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Enhance customer support with Amazon Bedrock Agents by integrating enterprise data APIs

AWS Machine Learning

In this post, we guide you through integrating Amazon Bedrock Agents with enterprise data APIs to create more personalized and effective customer support experiences. Although the principles discussed are applicable across various industries, we use an automotive parts retailer as our primary example throughout this post.

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Customize small language models on AWS with automotive terminology

AWS Machine Learning

For instance, in the automotive industry, users might not always provide specific diagnostic trouble codes (DTCs), which are often proprietary to each manufacturer. Similarly, in tasks like code generation and suggestions through chat-based applications, users might not specify the APIs they want to use.

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Simplify automotive damage processing with Amazon Bedrock and vector databases

AWS Machine Learning

In the automotive industry, the ability to efficiently assess and address vehicle damage is crucial for efficient operations, customer satisfaction, and cost management. By combining these powerful tools, we have developed a comprehensive solution that streamlines the process of identifying and categorizing automotive damage.

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Driving API Security Forward: Protecting Vehicle-to-Cloud Communications

Cisco - Contact Center

In the rapidly evolving automotive landscape, vehicles are no longer just machines that move us from point A to point B; they have transformed into complex, interconnected systems on wheels. With this… Read more on Cisco Blogs

APIs 75
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Amazon EC2 DL2q instance for cost-efficient, high-performance AI inference is now generally available

AWS Machine Learning

The same Qualcomm AI stack and base AI technology runs on the DL2q instances and Qualcomm edge devices, providing customers a consistent developer experience, with a unified API across their cloud, automotive, personal computer, extended reality, and smartphone development environments. reshape(output_shape) Decode the output produced.

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How FP8 boosts LLM training by 18% on Amazon SageMaker P5 instances

AWS Machine Learning

To enable FP8 training, models need to use the TE API to incorporate these layers when casted to FP8. Utilizing his twenty years of experience, he helps accelerate tech transformation of automotive companies. linear_type: nn.Module = te.Linear if using_te else nn.Linear. In his free time, he enjoys playing video games and travel.

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Automate chatbot for document and data retrieval using Agents and Knowledge Bases for Amazon Bedrock

AWS Machine Learning

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon through a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI.

Chatbots 127