Intro to Generative AI: A Recap of the Online Study Series 🤖✨

This blog post summarizes the key takeaways from the first session, “Intro to Generative AI,” of the “Build with AI on Google Cloud” online study series. This collaborative event was hosted by GDG Seattle 🇺🇸, GDG Surrey 🇨🇦, and GDG Vancouver 🇨🇦.

You can watch the full session here: Link to YouTube Video 🎬

Introductions to GDG Chapters 👋

• GDG Seattle: Margaret, an organizer since 2015, shared photos from past events and provided a LinkedIn QR code. 🖼️
• GDG Surrey: Preeti highlighted their focus on developer education and hands-on learning, including machine learning paper reading and writing clubs. 📚💡
• GDG Vancouver: Santos introduced their community as a vibrant group of developers, tech enthusiasts, and students. 🌟🧑‍💻

Study Series Overview 🗓️

The series consisted of five sessions focused on generative AI. It was inspired by a successful collaboration between GDG Seattle and GDG Surrey on a machine learning engineer certification series. The generative AI learning paths on Google Cloud Skills Boost were reorganized into four paths for developers, data scientists/analysts, and ML engineers. The five generative AI paths on Google Cloud Skills Boost included:

1. Beginner Intro to GenAI 🌱
2. Generate Smart GenAI Outputs 🧠💡
3. Build and Monetize Apps with GenAI 🛠️💰
4. Integrate GenAI into Your Data Flow ⚙️➡️
5. Deploy and Managing Models 🚀☁️

Each session featured two short talks by Googlers or community experts, followed by discussions and Q&A. 🗣️❓

Cloud Skills Boost Walkthrough ☁️🚀

A learning path on Cloud Skills Boost included multiple courses, each with videos, recommended readings, quizzes, and hands-on labs. Attendees were encouraged to sign up at [Cloud Skills Boost](Cloud Skills Boost.google) and RSVP to the event for free access. Labs on Cloud Skills Boost allowed users to run Google Cloud resources in a simulated environment using a student IDs and passwords. 💻🔑

Beginner Intro to GenAI Learning Path 🚦

This path comprised five courses:

• Intro to GenAI (45 minutes) ⏱️
• Intro to LLM (1 hour) 🕰️
• Intro to Responsible AI (30 minutes) ✅
• Prompt Design (Vertex AI, 3 hours 45 minutes) ✍️🎨
• Responsible AI: Apply AI Principles with Google Cloud (2 hours) 🛡️

These times indicated the total estimated time for videos, readings, quizzes, and hands-on labs.

Intro to GenAI Short Talk 💡🗣️

Margaret clarified the distinctions between AI 🤖, machine learning ⚙️, deep learning <0xF0><0x9F><0xA7><0xAB>, and generative AI ✨. She explained that generative AI creates new content using generative models, often multimodal. She also discussed Large Language Models (LLMs) as sophisticated autocomplete systems. Margaret highlighted the evolution of generative models in the vision domain, from GANs to diffusion models and diffusion transformers. 🖼️➡️🎨

Prompt Design Short Talk ✍️💡

Preeti defined prompt design as the art of asking AI the right way to get the best answers. She outlined a prompt design workflow:

1. Clarify the purpose of the prompt. 🤔
2. Create the prompt content structure and components. 🏗️
3. Test the prompt. 🧪
4. Identify areas for improvement. 🔍⬆️
5. Iterate and refine. 🔄✨

She emphasized specifying the desired output format and mentioned common pitfalls in prompt design. Preeti also briefly mentioned parameters like “temperature” 🔥, “top K,” and “top P” for controlling creativity and precision in AI outputs. 🌡️🎯

Vertex AI Demo for Prompt Design 💻✨

Preeti demonstrated how to navigate Google Cloud Skills Boost and the Vertex AI platform, highlighting options for adding system instructions, user prompts, images, and examples. She illustrated adjusting the “temperature” parameter 🔥 and mentioned advanced options like “top K” and “top P.” 🛠️

Conclusion 🎉

The session concluded by encouraging attendees to join the GDG Surrey Discord server for questions and to continue working through the “Beginner GenAI path” on Google Cloud Skills Boost. 💬🚀