AI

Build scalable creative solutions for product teams with Amazon Bedrock

Creative teams and product developers are constantly seeking ways to streamline their workflows and reduce time to market while maintaining quality and brand consistency. This post demonstrates how to use AWS services, particularly Amazon Bedrock, to transform your creative processes through generative AI. You can implement a secure, scalable solution that accelerates your creative workflow, […]

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Build a proactive AI cost management system for Amazon Bedrock – Part 2

In Part 1 of our series, we introduced a proactive cost management solution for Amazon Bedrock, featuring a robust cost sentry mechanism designed to enforce real-time token usage limits. We explored the core architecture, token tracking strategies, and initial budget enforcement techniques that help organizations control their generative AI expenses. Building upon that foundation, this

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Build a proactive AI cost management system for Amazon Bedrock – Part 1

As organizations embrace generative AI powered by Amazon Bedrock, they face the challenge of managing costs associated with the token-based pricing model. Amazon Bedrock offers a pay-as-you-go pricing structure that can potentially lead to unexpected and excessive bills if usage is not carefully monitored. Traditional methods of cost monitoring, such as budget alerts and cost

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Streamline code migration using Amazon Nova Premier with an agentic workflow

Many enterprises are burdened with mission-critical systems built on outdated technologies that have become increasingly difficult to maintain and extend. This post demonstrates how you can use the Amazon Bedrock Converse API with Amazon Nova Premier within an agentic workflow to systematically migrate legacy C code to modern Java/Spring framework applications. By breaking down the

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Metagenomi generates millions of novel enzymes cost-effectively using AWS Inferentia

This post was written with Audra Devoto, Owen Janson, and Christopher Brown of Metagenomi, and Adam Perry of Tennex. A promising strategy to augment the extensive natural diversity of high value enzymes is to use generative AI, specifically protein language models (pLMs), trained on known enzymes to create orders of magnitude more predicted examples of

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Creating AI that matters

When it comes to artificial intelligence, MIT and IBM were there at the beginning: laying foundational work and creating some of the first programs — AI predecessors — and theorizing how machine “intelligence” might come to be. Today, collaborations like the MIT-IBM Watson AI Lab, which launched eight years ago, are continuing to deliver expertise

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