[chris_f]

Here are some more example queries:

https://you.com/niche/pytorch?q=install+osx&fromSearchBar=tr...

https://you.com/niche/pytorch?q=save+trained+model

https://you.com/niche/pytorch?q=check+if+pytorch+is+using+GP...

[learndeeply]

For the first example the snippet isn't correct, it just says `conda list`. The website (TutorialPoint) it links to is also wrong and useless.

[chris_f]

Appreciate the feedback, it is helpful! The relevance tuning is a continuous work in progress.

[p1esk]

Sounds like a good idea, but I'd like to see how is it better than googling these phrases together with pytorch keyword. Not saying it's not better, just not clear if it is.

[chris_f]

In the broadest sense, a highly targeted search engine (like this) can provide better results because Google has to determine user search intent AND return the right results from trillions of webpages. The advantage of this search engine is that all of the users are looking for the same type of information, and the result sources can be curated to ensure high quality and relevant results.

The more targeted the topic, the harder the time Google has to provide quality signal through the noise of SEO and sheer volume of content on the web.

In addition to the above, the UI provides some cool features like allowing horizontal scrolling of sources to provider higher information density (important for discovery), and some source content can be viewed in the side pane without leaving the page.

But ultimately it would be good to hear if this approach does make it easier to find relevant and higher quality Pytorch info.