Remove APIs Remove Big data Remove Chatbots
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Centralize model governance with SageMaker Model Registry Resource Access Manager sharing

AWS Machine Learning

Customers can use the SageMaker Studio UI or APIs to specify the SageMaker Model Registry model to be shared and grant access to specific AWS accounts or to everyone in the organization. We will start by using the SageMaker Studio UI and then by using APIs.

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How Formula 1® uses generative AI to accelerate race-day issue resolution

AWS Machine Learning

During these live events, F1 IT engineers must triage critical issues across its services, such as network degradation to one of its APIs. This impacts downstream services that consume data from the API, including products such as F1 TV, which offer live and on-demand coverage of every race as well as real-time telemetry.

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Insights in implementing production-ready solutions with generative AI

AWS Machine Learning

ENGIEs One Data team partnered with AWS Professional Services to develop an AI-powered chatbot that enables natural language conversation search within ENGIEs Common Data Hub data lake, over 3 petabytes of data. This allowed them to quickly move their API-based backend services to a cloud-native environment.

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TechSee Launches “Visual Intelligence Platform”

TechSee

Furthermore, businesses can now build their own applications powered by VI’s customized computer vision insights using real-time APIs. Computer vision AI has the potential to close a substantial gap in self-service, as only 11% of respondents reported that chatbots were able to solve their issues without escalating to a human.

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Cepsa Química improves the efficiency and accuracy of product stewardship using Amazon Bedrock

AWS Machine Learning

User interface – A conversational chatbot enables interaction with users. Note on the RAG implementation The product stewardship chatbot was built before Knowledge Bases for Amazon Bedrock was generally available. About the authors Vicente Cruz Mínguez is the Head of Data & Advanced Analytics at Cepsa Química.

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Retrieval-Augmented Generation with LangChain, Amazon SageMaker JumpStart, and MongoDB Atlas semantic search

AWS Machine Learning

Generative AI models have the potential to revolutionize enterprise operations, but businesses must carefully consider how to harness their power while overcoming challenges such as safeguarding data and ensuring the quality of AI-generated content. As a Data Engineer he was involved in applying AI/ML to fraud detection and office automation.

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Generating value from enterprise data: Best practices for Text2SQL and generative AI

AWS Machine Learning

We are seeing numerous uses, including text generation, code generation, summarization, translation, chatbots, and more. One such area that is evolving is using natural language processing (NLP) to unlock new opportunities for accessing data through intuitive SQL queries. What percentage of customers are from each region?”