It's going to be a huge day. Get a topline view of what's on before you dive in, and learn some tips on how to get the most out of the day's sessions.

Generative AI is supercharging development. Learn how Google Cloud is helping developers smoothly integrate AI into projects by granting easy access to foundation models. Explore game-changing technology from Google DeepMind, and understand the tools, skills, and know-how developers need to build new experiences, accelerate code velocity, and scale AI projects in production.

In the disruptive, dynamic world of startups, innovation is the lifeblood of success, unlocking new opportunities and solutions, and staying one step ahead of the competition. But where does true innovation start? How do you build a culture of innovation? 

In this session, "Igniting the Spark: Strategies for Fostering a Culture of Innovation" Mike Langford, Head of VC & Startup Ecosystem, JAPAC, will explore the power of innovative thinking and its importance for startup success. We'll delve into Google's own innovation strategies; and you'll walk away with 5 actionable steps to transform your startup into a hub of creativity, pushing boundaries, and embracing the possibilities of tomorrow

Join this session to hear Partner perspectives on Generative AI technologies as Laks shares insights on its adoption and potential impact.
Innovation allows us to anticipate market shifts and foster a culture of creativity and continuous improvement.  Assetization involves strategically transforming innovative outputs into tangible assets, driving value creation and revenue generation.  The Accenture Innovation and Asset team actively utilizes a range of technologies, including generative AI, to stay at the forefront of innovation and deliver impactful solutions.   They've been integral members of the Trusted Tester program, forging close collaborations with Google Engineers worldwide across various technologies.  The partnership entails pushing the boundaries to achieve remarkable outcomes and drive innovation to new heights.

In this session you will learn how generative AI will help companies boost productivity, developers code faster, and organisations protect themselves from cyber attacks, along with many other benefits with Googles most capable AI technologies.

Code Completion: Learn how to use generative AI models to complete code snippets, like suggesting function names, variable names, and code blocks.
Code Generation: Learn how to use gen AI models to create code from natural language descriptions.
Code Chat: Learn how to use gen AI models to chat with developers about code; answering questions about code syntax, debugging code, and refactoring code.

In this course, you learn how Duet AI, a generative AI-powered collaborator from Google Cloud, helps you use Google products and services to develop, test, deploy, and manage applications. With help from Duet AI, you learn how to develop and build a web application, fix errors in the application, develop tests, and query data. Using a hands-on lab, you experience how Duet AI improves the software development lifecycle (SDLC).

Catch up with a quick summary of the day so far, and get the live poll results!

A masterclass in working with Conversational AI in Google Cloud. Learn how to:

Function calling lets you use functions as tools in generative AI applications. This feature of Gemini models makes it easier for developers to get structured data outputs from generative models. Developers can then use these outputs to call other APIs and return the relevant response data to the model. TLDR; function calling helps you connect your generative models to external systems so the generated content includes the most up-to-date information.

In this lab, you'll use Data Store Agent functionality in Vertex AI Conversation to build, configure, and deploy a virtual agent that can assist customers who have questions about products and devices in the Google Store, including phones, watches, laptops, smart home devices, and other consumer devices.

Chatbot company, Botnoi Group, is leveraging AI and natural language processing technology to improve the way we live. Using Google Cloud AI technologies, they are developing new tools that can overcome language barriers and make use of their local data, while also helping to build knowledge and skills.  Join this session to hear more about how they are leveraging AI for good, for now and the future.

In this session, Shauna will share how Glean's enterprise search platform helps developers & engineers improve productivity and spend less time outside of code to reduce frustrations with finding information and to ship better code faster.

Got big questions? Throw them to our panel of Google Cloud technical experts to discuss live. 

Demand for Cloud Skills is growing. Discover how you can capitalise with Google Cloud credentials and certifications to help you stand out in the cloud industry.

This was just the beginning - what are the next steps of your learning journey?

We're kicking off day two with a brief introduction before we dive into the day's learnings. Get a topline view of what's on before you dive in, and learn some tips on how to get the most out of the day's sessions. 

What are embeddings, and why are they useful? In this session, we'll discuss the different types of embeddings, how they're created and the many benefits of using them - such as their ability to reduce dimensionality, capture semantic relationships, and improve the performance of machine learning models. We'll then take a look at using embeddings with vector databases, and discuss some of the most common applications of embeddings, such as similarity search and retrieval augmented generation.

LLMs are only as good as the data you feed them. But to get the best data - and to build a production quality RAG system - you need the best search technology. This session will look at how Google's Search technology can empower LLMs with its production quality hybrid search, document processing and reranking algorithms, all to help you get the most out of your data.

Vector Search can search from billions of semantically similar or semantically related items. A vector similarity-matching service has many use cases such as implementing recommendation engines, search engines, chatbots, and text classification. In this session we will guide you through tasks involved in the Google Cloud Skills Boost Lab 'Getting Started with Vector Search and Embeddings' where you can learn how to use Vertex AI Embeddings for text to create text embeddings and use them to create a vector search index.

Utilizing GenAI to solve problems has become a new trend in the Travel industry.  KKday recently developed a smart agent for customer service, helping their team to rapidly find answers to customers' questions.  However, by continuing to improve data quality, KKday sees the opportunity for better performance, not just in smart agents, but across all AI Applications.  
Join this session to learn how KKday is using GenAI and supervised learning algorithms to build a Smart Tagging project to further build and leverage high quality data. The anticipated outcomes of this project for KKday are:

Generative AI increases the need for API Management and API Security. APIs are the contract for machine-led creation and consumption. 
Discover how APIs can enable enterprises to make generative AI the core driver for improved customer experiences, radical productivity, and unlocking the value of data.

Catch up with a quick summary of the day so far, and get the live poll results!

Get up close and personal with generative AI on Google Cloud, a technology that allows you to create your own gen AI applications. This session will cover the basics of generative AI, prompt design, and various prompting techniques. We'll explore both text-based and multimodal use cases, and get hands-on working with Gemini Pro and Gemini Pro Vision models through the Vertex AI Gemini API. You'll leave the session with better insights on how gen AI can be used to build innovative applications that can process information across text, code, images, and video with Gemini models on Google Cloud.

RAG typically uses external data sources only based on text. With Gemini Pro Vision and multimodal embeddings, you can now perform multimodal RAG on text and images. Get hands-on as we teach you to perform multimodal RAG on a financial document that contains both text and images (charts, diagrams).

Don't miss this practical session teaching how to get started with OSS Models on Vertex AI, apply tuning, and deploy the model to online serving endpoints. We step through an end-to-end journey with LLaMa2 and show you how to tune it with your own data, then deploy it in production using Vertex AI. 

Got big questions? Throw them to our panel of Google Cloud technical experts to discuss live.

For retail companies, recommendation systems improve customer experience and thus can increase sales. In this lab, you will learn how to use the Gemini Pro Vision model to rapidly create a multimodal recommendation system. The Gemini Pro Vision model can provide both recommendations and explanations using a multimodal model.

In this lab, you will begin with a scene (e.g. a living room) and use the Gemini Pro Vision model to perform visual understanding. You will also investigate how the Gemini Pro Vision model can be used to recommend an item (e.g. a chair) from a list of furniture items as input.

This was just the beginning - what are the next steps of your learning journey?