We have been seeing amazing progress in generative AI and LLM recently. Thanks to the open-source efforts like LLaMA, Alpaca, Vicuna, and NAME_1, we can now see an exciting future of building our own open-source language models and personal AI assistant.

These models are usually big and compute-heavy. To build a chat service, we will need a large cluster to run an inference server, while clients send requests to servers and retrieve the inference output. We also usually have to run on a specific type of GPUs where popular deep-learning frameworks are readily available.

This project is our step to bring more diversity to the ecosystem. Specifically, can we simply bake LLMs directly into the client side and directly run them inside a browser? If that can be realized, we could offer support for client personal AI models with the benefit of cost reduction, enhancement for personalization, and privacy protection. The client side is getting pretty powerful.

Won’t it be even more amazing if we can simply open up a browser and directly bring AI natively to your browser tab? There is some level of readiness in the ecosystem. WebGPU has just shipped and enables native GPU executions on the browser.

Still, there are big hurdles to cross, to name a few:

We need to bring the models somewhere without the relevant GPU-accelerated Python frameworks.
Most of the AI frameworks rely heavily on optimized computed libraries that are maintained by hardware vendors. We need to start from scratch.
Careful planning of memory usage,