rshemet

5 ms·

31.
by rshemet 1y ago
The models themselves live in an isolated sandbox. On top of that, each mobile app has its own sandbox - isolated from the phone's data or tools. Both the model and the app only have access to the tools or data that you choose to give
32.
by rshemet 1y ago
you can plug in a vector DB and run Cactus embeddings for retrieval. Assuming you're using React Native, here's an example: https://github.com/cactus-compute/cactus/tree/main/react#emb... (Flut
33.
by rshemet 1y ago
great stuff. (good timing for a post given all the comet news too :) ) DM me on BF - let's talk!
34.
by rshemet 1y ago
appreciate the feedback! Made the demo links more prominent on the README. Some Android models won't support GPU hardware; we'll be addressing that as we move to our own kernels. The app itself is just a demonstration of Cactus pe
35.
by rshemet 1y ago
Thank you! it goes without saying that the field is rapidly developing, so the use cases range from private AI assistant/companion apps to internet connectivity-independent copilots to powering private wearables, etc. We're curre
36.
by rshemet 1y ago
Cactus is a framework - not the app itself. If you're looking for an Android demo, you can go to https://play.google.com/store/apps/details?id=com.rshemetsub... Otherwise, it's easy to build any of the e
37.
by rshemet 1y ago
didn't Ollama vendor Llama cpp too? Most projects typically start with llama.cpp and then move away to proprietary kernels
38.
by rshemet 1y ago
Interesting to think about the concept of local-first in the age of AI. Wanting to be able to run AI fully privately, and offline is the reason we created Cactus: https://github.com/cactus-compute/cactus Fully open-sou
39.
by rshemet 1y ago
hey! we're building Cactus ( https://github.com/cactus-compute ), effectively Ollama for smartphones. I'd love to learn more about your MCP implementation. Wanna chat?