Build an AI/ML-enhanced image processing enterprise workflow

Combining file backup ("boring") with analyzing images using AI/ML ("exciting") probably isn't a workflow you think about often. However, by combining them together, you can build a useful enterprise solution (or be inspired as to what else is possible). Google provides a diverse array of developer tools you can use to realize this ambition, in this case, a set of APIs from two diverse product groups: Google Workspace (formerly G Suite and Google Apps) and Google Cloud (GCP). More compellingly, the basic principle of mixing-and-matching Google technologies as the "right tool for the job" can be applied to many other challenges faced by your organization or your customers.

Industries like manufacturing, architecture, media, and advertising are four industries generating an enormous number of images per project. Over time, this can clutter up anyone's corporate Google Drive. After the conclusion of a project or campaign, it's much less likely a user will be accessing those files often in the future. In this session, attendees will hear about a sample app (Python) using four APIs from GCP & GWS to accomplish the goal of backing up those images, to clear them from Google Drive, analyzing their contents, and generating an inventory of the file names, types, sizes, contents, and archived location, all in a single spreadsheet. Join us to learn how to "stitch" together this compelling solution using REST APIs from Google.

Easy path to machine learning

In today's world of ChatGPT & machine learning, {data scientists & developers are creating insightful tools,insightful tools are being created} like never before. However, not everyone has the requisite skills or background to jump right into building & training GenAI or other ML models in PyTorch or TensorFlow. This overview helps democratize AI/ML for all developers, introducing concepts and the standard workflow. If you're new to this exciting topic, Google Cloud AI/ML "building block" APIs, part of its Vertex AI platform, are some of the best ways to get started. What does it mean for developers? It means that if you can call an API, you can leverage the power of machine learning.

This session provides a basic ML primer for those who are new, giving examples of where AI & ML are making an impact today, whether in a Google product or out in the wild. That's followed by an introduction to Google APIs and how to use them, focusing on the GCP AI/ML building block APIs but also including other Google APIs to consider when building your first AI/ML application. Real code will show you how much easier it will be for you to get started on your AI/ML journey!

Powerful Google developer tools for immediate impact!

Are you a professional developer or student new to Google developer tools? You may know Google for search, YouTube, Android, Chrome, and Gmail, but did you know Google has many programmer resources like compute & storage services, networking & security, APIs, AI/ML tools, and hosting platforms? This session introduces you to some of the most impactful services with the purpose of inspiring what you can accomplish in a short amount of time. They are great for work projects on your plate or for student coursework or hackathons.

Highlights include where to run your apps in the cloud without managing VMs (serverless), different types of databases to store your data, "building block" AI/ML APIs to help get you started even if you have little or no experience with machine learning, and general-purpose Google APIs giving you access to resources like spreadsheets, big data analysis tools, and so on. The session concludes with a variety of applications demonstrating the versatility and usefulness of Google APIs to show you what is possible. Join us to discover how Google can help you write your next awesome app!

Running your Gen AI apps on Serverless computing

You've built the next hot gen AI app and have it running great on internal servers. How do you get that out to the world? Cloud optimization and app modernization go hand-in-hand. It is all about taking on-prem apps, getting them containerized, running on VMs, perhaps orchestrating with Kubernetes, and eventually into the cloud. Once you're far enough down this path, you'll come across serverless. What exactly is serverless? It's one of the fastest growing segments in cloud allowing developers to focus on what they're building instead of what it runs on. That said, while serverless is a viable modernization solution for many applications, there are some use cases where it may not be the best option. Hear about those scenarios as well.

This session begins with a review of cloud service levels then looks specifically at serverless compute platforms. Whether it's web apps, functions/microservices, mobile backends, containers, or a customized business automation & extension platform, Google has a tool for your needs. Attendees will see how to deploy & run code using the Gemini API on each. Code samples will be in Python & JavaScript, but many other languages are supported. Whether you're a software engineer, student/researcher, data scientist/analyst, or DevOps/IT staff, you'll know how to host & run gen AI code or almost any app on Google's cloud and become part of the next-generation cloud-ready workforce.

BENEFIT TO DEVELOPERS/AUDIENCE TAKEAWAYS
- Become familiar with what serverless is and its corner of the cloud computing industry
- Learn about the serverless compute platforms available from Google and other cloud vendors
- Get a good idea of the similarities and differences between these platforms
- Discover how to deploy application code to one or more of these platforms

PREREQUISITES
* General knowledge of gen AI (Gemini, ChatGPT, etc.), web apps, app hosting, cloud computing, etc.
* You're a developer, technical consultant, software engineer, DevOps/SysAdmin/IT staff, systems analyst, etc.
* Basic working skills in Python and/or JavaScript
* Some experience working with serverless, e.g., Lambda, may be beneficial but not required

TAGS
Google, Google Cloud, serverless, serverless computing, cloud computing, Google App Engine, App Engine, Google Cloud Functions, Cloud Functions, Google Cloud Run, Cloud Run, Python, JavaScript, Node.js, PHP, Java, Go, Ruby, C#, .NET, C++, Rust, Kotlin, APIs, API, Google APIs, PaaS, IaaS, SaaS, Google Workspace, GWS, Google Apps Script, Google Cloud Platform, GCP, cloud, Google APIs, REST, software, programming, applications, development, developer, HTTP, containers, container, Docker, Cloud Buildpacks, Buildpacks, CNCF, cloud-native, standard, web apps, mobile, mobile backends, Gemini, AI, ML, AI/ML, generative AI, genAI

Why are using Google APIs so confusing?

If you've ever tried to use Google APIs, you'll discover they can vary wildly. Not only do they operate differently from each other, you'll find that the security mechanism for one will likely differ for another. Even if you're using the same programming language, client library usage can vary greatly between product groups like Google Cloud (GCP), Firebase, Google Workspace (GWS; e.g., Gmail, Google Drive, Calendar, Docs, Sheets, Slides, etc.), YouTube, Google Maps (GMP), Google AI/Gemini, etc. This session attempts to corral all the different options available to developers by providing an overview of the differing API product families, the various accepted types of API credentials, e.g., API keys, OAuth client IDs, service accounts, which APIs are free (and which aren't), and how to finally use Google APIs the way you need in order to solve problems for your organization or your customers'.

The speaker is not a representative of Google but does have over a dozen years of experience on various Google API product teams and is well-known in the Python and Google developer communities. As an APIs-focused freelance consultant, their primary objective of helping the developer industry get over the obvious hurdles is key, so this session isn't so much focused on the technology, but rather, aims to remove confusion in the marketplace in order for developers to move forward with solutions rather than getting roadblocked by Google's API usage inconsistencies and confusion. The goal is for the audience to become knowledgeable about the Google developer ecosystem so they can make informed decisions on the right solutions for their needs, regardless of whether they choose to use Google developer tools or not.

PREREQUISITES
- Experience using Google APIs is helpful but required
- Basic API usage from Python or Node.js/JavaScript
- Some understanding of API security & credentials

OBJECTIVES/TAKEAWAYS
- Learn about the Google APIs ecosystem
- Gain familiarity with different Google API product families
- Get an understanding of Google APIs security mechanisms & credentials types
- See actual short code samples demonstrating Google API usage

From 0 to Google APIs: Beyond search & AI... leverage all of Google

Google is more than search & AI. As end-users, we all have powerful tools at our fingertips to help us be more efficient in work & life. But beyond messaging, social media, calendaring, mapping, web search, and AI chat tools, the real opportunity is where innovative companies make their technologies available to developers via the magic of APIs, and Google is no exception. It provides APIs for Google Translate, Maps, Drive, YouTube, Sheets, Gmail, and Gemini, to name a few, and don't forget the multitude of Cloud services from GCP also available via API. That's the good news, but using Google APIs isn't without its challenges.

There are various client libraries and different types of credentials. Which do you use with which APIs, how do you know what's supported, and why do Google APIs feel inconsistent from each other? Join tech consultant & ex-Googler Wesley Chun who pulls back the wizard's curtain to show how to use numerous Google APIs and leave with the knowledge to start using at least one Google API on your next project. If you've attended any of his AI/ML or developer tools sessions in the past, this deeper dive is what you need to get started today. By access Google technologies via API, developers can build new & unique solutions for their organization or their customers by leveraging some of Google's well-known & desired features.

[GDG organizers: this session can also be paired with a hands-on workshop]

PREREQUISITES/PRE-WORK
This session is for developers interested in using Google APIs. Attendees should have basic knowledge of Python or Node.js. Experience accessing Google APIs may be helpful but is not required.

LEARNING OBJECTIVES (What will attendees get out of your talk? When they leave the room, what will they know that they didn't know before?)
After this session, attendees will have a better understanding of how to use Google APIs, what the different credentials types are, what client libraries are and which ones to use, understand the difference between simple vs. authorized API access, and have seen working Python or Node.js/JavaScript code accesssing Google APIs.

TAGS
Google, API, APIs, Google APIs, client libraries, simple, authorized, authentication, authorization, OAuth2, REST, HTTP, API keys, OAuth client IDs, service accounts, GCP, Google Cloud Platform, Vision, Natural Language, BigQuery, Workspace, Drive, Docs, Sheets, Slides, Apps Script, Maps, YouTube, Python, Node.js, JavaScript, server-side, .NET, C#, Objective-C, Swift, PHP, Java, Dart, Go, Ruby, cloud, open source, web, mobile, apps, programming, development, developers, AI, ML, AI/ML, Gemini, SDK, SDKs

Deploy GenAI web apps without VMs or servers!

You've built the next hot gen AI app and have it running great on your laptop or internal server. How do you get that out to the world? Servers, right? Many times yes, but modern app development also includes serverless. What exactly is serverless? It's one of the fastest growing segments in cloud allowing developers to focus on what they're building instead of what it runs on. It is also sustainable: By choosing serverless, your app only runs when it has users whereas with a VM or server, it's up 24x7, meaning you're billed all the time. Who wants that?

This session begins with a brief review of a previous session on Serverless computing with Google Cloud, most recently delivered at the I/O Extended event in Jul 2024. If you missed this session, check out an previous recording (https://youtu.be/F3drg0HJDHw) as this workshop provides a hands-on follow-up where you get experience and build muscle-memory deploying a simple genAI web app to GCP serverless platforms.

The sample app is available in Python & JavaScript, so pick one that works best for you, or port to your favorite dev tool. The bottom-line: Whether you're a software engineer, student, researcher, data scientist, or DevOps/IT staff, you'll know how to host & run your apps (GenAI & otherwise) on Google's cloud without servers and become part of the next-generation cloud-ready workforce.

BENEFIT TO DEVELOPERS/AUDIENCE TAKEAWAYS
- Get an overview of what serverless is and its corner of cloud computing
- Learn about serverless compute platforms from Google Cloud (or other vendors/CSPs)
- Discover how to deploy GenAI and other apps to one or more of these platforms

PREREQUISITES
- General awareness of GenAI (Gemini, ChatGPT, etc.), web apps or mobile backends, API-/app-hosting, cloud computing, etc.
- Basic working skills in Python and/or Node.js
- Some experience with serverless, e.g., Lambda, may be beneficial but not required

TAGS
Google, Google Cloud, serverless, serverless computing, cloud computing, Google App Engine, App Engine, Google Cloud Functions, Cloud Functions, Google Cloud Run, Cloud Run, Python, JavaScript, Node.js, TypeScript, Google Cloud Run Functions, Cloud Run Functions, PHP, Java, Go, Ruby, C#, .NET, C++, Rust, Kotlin, APIs, API, Google APIs, PaaS, IaaS, SaaS, Google Cloud Platform, GCP, cloud, Google APIs, software, programming, applications, cloud-native, web apps, mobile backends, Gemini, Gemini API, Google AI, GCP Vertex AI, Vertex AI, AI, ML, AI/ML, generative AI, genAI, development, developer, HTTP, containers, container, Docker, Cloud Buildpacks, Buildpacks, CNCF