| As someone who has actively participated in DDH for a while now, here are my views: - A non-trivial part of the current contributions included "cheat sheets" which IMO, really required a lot of effort to ensure correctness/usability but don't really provide much improvement to search results(I don't think I myself used the feature in the past 1.5 years more than 3-4 times), so, this should really free up time for DDG staff to focus on the more important instant answers and features. - The community has been, for a while now, getting smaller and less contributing in the recent past. Backed by data from official repos(the number of commits over time, that is)[1]. After all, there are only a finite number of instant answers before they just become redundant. - The current model for the triggers(when an instant answer gets displayed) is quite restrictive. It's just regex-based. IMO, a lot more growth can be achieved using ML models for triggering, A/B testing etc. I'm still kind of disappointed with this. Perhaps unrelated, but does anyone have any suggestions for people willing to work on similar open source projects. [1]: https://github.com/duckduckgo/zeroclickinfo-spice/graphs/con... , https://github.com/duckduckgo/zeroclickinfo-goodies/graphs/c... |
Entire web archives such as the entire dump of wikipedia and stackexchange (including media and indexes for search) can be stored locally. The missing piece is Google level search quality on the local machine. Given that brute force substring search can process Gigabytes in seconds nowadays. If you have enterprise grade server hardware things are reaching 1000GB/s. At this rate, there is no reason to think in a couple years local search of all known human knowledge can't happen on a local device at Google level result quality.
For anyone interested in the search space look into whats possible today in local offline search.