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Rather than maintaining constantly running endpoints, the system creates them on demand when document processing begins and automatically stops them upon completion. The decoupled nature of the endpoints also provides flexibility to update or replace individual models without impacting the broader systemarchitecture.
Agent broker methodology Following an agent broker pattern, the system is still fundamentally event-driven, with actions triggered by the arrival of messages. New agents can be added to handle specific types of messages without changing the overall systemarchitecture.
The systemarchitecture comprises several core components: UI portal – This is the user interface (UI) designed for vendors to upload product images. AWS Lambda – AWS Lambda provides serverless compute for processing. Amazon API Gateway passes the request to AWS Lambda through a proxy integration.
Understanding the intrinsic value of data network effects, Vidmob constructed a product and operational systemarchitecture designed to be the industry’s most comprehensive RLHF solution for marketing creatives. Dynamo DB stores the query and the session ID, which is then passed to a Lambda function as a DynamoDB event notification.
Over the past handful of years, systemsarchitecture has evolved from monolithic approaches to applications and platforms that leverage containers, schedulers, lambda functions, and more across heterogeneous infrastructures. To do so, the platform provides a range of analytics across the complete data life cycle.
But consider the Amazon team that came up with Lambda. Some customers report up to an order of magnitude reduction in cost when they switch to Lambda. Yet the Lambda team did not have to answer the sobering question: “Do you know how much revenue Lambda might cannibalize?” You could feel the tail wind.
There are various technologies that help operationalize and optimize the process of field trials, including data management and analytics, IoT, remote sensing, robotics, machinelearning (ML), and now generative AI. AWS Lambda is then used to further enrich the data. The transformed data acts as the input to AI/ML services.
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