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Harnessing event-driven architecture for scalable AI solutions

In today’s tech landscape, event-driven architecture is transforming how applications handle data, interact with users, and execute complex processes. At DevSparks 2024, YourStory‘s flagship developer summit held in Bengaluru, Todd Greene, Co-founder and CEO, PubNub, shared insights on how this architecture is enhancing AI integration across various platforms.

Extending AI capabilities

Event-driven architecture simplifies AI integration by allowing systems to respond to specific events rather than undergoing a full-scale development phase. This enables real-time monitoring and decision-making processes, making it highly adaptable for various use cases, such as moderating and filtering content, language translation, and IoT signal processing.

Greene emphasised the versatility of event-driven systems, highlighting their ability to handle different types of events beyond chat messages. These systems can manage IoT signals, game player interactions, and purchase signals, offering seamless integration of AI to detect fraud, ensure regulatory compliance, and optimise operational efficiencies.

A significant advancement at PubNub is the integration with Hugging Face, a renowned repository for AI models. This integration allows developers to access and utilise over 5,00,000 AI models, facilitating the moderation and enhancement of applications in languages and scenarios that were previously underserved. The ability to route events to these models dynamically extends the functionality of applications, enabling more personalised and context-specific AI responses.

One of the critical challenges in AI implementation is the cost associated with processing large volumes of data. Greene pointed out that event-driven architecture can mitigate these costs by enabling selective AI processing. By profiling user trust levels, systems can decide which users require intensive AI scrutiny and which do not, optimising resource allocation and reducing unnecessary expenditures.

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Growth amplification through experimentation

Growth amplification involves improving key performance indicators (KPIs) through incremental enhancements. In traditional setups, running experiments to optimise these KPIs is a laborious process. However, with event-driven architecture, PubNub enables real-time experimentation without extensive developer involvement. This platform allows for immediate adjustments and insights, significantly accelerating the iteration process.

“You’re not really going to go back to the drawing board. And you’re not going to test on a user-by-user basis. You probably want to test on the aggregate audience together. The concepts are the same. But technically, how do you take a stream of events coming in from millions of people, segment them into logical groups that make sense for your business, and then fire off events based on how those cohorts behave? The technical challenges are very different,” Greene said.

Addressing the burgeoning traffic from billions of IoT devices, Greene explained that event-driven software is inherently more efficient. By transmitting small, specific packets of data instead of large REST requests, this architecture minimises internet traffic and enhances scalability. Moreover, it provides a controlled environment for implementing business rules and fraud detection, ensuring a balance between flexibility and security.

“Event-driven software actually reduces traffic on the internet, not expands it, because you’re literally just sending little packets of information specific with the content you need, not these huge packets of REST request data and responses coming back. So it’s actually, first of all, from a scaling perspective, very efficient,” Greene said.

Greene’s insights at DevSparks highlight the transformative potential of event-driven architecture in AI integration. By enabling real-time, scalable, and cost-efficient AI applications, this approach paves the way for innovative solutions across industries. As advancements in AI and event-driven systems continue, businesses will need to quickly adapt and optimise to stay competitive.

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