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> Paid ads are prohibitively expensive I've had some success with them. There are tricks, you just need to look for them. Unfortunately my product (https://nue

> Paid ads are prohibitively expensive I've had some success with them. There are tricks, you just need to look for them. Unfortunately my product (https://nuenki.app https://nuenki.app) is very low margin so it doesn't quite work out, but I wouldn't write them off entirely. AI just means that you need something other than your code to be the product. Also, both from pg's essay and my own experience, marketing matters more. BTW you write like an LLM. I don't think you are one, but mind that.

mgl 2y ago
What tricks do you have in mind, like super personalized retargeting?
- Alex-Programs 2y ago
  I have one trick, and I won't share it because it's very niche and my margins are very thin (well, still slightly negative...) so any competition would kill it entirely. But it came about as a result of closely looking at my audience, looking for ways to precisely target them, and creating ads in a way that that demographic likes. Before that, I had some success using Python to generate many thousands of niche google keywords (e.g. don't advertise on "Learn Spanish", but instead "How to learn Estonian quickly" and "What's the best way to learn Hungarian online") and advertising on them. It didn't have a positive ROI for me, but it might for other people with larger margins. Tricks exist, you just have to look for them. Remember that most marketing people can't code, and exploit that.
XCSme 2y ago
Your app looks really cool. I like how you can hover to see the original. That being said, I wouldn't really use it for privacy reasons. Is all the data sent to some third-party API? What stops it from sending banking information, contact details, email addresses, credentials, etc?
- Alex-Programs 2y ago
  The data is sent to a relay server, which then sends it on to Deepl/Claude. There are quite a few layers of privacy: 1. Websites on the blacklist (e.g. banking sites), or with certain terms in the URL (e.g. "account"), are blacklisted 2. Websites can be blacklisted by the user 3. Sentences are checked for sensitive language, and filtered for banking info/emails/credentials/etc 4. The words in a sentence must be over a certain proportion (80% iirc) of known English words 5. Once the sentences are sent to the server, the server doesn't log who-sent-what, and the upstream translation services don't know either (because it all comes from the relay). Translations are cached, though. It's a necessity in order for it to be even remotely economical to do so much translation.
  - XCSme 2y ago
    Yeah, I am not worried about the privacy for sending the data to your servers, but for it being forwarded to the cloud LLM models. Could you add support for local models/Ollama?
    - Alex-Programs 2y ago
      Sorry, I missed your reply! Local LLMs previously weren't good enough, but I've recently done another set of benchmarks (https://nuenki.app/blog/llm_translation_comparison https://nuenki.app/blog/llm_translation_comparison) and llama 3.3 70b is getting there with some languages. Currently I'm in the process of integrating it via Groq, but it could plausibly be done with local LLMs. Above a certain scale I'll start self hosting, but I'm nowhere near justifying those fixed costs yet. Would you prefer to run ollama locally, or just know that the translation server is running its own models rather than forwarding onto cloud providers?
      - XCSme 2y ago
        I just don't want to send the content of the browsed sites to any third-party service. I am using LanguageTool though, having a local alternative to that will be great too.

mgl 2y ago

What tricks do you have in mind, like super personalized retargeting?

Alex-Programs 2y ago
I have one trick, and I won't share it because it's very niche and my margins are very thin (well, still slightly negative...) so any competition would kill it entirely. But it came about as a result of closely looking at my audience, looking for ways to precisely target them, and creating ads in a way that that demographic likes. Before that, I had some success using Python to generate many thousands of niche google keywords (e.g. don't advertise on "Learn Spanish", but instead "How to learn Estonian quickly" and "What's the best way to learn Hungarian online") and advertising on them. It didn't have a positive ROI for me, but it might for other people with larger margins. Tricks exist, you just have to look for them. Remember that most marketing people can't code, and exploit that.

XCSme 2y ago

Your app looks really cool. I like how you can hover to see the original. That being said, I wouldn't really use it for privacy reasons. Is all the data sent to some third-party API? What stops it from sending banking information, contact details, email addresses, credentials, etc?

Alex-Programs 2y ago
The data is sent to a relay server, which then sends it on to Deepl/Claude. There are quite a few layers of privacy: 1. Websites on the blacklist (e.g. banking sites), or with certain terms in the URL (e.g. "account"), are blacklisted 2. Websites can be blacklisted by the user 3. Sentences are checked for sensitive language, and filtered for banking info/emails/credentials/etc 4. The words in a sentence must be over a certain proportion (80% iirc) of known English words 5. Once the sentences are sent to the server, the server doesn't log who-sent-what, and the upstream translation services don't know either (because it all comes from the relay). Translations are cached, though. It's a necessity in order for it to be even remotely economical to do so much translation.
- XCSme 2y ago
  Yeah, I am not worried about the privacy for sending the data to your servers, but for it being forwarded to the cloud LLM models. Could you add support for local models/Ollama?
  - Alex-Programs 2y ago
    Sorry, I missed your reply! Local LLMs previously weren't good enough, but I've recently done another set of benchmarks (https://nuenki.app/blog/llm_translation_comparison https://nuenki.app/blog/llm_translation_comparison) and llama 3.3 70b is getting there with some languages. Currently I'm in the process of integrating it via Groq, but it could plausibly be done with local LLMs. Above a certain scale I'll start self hosting, but I'm nowhere near justifying those fixed costs yet. Would you prefer to run ollama locally, or just know that the translation server is running its own models rather than forwarding onto cloud providers?
    - XCSme 2y ago
      I just don't want to send the content of the browsed sites to any third-party service. I am using LanguageTool though, having a local alternative to that will be great too.