Privacy

In our previous post, Mobile On-device AI: Smarter Faster Private Apps, we explored the fundamentals of running AI locally on mobile devices. Now, it’s time to get hands-on and see this technology in action!

This practical guide walks you through implementing mobile on-device AI using Google’s powerful Gemma model family, including the cutting-edge Gemma 3n. You’ll learn to deploy these models across iOS, Android, and web platforms using industry-standard frameworks.

What You’ll Learn Here

• Test various Gemma models, including Gemma 3n, in Google AI Studio.
• Run sample on-device AI applications on Android using tools like the Google AI Edge Gallery App and MediaPipe.
• Implement on-device Large Language Model (LLM) inference on iOS using MediaPipe.
• Explore how to run LLMs in mobile web browsers with JavaScript and MediaPipe.
• Gain practical experience deploying and interacting with Gemma models across different mobile platforms.

Prerequisites: Basic mobile development knowledge helpful but not required.

I stopped using Chrome a long time ago due to privacy concerns, and I’ve been switching between Firefox, Edge, and occasionally Brave. But I never spent the time to fully compare these browsers and analyze which one best suits my needs. Today, I decided to look deeply into these browsers and ended up going down a rabbit hole of researching their privacy features.

Why is this important? Every time we browse a website, we are sharing bits of our digital life with companies we don’t know. These companies collect vast amounts of data about our browsing habits, preferences, and personal information. It is so cringy and annoying to see YouTube showing a ‘suggested video’ of the dental procedure that you searched about and are planning to get done. The browser you choose plays a significant role in how much of your data is collected and shared.