Yacy VS Searx

It turns out you can make it all the way to become president of Harvard [1] while ignoring this rule so it is questionable whether it is as set in stone as you make it out to be, at least in certain disciplines.

In a way these models are a perfect mirror of the current academic climate. They plagiarise without remorse, they follow the latest identity-politics diktat to a point and make up 'facts' when needed to reach a desired narrative. Google Gemini is the latest example [2] of where this leads.

Given that it is plausible that models like these will soon be used in educational settings this is a recipe for disaster. The same goes for the trend to replace search engine results with 'interpreted' results in which LLMs take up the same role as Winston in 1984: Winston works in the Ministry of Truth where he alters historical records to fit the needs of the Party.

It is time for a decentralised distributed search engine which limits itself to pure search, something like YaCy [3]. Something to replace Winstonian search engines like Google and Bing (et al.).

[1] https://www.campusreform.org/article/claudine-gay-is-a-dei-h...

[2] https://news.ycombinator.com/item?id=39465255

[3] https://yacy.net/

> Now I just need some kind of open source search engine to run on it ...

Here you go: https://yacy.net

I remember https://yacy.net/ but the big problem of this project was java and had not implementations in others languages. I mean it as imagine torrent was only in perl.

Admarus is similar as Yacy but aims to be distributed where Yacy is federated. Both are made for the web

You should check out https://yacy.net: a global, P2P web search engine, where each peer can build and share its own index, etc.

I also have an instance of Yacy installed, which I use to index the entire system, giving me my own private, internal search engine.

I think searx was largely built by a single person.

https://github.com/searx/searx

I use Recoll to index all of it. Recoll WebUI exposes an API, which I plugged into Searx.

The quality of Google search results has been awful for many years now, but if you still want to use it, the only usable way is via a frontend like Searx[1]. Using any of Google's frontends for any of their services is an exercise in frustration from dodging ads and fighting their hostile UI.

[1]: https://github.com/searx/searx

RSS-Bridge has a Google search adapter. You can also fake it with Searx (which offers RSS feeds of search results).

I've recently wondered how effective local models were at chaining together thoughts as proposed in https://ofir.io/self-ask.pdf. Turns out they are indeed capable of doing so while also creating reasonable chains of thoughts that are easily as good as OpenAI's models. To make it completely free to run I used SearX running inside a Docker container with a second model curating the search results for the main model to get answers from the web.