Author name: aiepicentre

Amazon Bedrock Agents observability using Arize AI

Amazon Bedrock, Amazon Bedrock Agents, Amazon Machine Learning, Artificial Intelligence, Generative AI, Intermediate (200) /

This post is cowritten with John Gilhuly from Arize AI. With Amazon Bedrock Agents, you can build and configure autonomous agents in your application. An agent helps your end-users complete actions based on organization data and user input. Agents orchestrate interactions between foundation models (FMs), data sources, software applications, and user conversations. In addition, agents […]

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How SkillShow automates youth sports video processing using Amazon Transcribe

Amazon Transcribe, AWS Lambda, Customer Solutions, Media & Entertainment, Partner solutions, Sports /

This post is co-written with Tom Koerick from SkillShow. The youth sports market was valued at $37.5 billion globally in 2022 and is projected to grow by 9.2% each year through 2030. Approximately 60 million young athletes participate in this market worldwide. SkillShow, a leader in youth sports video production, films over 300 events yearly

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NewDay builds A Generative AI based Customer service Agent Assist with over 90% accuracy

Amazon Bedrock, Amazon Cognito, Artificial Intelligence, AWS Fargate, Contact Center, Customer Solutions, Financial Services, Generative AI /

This post is co-written with Sergio Zavota and Amy Perring from NewDay. NewDay has a clear and defining purpose: to help people move forward with credit. NewDay provides around 4 million customers access to credit responsibly and delivers exceptional customer experiences, powered by their in-house technology system. NewDay’s contact center handles 2.5 million calls annually,

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No-code data preparation for time series forecasting using Amazon SageMaker Canvas

Amazon SageMaker, Amazon SageMaker Data Wrangler, Intermediate (200), Technical How-to /

Time series forecasting helps businesses predict future trends based on historical data patterns, whether it’s for sales projections, inventory management, or demand forecasting. Traditional approaches require extensive knowledge of statistical methods and data science methods to process raw time series data. Amazon SageMaker Canvas offers no-code solutions that simplify data wrangling, making time series forecasting

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Build an agentic multimodal AI assistant with Amazon Nova and Amazon Bedrock Data Automation

Amazon Bedrock, Amazon Bedrock Agents, Amazon Bedrock Data Automation, Amazon Bedrock Knowledge Bases, Amazon Machine Learning, Amazon Nova, Artificial Intelligence, Generative AI /

Modern enterprises are rich in data that spans multiple modalities—from text documents and PDFs to presentation slides, images, audio recordings, and more. Imagine asking an AI assistant about your company’s quarterly earnings call: the assistant should not only read the transcript but also “see” the charts in the presentation slides and “hear” the CEO’s remarks.

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Build a scalable AI video generator using Amazon SageMaker AI and CogVideoX

Amazon SageMaker, Amazon SageMaker AI, Artificial Intelligence, Generative AI, Intermediate (200) /

In recent years, the rapid advancement of artificial intelligence and machine learning (AI/ML) technologies has revolutionized various aspects of digital content creation. One particularly exciting development is the emergence of video generation capabilities, which offer unprecedented opportunities for companies across diverse industries. This technology allows for the creation of short video clips that can be

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Building trust in AI: The AWS approach to the EU AI Act

Artificial Intelligence, Responsible AI /

As AI adoption accelerates and reshapes our future, organizations are adapting to evolving regulatory frameworks. In our report commissioned to Strand Partners, Unlocking Europe’s AI Potential in the Digital Decade 2025, 68% of European businesses surveyed underlined that they struggle to understand their responsibilities under the EU AI Act. European businesses also highlighted that an

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Meeting summarization and action item extraction with Amazon Nova

AI/ML, Amazon Bedrock, Amazon Nova, Generative AI, Intermediate (200), Technical How-to /

Meetings play a crucial role in decision-making, project coordination, and collaboration, and remote meetings are common across many organizations. However, capturing and structuring key takeaways from these conversations is often inefficient and inconsistent. Manually summarizing meetings or extracting action items requires significant effort and is prone to omissions or misinterpretations. Large language models (LLMs) offer

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