• 8 Posts
  • 883 Comments
Joined 1 year ago
cake
Cake day: December 13th, 2024

help-circle
  • I mean, I get that, but why is Proton offering one? What value do I get from Proton’s LLM that I wouldn’t get from any other company’s LLM? It’s not privacy, because it’s not end to end encrypted. It’s not features, because it’s just a fine tuned version of the free Mistral model (from what I can tell). It’s not integration (thank goodness), because they don’t have access to your data to integrate it with (according to their privacy policy).

    I kind of just hate the idea that every tech company is offering an LLM service now. Proton is an email and VPN company. Those things make sense. The calendar and drive stuff too. They have actual selling points that differentiate them from other offerings. But investing engineering time and talent into yet another LLM, especially one that’s worse than the competition, just seems like a waste to me. And especially since it’s not something that fits into their other product offerings.

    It truly seems like they just wanted to have something AI related so they wouldn’t be “left behind” in case the hype wasn’t a bubble. I don’t like it when companies do that. It makes me think they don’t really have a clear direction.

    Edit: it looks like they use several models, not just one:

    Lumo is powered by open-source large language models (LLMs) which have been optimized by Proton to give you the best answer based on the model most capable of dealing with your request. The models we’re using currently are Nemo, OpenHands 32B, OLMO 2 32B, GPT-OSS 120B, Qwen, Ernie 4.5 VL 28B, Apertus, and Kimi K2.

    - https://proton.me/support/lumo-privacy

    I have a laptop with 48GB of VRAM (a Framework with integrated Radeon graphics) that can run all of those models locally, so Proton offers even less value for someone in my position.





  • I meant I run it.

    But to answer your question, it uses subaddressing really well. When you give your email to a company, you add a label to the address just for that company, then all of their emails go in that label. You can easily toggle things like notifications, mark as read, and show in aggbox (our version of the inbox, since there isn’t really an inbox when everything is sorted already). Then if that company leaks your email, you can block that label.

    You can also set up screening labels that are meant for real people, then any new senders get screened to make sure they’re human before you get their mail.







  • I’m rewriting how my ORM, Nymph.js handles access controls. Right now, it stores the access control vars (user, group, permissions) in the same table as all of the other data, which makes the full text search slow because it has to join the tables multiple times. I’m moving those access controls into the entity tables where all the joins start from, so a simple index can handle that before it even joins the FTS tokens table.

    The hard part is going to be migrating existing data in my email service that uses Nymph. It’ll be multiple steps: create the new columns, make sure new entities add that data to both the new columns and the old way, migrate all entities to have the data in both, update the queries to use the new columns and stop storing data the old way, then delete all the old data. It’ll be the opposite of fun, but hopefully once I’m done it’ll be way faster.