses. This is fueling innovation across

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Build a movie chatbot for TV/OTT platforms using Retrieval Augmented Generation in Amazon Bedrock

Advanced (300), Amazon Bedrock, Technical How-to /

Improving how users discover new content is critical to increase user engagement and satisfaction on media platforms. Keyword search alone has challenges capturing semantics and user intent, leading to results that lack relevant context; for example, finding date night or Christmas-themed movies. This can drive lower retention rates if users can’t reliably find the content

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Build generative AI agents with Amazon Bedrock, Amazon DynamoDB, Amazon Kendra, Amazon Lex, and LangChain

Amazon Bedrock, Amazon Kendra, Amazon Lex, Amazon Machine Learning, Artificial Intelligence, Generative AI, Technical How-to /

Generative AI agents are capable of producing human-like responses and engaging in natural language conversations by orchestrating a chain of calls to foundation models (FMs) and other augmenting tools based on user input. Instead of only fulfilling predefined intents through a static decision tree, agents are autonomous within the context of their suite of available

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How AWS Prototyping enabled ICL-Group to build computer vision models on Amazon SageMaker

Amazon SageMaker, Amazon SageMaker Ground Truth, Best Practices, Customer Solutions, Technical How-to /

This is a customer post jointly authored by ICL and AWS employees. ICL is a multi-national manufacturing and mining corporation based in Israel that manufactures products based on unique minerals and fulfills humanity’s essential needs, primarily in three markets: agriculture, food, and engineered materials. Their mining sites use industrial equipment that has to be monitored

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