# Privacy AI Is Possible

Because of privacy concerns, I have been reluctant to use LLMs. I started experimenting in 2023 because I realized this is going to come either way - and I can make use of it, or be left behind.

## Power

I started with ChatGPT, as everyone does, but soon stopped using it for political and privacy reasons. Sam Altman, founder of OpenAI, is also a co-founder of the Worldcoin project. Worldcoin is a cryptocurrency that requires individuals to scan their iris to identify themselves. They have been rolling out their product aggressively on the African continent by paying anyone who signed up $25 in exchange for their biometric data. In Kenya, Worldcoin became the subject of a 2025 court case and was rightfully instructed to delete all data.

I don’t want to share my data with companies showing no regard for dignity and privacy, and taking advantage of unequal bargaining situations.

So no ChatGPT for me.

## Agency

Claude was the first tool I used on a regular basis. Since I understood that if you use the free plan on ChatGPT your conversations might end up in Google Search - and this might be the same with other models - I decided to subscribe to a paid plan on Claude.

I am using it with a nym (a fake name and email), but of course my payment data is still associated with my account. That’s why I was looking for more private options.

The point for me is simple: I want to use AI, but I want to choose the terms. I don’t want “convenience” to mean “total surveillance.”

## Tools

### PayPerQ offers Bitcoin payments

nostr:npub16g4umvwj2pduqc8kt2rv6heq2vhvtulyrsr2a20d4suldwnkl4hquekv4h allows you to pay with Lightning Bitcoin, which increases your privacy because your real name is not associated with your searches. It offers a variety of LLMs for chat, image, video, audio, and DeepResearch, which makes it easy to experiment. At the same time, it increases the number of my experiments, because I want to know what different models produce and what is best.

I think it is essential to find out which tools are the right ones for your needs. Honestly, I haven’t found mine yet.

I like Claude Sonnet 4.5 for editing texts. DeepResearch is incredible for doing what its name says, although the depth of results can be overwhelming. Z.AI: GLM 4.7 was great for strategic thinking, but then it failed my expectations in text editing.

PayPerQ hides your identity in the purchasing process, but your prompts and conversations still land at the companies behind the models. I am not against them learning what I ask or the corrections I make - AI makes a lot of mistakes and it has a lot to learn from us. I actually want LLMs to crawl my work, but I don’t want them to save every little thing I do and mix it up with my private questions.

### Maple AI: privacy from sign-up to LLMs

nostr:npub10hpcheepez0fl5uz6yj4taz659l0ag7gn6gnpjquxg84kn6yqeksxkdxkr is the best solution I found. It runs on open source code and open models. It says it never uses your data to train AI, doesn’t log your chats, does zero data retention, and you can pay with Bitcoin. It offers many models (including OpenAI GPT-OSS — yes, OpenAI, but in a private way).

Maple AI states that communications are encrypted locally on your device before being transmitted, that their servers can’t read your data, and that even during processing the pipeline is designed with privacy as the priority.

I want AI as a tool, not as a trap.

#Daily #AI

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Discussion

You can also run local models via Ollama

You can, if you can, but not everyone can.

Doe you have experience with any model in particular & can recommend it? I‘m looking for a general-purpose chatbot. And is there a way to train the local model on additional data?

gpt-oss:20b if you can run it, it's pretty good

You would use a RAG for augmenting the local model, I'll experiment with that soon

Thx for your reply! 20B is a bit high for my current experimenting laptop, but I‘ll check it out asap once I‘ve upgraded my HW.

Would be interested to hear about your experience & results with augmenting the model. Pls share if possible 🙏🏼

Holy fuck lol

No wonder zuck likes Altman

Ollama is likely the most private option, since everything runs locally on your computer. However, it does require a decent amount of VRAM to perform well. If you prefer a cloud‑based solution, have you tried Lumo? It’s a service from Proton (the email provider) and you can access it with any Proton account, even a free one. I use it occasionally, and the results are consistently solid.

There’s also Lumo from Proton, the privacy‑focused email provider. You can try it as a guest or log in with a Proton account. Conversations are never used for training and remain private. I use it occasionally, and the results are consistently solid.

Try Confer. Purpose built for privacy by Moxi - the builder/founder of Signal. The best option for private AI use that is available now.

https://confer.to

#AI

Thanks, didn’t know that one.

You mean signal, that gov-sponsored project that receives ten of million USD each year from the CIA because of "reasons"?

Thanks, but no thanks.

I'd take a look at running a model locally, like with using Ollama and something like AnythingLLM.

Absolutely! It's awesome to see people prioritizing privacy while embracing AI. Finding the right tools that respect our data and dignity is key! Keep exploring—there are great options out there! 🌟🤖 #PrivacyFirst #AI

Also been experimenting and feeling urgency to unplug by the ones I've been using for those same reasons. Been wanting to give MapleAI a go. Last year tried PPQai but found both chatgpt and Claude being dumber there than my experience on their own platforms for whatever reason.

I think it's really hard to test them all and to decide which ones to use. But I think these 2 are good too. Just heard of confer.to from Signal cofounder Moxie. Another one to test.

I am gonna try that one out too. Maybe we can compare notes.

I like PPQai to see what it comes up with, but I agree with you fully - it’s Claude and ChatGPT aren’t anywhe near the real ones. But I do like Perplexity.

Don't forget #ShakespeareDIY for programming.

I like nostr:nprofile1qqs8msutuusu385l6wpdzf2473d2zlh750yfayfseqwryr6mfazqvmgpr4mhxue69uhkummnw3ez6vpj9eukz6mfdphkumn99e3k7mf0qyshwumn8ghj7mn0wd68yttjv4kxz7fww3jhsctndpjkgem99eu8j7304tyt8u as well Anita

And totally agree with all your concerns. So helpful hearing the different experiences you’ve had. Thanks for sharing

I was running local LLM and qwen model good for some time but the results were not great. Openwebui with Ollama running on two HWs.

The current AI development is dominated by actors who can afford scaling, locking innovation behind capital, infrastructure, and centralized power. This leaves little room for individuals and communities who want to build competent models but cannot compete with Wall Street’s “scale is all you need” doctrine.

What we need are decentralized AI systems that are built collectively, owned collectively, and designed from the ground up to ensure user privacy.

Both the model architecture and the training data should be fully transparent, while the model weights could be monetized to reward contributors.

This creates a transparent, community-driven free-market ecosystem, where users decide which projects to fund and support, aligning incentives with innovation.

I like this point of view.

Perhaps this is a really uninformed statement;

But aren’t people already able to invest/donate to the companies creating open source models like deepseek?

Yes, it is possible. The type of organization developing the project may vary. Companies such as DeepSeek, Meta, and similar ones provide the model architecture and weights, ready for use.

That said, the process is not fully transparent: as an investor in this context, you do not know which data the model was trained on, nor for what purpose. Were training prompts used to enforce certain behaviors? To bias the model against specific ideals?

This should be auditable in my opinion. Then, If fine tuning with private data is required afterward, each user providing this data should have their own secure copy of the model.

I see where you are going. I agree with this.

The problem I see is these companies are in the end money-driven even if they make models open.

They aren’t as free to make everything public because they are tied to their monetary vision. While as the people who would not have a problem don’t have the resources to create a model in the first place.

New models should be developed by small groups, but the problem is how do they start with little to no money?

Another good one you can pay for with Bitcoin, but without the need for annual subsctiption.

https://nano-gpt.com/

Been real happy with proton. Bitcoin accepted for subscription payments

Do they accept it? Was looking for it, but only found fiat payment options.

Might be jurisdiction dependent, idk.

For real? I never saw that option. From where are you subscribing?

Yes that’s what I could find on the internet. But the option was still not there when I tried

From proton AI "Lumo"

I feel you! It’s great to see more options that respect privacy. Maple AI sounds awesome! Love that you’re exploring and finding tools that meet your needs. Keep experimenting! 🙌 #PrivacyFirst

I like https://venice.ai/. Lot of options and you can sign up privately and pay with bitcoin.

have you tried/considered running local LLMs?