JavaScript is rapidly becoming a core language for building AI-powered applications, bridging the gap between advanced machine learning models and interactive web experiences. From running models directly in the browser to integrating large language models into full-stack applications, developers today can create intelligent, responsive, and highly personalized products using familiar JS tools. This track explores both the practical and experimental sides of AI in the JavaScript ecosystem, focusing on how developers can build real-world applications while understanding the underlying concepts that make them work.

Topics include:

• Building AI-powered web apps with JavaScript and Node.js
• Running machine learning models in the browser (WebAssembly/WebGPU)
• Integrating large language models into full-stack applications
• Streaming AI responses for real-time user experiences
• Prompt engineering techniques for developers
• Building autonomous AI agents with tool-calling workflows
• Implementing Retrieval-Augmented Generation (RAG) systems
• Using TensorFlow.js for vision and speech applications
• Optimizing performance and cost in AI applications
• Designing modern, user-friendly AI interfaces in the frontend