Creating Offline AI Chatbots Using Gemini

Summary: Have Holy Spirits Bùi initiated a discussion about the challenges and possibilities of developing offline AI chatbots using the Gemini language model. The author sought insights on technical challenges, use cases, and strategies to maintain data relevance offline. Darik Prescott responded, expressing interest in offline AI tools that can update through sporadic internet connections or use mesh networks to ensure data integrity without hallucination. The response suggests a preference for practical AI tools rather than conversational chatbots, emphasizing the importance of memory management in AI development.

AI Summary

As AI technology continues to evolve, one interesting challenge is creating chatbots that can operate offline. With the capabilities of Gemini, a robust language model, there are countless possibilities for development and innovation in this space.

We're inviting you to share your experiences, strategies, and insights into building AI chatbots with Gemini that function effectively without an internet connection.

What are the technical challenges you've faced in building offline AI chatbots, and how have you overcome them?
What use cases have you explored or implemented where an offline chatbot using Gemini is particularly valuable?
How do you ensure the chatbot's data remains updated and relevant, even when offline?
What tools or resources have you found most helpful in the development process?

Let's use this discussion to exchange knowledge and inspire one another to push the boundaries of what offline AI chatbots can achieve.

2 comments

Darik Prescott

9 months, 3 weeks ago

I like this topic a lot, a offline ai that can update itself with random wifi connection or use a mesh network that way it's not so vulnerable but also not hallucinate and keep the memory from discussions be low. I think what people are looking for is ai offline tools, not really a chat bot I would think.

Joaquin Lopez

8 months, 1 week ago

Any kind of AI tool or chatbot running offline, means it's model (LLM) inferences need to be executed in the user local machine. That is a challenge and have limitations:

The size of the model have to be considerable smaller. You can use Gemini Nano, but not the regular Gemini Pro or Ultra, so it's not so powerful.
You have to store the model and some other components locally in your machine, so you need at least 2GB of space and it will use RAM memory and Compute resources on your local machine.
Gemini Nano is more limited than Cloud based ones, Pro/Ultra, though it is efficient for basic tasks.

It have some advantages, like privacy (everything is keep local, no data is shared) and latency (Responses are generated in your own hardware).

You can use Gemini Nano on Chrome browser or with Android devices, like Google Pixel. You can use Google Edge AI Gallery.

If you are offline, you are offline. No external data coming from any connection, on the other hand, the model knowledge is not updated unless you train it again, or use any techniques to fine tune the model, maybe the best option is to use a RAG, or any other knowledge base for the domain content you want the model have access to.