Build AI apps using Gemini [Workshop] | Hack This Fall 2024 Virtual ?

Introduction

Hello everyone and good morning! I hope you are having a fantastic and productive hackathon experience. As we embark on Day Two of our hackathon with nearly 24 hours left for hacking, I want to take a moment to check in. Please feel free to share in the chat how everything is going for you and how your past 12 hours of hacking have been.

As we hope for everyone to stay hydrated and avoid burnout, we’re excited to bring you an insightful workshop today. Anubhab Singh, a Google Developer Expert, joins us to share valuable insights on building AI applications using Gemini.

Insights from Anubhab Singh

Workshop Overview

To kick things off, Anubhab emphasized that our focus today will be on practical tips for building innovative applications, rather than diving deep into machine learning theory. With numerous innovative projects emerging, he encourages participants to utilize the tools and technology that can give their projects an edge in this competitive hackathon.

Getting Started

Anubhab highlighted two significant features of Gemini that developers should consider:

Long Context: Gemini offers more than 2 million context tokens, a groundbreaking feature compared to other LLMs (Large Language Models). This means developers can work with massive amounts of data, including extensive text documents, entire code bases, or even lengthy chat histories, all in one prompt.
Grounding: This recently released feature enhances the model’s capabilities by allowing it to fetch up-to-date information directly from Google Search, minimizing issues related to hallucinations or outdated knowledge.

Practical Demonstration

Using AI Studio, Anubhab demonstrated how to leverage long context by processing lengthy legal documents effectively. The AI was able to summarize complex cases and extract specific information with high accuracy, showcasing Gemini's benefits for real-world applications.

He also touched on utilizing grounding to access current information, such as sports events, directly integrating Google search results.

Through these demonstrations, Anubhab made it clear that while long context simplifies processing large amounts of data, grounding allows developers to supplement their applications with real-time information for more reliable outputs.

Development Tips

To wrap up the session, Anubhab shared a crucial tip: ensure that AI is a facilitator in your application rather than the entire solution. It’s essential to balance the AI component with robust traditional algorithms or rule-based systems to create well-rounded applications.

Conclusion

Thank you for joining us for this enlightening session. We encourage all participants to engage with the tools and resources shared during the workshop and to continue exploring how to leverage Gemini effectively for their hackathon projects.

Stay tuned for more sessions, and don't hesitate to reach out to Anubhab on Discord for any further questions related to AI or Gmail technologies.

Keywords

Gemini
AI apps
Long context
Grounding
Hackathon
AI Studio
Google Search
Real-time information
Machine Learning

FAQ

What is Gemini? Gemini is Google’s primary model designed to compete in the realm of LLMs, offering features such as long context and grounding.

How many context tokens does Gemini support? Gemini currently supports over 2 million context tokens, allowing for the processing of extensive documents and data.

What is grounding in the context of AI? Grounding is a feature that integrates real-time data from Google Search into the model's responses, allowing for accurate and current information retrieval.

How can I use AI Studio? AI Studio provides a platform for testing different AI models, including Gemini. Developers can create free API keys, run experiments, and access the technology without any initial costs.

What is the main takeaway for building with Gemini? AI should be utilized as a supportive tool within your application rather than the sole functionality. Traditional algorithms should still play a significant role in facilitating your app's features.