In this talk, I'll share how to streamline the entire AI integration from private data all the way to our JS projects, all in one line of code using Unbody.io. We'll explore the challenges that non-ai developers are facing with getting into AI world, and the simplicity behind Unbody, avoiding intimidating AI jargon, and focus on its practical application.

In this presentation, we will delve into the exciting world of creating an AI-powered chatbot using SvelteKit. The session aims to provide an easy-to-digest guide for developers, covering key concepts and tools to seamlessly integrate artificial intelligence into your chatbot project.

With the rapid adoption of AI models in software products, Chrome’s introduction of local-first, on-device AI models offers developers a powerful new way to build intelligent and fast AI features directly within the browser. This talk will explore Chrome’s Built-in AI models, their architecture, APIs, developer tooling, and also demonstrate how it supports low-latency AI experiences without relying solely on cloud-deployed models.

We’ll walk through the architecture behind Chrome’s on-device models, discuss real-world edge cases and common concerns from integrating the built-in AI APIs, and outline key system and compatibility requirements that every developer should know. This talk will also mention the evolution of Chrome’s AI ecosystem, from its early releases to current capabilities, along with a preview of upcoming features and insights from its developer community.

For advanced listeners in the audience, this talk will include Chrome’s hybrid AI support pairing with Firebase to extend applications with cloud-backed storage and processing, enabling developers to blend on-device intelligence with online workflows.

To keep this talk interactive and practical, I will use my open-source Chrome extension project built during the recently concluded Chrome AI hackathon as a demo, highlighting how the Prompt and Summariser APIs are being used in the Chrome extension.

Don’t let Python developers have all of the fun with LLMs.

This talk is a gentle introduction to Generative AI and Large Language Models for front-end developers looking to build intelligent chatbots and applications. We’ll dive into Langchain.js, an open-source orchestration framework for building AI Applications.

We will start by exploring the basics of Generative AI (GenAI) and Large Language Models (LLMs), how they work, and cover some common pitfalls and how they can be avoided. We’ll take a closer look at vectors, retrievers, and how to build an agent capable of choosing tools to perform specific tasks.

About Adam: Adam Cowley is a dedicated developer with a keen interest in data and graph databases. Serving as the Senior Developer Advocate at Neo4j, Adam produces educational content for GraphAcademy, Neo4j’s free, self-paced, online learning platform. His technical experience spans two decades, developing websites, mobile apps and mixed reality experiences for budding startups to the world’s biggest companies