- cross-posted to:
- privacy@programming.dev
- cross-posted to:
- privacy@programming.dev
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
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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-r1:7bThen 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.
My assumption is always the person I am talking to is a normal window user who don’t know what a terminal is. Most of them even freak out when they see “the black box with text on it”. I guess on Lemmy the situation is better. It is just my bad habit.
No worries! You’re probably right that it’s better not to assume, and it’s good of you to provide some different options.
Check out Ollama, it’s probably the easiest way to get started these days. It provides tooling and an api that different chat frontends can connect to.
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.
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.
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I used this a while back, it was pretty straightforward https://github.com/nathanlesage/local-chat
Only if my hardware could support it…
I can actually use locally some smaller models on my 2017 laptop (though I have increased the RAM to 16 GB).
You’d be surprised how mich can be done with how little.
Me when Gemini (aka google) collects more data than anyone else:
Not really shocked, we all know that google sucks
I would hazard a guess that the only reason those others aren’t as high is because they don’t have the same access to data. It’s not that they don’t want to, they simply can’t (yet).
Which is good (for now). Glad I don’t use that shit
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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.
Data from surfshark aka nordvpn lol. Take it with a few chunks of salt
DeepSeek at home: None
How much VRAM does your machine have? Are you using open webui?
Doesn’t the official local app still have telemetry? I might be remembering wrong
You just use the model in an opensource program, not theirs.
How?
Also llama.cpp, kobold.cpp, TabbyAPI, Aphrodite engine. There’s dozens of programs, at least, that run LLMs locally.
There’s programs like Ollama and Lmstudio that let you download LLMs and run them locally
Back in the day, malware makers could only dream of collecting as much data as Gemini does.
And what about goddamn Mistral?
Its French as far as I know so at least it abides to gdpr by default.
All services you see above are provided to EU citizens, which is why they also have to abide by GDPR. GDPR does not disallow the gathering of information. Google, for example, is GDPR compliant, yet they are number 1 on that list. That’s why I would like to know if European companies still try to have a business case with personal data or not.
I have a bridge to sell you if you think grok is collecting the least amount of info.
Ikr XD
Who TF using Grok.
Fascists. Why?
Most of my workforce strangely enough. They claim it’s the best for them in terms of mathematics, but I can’t find that to be a good reason.
I’m interested in seeing how this changes when using duck duck go front end at duck.ai
there’s no login and history is stored locally (probably remotely too)
Or you could use Deepseek’s workaround and run it locally. You know, open source and all.
Is there away to fake all the data they try to collect?
Pretty sure this is what they scrape from your device if you install their app. I dont know how else they would get access to contacts and location and stuff. So yeah you can just run it on a virtual android device and feed it garbage data, but i assume the app or their backend will detect that and throw out your data.
How about if I only use the web version?
Root, install xprivacy (or xprivacylua if your phone isn’t 10 years old).
I just came across this article which for people who are into self hosting can take a look and participate. It’s basically a tool that generating never ending web pages with non sense that load slow (but not too slow the AI tools move on) to slow down and thus cost them more to scrape the internet if enough people are doing it. You can also hide it in a way that legit user would never see this on your site:
https://arstechnica.com/tech-policy/2025/01/ai-haters-build-tarpits-to-trap-and-trick-ai-scrapers-that-ignore-robots-txt/ https://zadzmo.org/code/nepenthes/
Note this is if you use their apps. Not the api. Not through another app.
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.
Am I missing something? What do the numbers mean in relation to the type? Sub types?
