AWS Simplifies Model Customization to Help Customers Build Faster, More Efficient AI Agents

Key Terms

reinforcement fine tuning technical

Reinforcement fine tuning is the process of taking a general-purpose AI model and improving it for a specific task by giving it feedback or rewards for desired behavior, much like coaching someone with practice, correction, and praise until they reliably perform well. For investors, it matters because this tuning can materially boost a product’s accuracy, user experience and market fit — affecting development costs, time to market, competitive advantage and regulatory or reputational risk.

serverless model customization technical

Serverless model customization is the process of tailoring a machine learning or AI model to a company's specific data and needs without managing dedicated servers or infrastructure; the provider automatically handles computing resources behind the scenes. For investors, it matters because it lets businesses add unique features or improve accuracy quickly and at lower operational cost—like renting a fully staffed workshop to modify a tool instead of buying and maintaining the whole factory—potentially speeding product rollout and reducing capital investment.

reinforcement learning technical

A type of artificial intelligence that learns by trial and error, receiving feedback from its actions to favor choices that lead to better outcomes. Think of it like a salesperson learning which pitches close deals by trying different approaches and keeping the ones that work. For investors, reinforcement learning matters because it can power smarter trading systems, optimize business operations, or improve products—potentially boosting efficiency and profits while also introducing model and execution risks.

Amazon Bedrock and Amazon SageMaker AI put advanced model customization into the hands of any developer, while reducing costs and improving performance

LAS VEGAS--(BUSINESS WIRE)-- At AWS re:Invent, Amazon Web Services, Inc. (AWS), an Amazon.com, Inc. company (NASDAQ: AMZN), today announced new Amazon Bedrock and Amazon SageMaker AI capabilities: Reinforcement Fine Tuning (RFT) in Amazon Bedrock and serverless model customization in Amazon SageMaker AI with reinforcement learning.

Key takeaways

• New Amazon Bedrock and Amazon SageMaker AI capabilities give customers access to advanced techniques for model customization.
• Reinforcement Fine Tuning in Amazon Bedrock makes it easier to tailor models to unique cases and improve accuracy.
• Amazon SageMaker AI cuts advanced model customization workflows from months to days, accelerating AI development and bringing new solutions to market faster.

To get the full story on these new customization capabilities, visit About Amazon.

About AWS

Amazon Web Services (AWS) is guided by customer obsession, pace of innovation, commitment to operational excellence, and long-term thinking. By democratizing technology for nearly two decades and making cloud computing and generative AI accessible to organizations of every size and industry, AWS has built one of the fastest-growing enterprise technology businesses in history. Millions of customers trust AWS to accelerate innovation, transform their businesses, and shape the future. With the most comprehensive AI capabilities and global infrastructure footprint, AWS empowers builders to turn big ideas into reality. Learn more at aws.amazon.com and follow @AWSNewsroom.

View source version on businesswire.com: https://www.businesswire.com/news/home/20251202536517/en/

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Source: Amazon.com, Inc.