Real-Time Virtual Content Adaptation with AI

In this workshop, we discuss the merits of serverless architecture and how it can be applied to the AI space. We'll explore options around building serverless RAG applications for a more lambda-esque approach to AI. Next, we'll get hands on and build a sample CRUD app that allows you to store information and query it using an LLM with Workers AI, Vectorize, D1, and Cloudflare Workers.

In this workshop, we’ll build a game using the PlayCanvas WebGL engine from start to finish. From development to publishing, we’ll cover the most crucial features such as scripting, UI creation and much more.
Table of the content:- Introduction- Intro to PlayCanvas- What we will be building- Adding a character model and animation- Making the character move with scripts- 'Fake' running- Adding obstacles- Detecting collisions- Adding a score counter- Game over and restarting- Wrap up!- Questions
Workshop levelFamiliarity with game engines and game development aspects is recommended, but not required.

In this workshop we'll take a tour of applied AI from the perspective of front end developers, zooming in on the emerging best practices when it comes to working with LLMs to build great products. This workshop is based on learnings from working with the OpenAI API from its debut last November to build out a working MVP which became PowerModeAI (A customer facing ideation and slide creation tool).
In the workshop they'll be a mix of presentation and hands on exercises to cover topics including:
- GPT fundamentals- Pitfalls of LLMs- Prompt engineering best practices and techniques- Using the playground effectively- Installing and configuring the OpenAI SDK- Approaches to working with the API and prompt management- Implementing the API to build an AI powered customer facing application- Fine tuning and embeddings- Emerging best practice on LLMOps

In this workshop, we’ll build a complete game using the PlayCanvas engine while learning the best practices for project management. From development to publishing, we’ll cover the most crucial features such as asset management, scripting, audio, debugging, and much more.

In this workshop, we'll introduce you to the core concepts of building Mixed Reality experiences with WebXR and Balon.js.
You'll learn the following:- How to add 3D mesh objects and buttons to a scene- How to use procedural textures- How to add actions to objects- How to take advantage of the default Cross Reality (XR) experience- How to add physics to a scene
For the first project in this workshop, you'll create an interactive Mixed Reality experience that'll display basketball player stats to fans and coaches. For the second project in this workshop, you'll create a voice activated WebXR app using Balon.js and Azure Speech-to-Text. You'll then deploy the web app using Static Website Hosting provided Azure Blob Storage.

Have you wanted to explore AI, but didn't want to learn Python to do it? Tensorflow.js lets you use AI and deep learning in javascript – no python required!
We'll take a look at the different tasks AI can help solve, and how to use Tensorflow.js to solve them. You don't need to know any AI to get started - we'll start with the basics, but we'll still be able to see some neat demos, because Tensorflow.js has a bunch of functionality and pre-built models that you can use on the server or in the browser.
After this workshop, you should be able to set up and run pre-built Tensorflow.js models, or begin to write and train your own models on your own data.