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Creating asynchronous AI agents with Amazon Bedrock

AWS Machine Learning - AI

This architecture can enable businesses to streamline operations, enhance decision-making processes, and automate complex tasks in new ways. These systems are composed of multiple AI agents that converse with each other or execute complex tasks through a series of choreographed or orchestrated processes.

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Reasons to hire IoT developer to transform the industrial sphere

Xicom

They are striking in terms of visibility, operational efficiency, productivity and innovative business models. Intelligent homes, intelligent security systems, real-time monitoring and tracking systems, switching plants, smart gloves, smart mirrors, smart devices, etc. What is IoT? IoT is the short form of Internet of Things.

IoT 40
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Grown-Up Lean

LeanEssays

Flexibility to changes in volume and product mix in production are the same as flexibility to changes in design, schedule, and cost targets in development. Continuous improvement in production equates to frequent, incremental innovations in development. Small, independent teams own a small service – called a microservice these days.

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Journey to Event Driven – Part 4: Four Pillars of Event Streaming Microservices

Confluent

With event-first design, the data becomes the API which, like any production system, needs to support change and evolution (i.e., Furthermore, in embracing loose coupling, we inherit a clean separation of concerns (SoC) , which provides the ability to develop and operate various aspects of the system architecture independently.

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22 Health IT Experts Reveal the Single Best Way to Simplify Interoperability in Healthcare IT

Datica

I’ve been involved with innovative products that mostly live outside the core EHR system for more than 15 years. Amit served in the Israel Defense Force’s elite cyber intelligence unit (Unit 81) and is a cybersecurity expert with extensive experience in system architecture and software development. Jeremy Ognall.

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Optimizing AI responsiveness: A practical guide to Amazon Bedrock latency-optimized inference

AWS Machine Learning - AI

In this section, we explore how different system components and architectural decisions impact overall application responsiveness. System architecture and end-to-end latency considerations In production environments, overall system latency extends far beyond model inference time.