This is a bit like my <a href="http://wherewords.id" rel="nofollow">http://wherewords.id</a> that I made as a fun holiday project. I used the S2 cells (same as the one used by pokemon go), and my own wordlist. Using this approach, I believe I got accuracy down to squares of approximately 2x2 metres with 4 words (from a wordlist of 4096 words). FixPhrase only claims accuracy of 11m, which isn't terrible, but won't locate a single parking space or front door particularly well.<p>The wordlist is surprisingly hard work. The first location I clicked on fixphrase had as one of its words 'french'. That's potentially pretty confusing. It's super hard to get a good wordlist, and it's not just negative words, words that are particularly unusual or words likely to create bad combinations, it's also removing homonyms, words likely to be confused (capital/capitol, carless/careless), geographic words, or words that are combinations of other words in the word list.
neither this nor w3w are as useful as googles already open source <a href="https://maps.google.com/pluscodes/" rel="nofollow">https://maps.google.com/pluscodes/</a> in my opinion.<p>With plus codes you can both have a short, memorable address and gauge relative distance with other nearby addresses. I'm not sure I can think of a reason to ever use fixphrase or w3w as an alternative to this already existing open standard.
It looks like the key difference between this and what3words is that squares near each other have mostly the same words. With only the last word changing for adjacent squares, and even then they are similar. I can see the motivation for this (you can abbreviate to fewer words for a general area), but alto suspect it is partially about the W3w patent. However it also increases the risk of being slightly wrong with a location, w3w is good for things like emergency rescue as you can’t be slightly wrong.
Would be helpful if it accepted UK versions of the words - my current location includes "stylized" but replacing that by "stylised" (as you might well after hearing it on the phone) fails and just returns "London, vaguely".<p>(cf <a href="https://news.ycombinator.com/item?id=31830437" rel="nofollow">https://news.ycombinator.com/item?id=31830437</a> )
I picked a random location and got "daringly kleenex sloppily very". Are there any issues with the fact that "kleenex" is a registered trademark?
So, What3Words is marketing and advertising heavily in India and I have to kinda chuckle at the complexities of the words that are not as common as we speak in everyday English. Try saying "interacts.scrapped.evoked" to an Uber driver and he would cancel you instantly.
The work behind what3words isn't the algorithm. It's the word list used. They have linguistics who check the sounds of words, are they too similar to another word are they rude, etc, etc..