A chart titled “What Kind of Data Do AI Chatbots Collect?” lists and compares seven AI chatbots—Gemini, Claude, CoPilot, Deepseek, ChatGPT, Perplexity, and Grok—based on the types and number of data points they collect as of February 2025. The categories of data include: Contact Info, Location, Contacts, User Content, History, Identifiers, Diagnostics, Usage Data, Purchases, Other Data.
- Gemini: Collects all 10 data types; highest total at 22 data points
- Claude: Collects 7 types; 13 data points
- CoPilot: Collects 7 types; 12 data points
- Deepseek: Collects 6 types; 11 data points
- ChatGPT: Collects 6 types; 10 data points
- Perplexity: Collects 6 types; 10 data points
- Grok: Collects 4 types; 7 data points
Who would have guessed that the advertising company collects a lot of data
And I can’t possibly imagine that Grok actually collects less than ChatGPT.
Locally run AI: 0
Are there tutorials on how to do this? Should it be set up on a server on my local network??? How hard is it to set up? I have so many questions.
If by more learning you mean learning
ollama run deepseek-r1:7b
Then yeah, it’s a pretty steep curve!
If you’re a developer then you can also search “$MyFavDevEnv use local ai ollama” to find guides on setting up. I’m using Continue extension for VS Codium (or Code) but there’s easy to use modules for Vim and Emacs and probably everything else as well.
The main problem is leveling your expectations. The full Deepseek is a 671b (that’s billions of parameters) and the model weights (the thing you download when you pull an AI) are 404GB in size. You need so much RAM available to run one of those.
They make distilled models though, which are much smaller but still useful. The 14b is 9GB and runs fine with only 16GB of ram. They obviously aren’t as impressive as the cloud hosted big versions though.
If you want to start playing around immediately, try Alpaca if Linux, LMStudio if Windows. See if it works for you, then move from there.
Alpaca actually runs its own Ollama instance.
I used this a while back, it was pretty straightforward https://github.com/nathanlesage/local-chat
https://ollama.ai/, this is what I’ve been using for over a year now, new models come out regularly and you just “ollama pull <model ID>” and then it’s available to run locally. Then you can use docker to run https://www.openwebui.com/ locally, giving it a ChatGPT-style interface (but even better and more configurable and you can run prompts against any number of models you select at once.)
All free and available to everyone.
Back in the day, malware makers could only dream of collecting as much data as Gemini does.
I’m curious what data t3chat collects. They support all the models and I’m pretty sure they use Sentry and Stripe, but beyond that, who knows?
Anthropic and OpenAPI both have options that let you use their API without training the system on your data (not sure if the others do as well), so if t3chat is simply using the API it may be that they themselves are collecting your inputs (or not, you’d have to check the TOS), but maybe their backend model providers are not. Or, who knows, they could all be lying too.
I have a bridge to sell you if you think grok is collecting the least amount of info.
