5 ms·

I think What3Words is in principle a nice idea, but it could have been implemented much better. I am thinking of the following: - have a fixed pattern, e.g. ad

I think What3Words is in principle a nice idea, but it could have been implemented much better. I am thinking of the following: - have a fixed pattern, e.g. adjective.adjective.noun. - create groups of words and put them in hierarchies. E.g. noun->animal->predator - cover the world with a one-dimensional Hilbert curve - Increment the noun along the curve. When all nouns are exhausted, start with the first noun again and increment the adjective in the middle, a.s.o. (analog to how incrementing a number with several digits works). With this approach, the location purple.flying.tiger would be next to purple.flying.lion.

Gys 3y ago
It is not like that by design. Remember, this is backed by VCs that already put in a lot of money and in some future will want to make a lot of money. The 3 words idea is patented and the basic idea is to have a drm protected database that is needed to find the actual location. The play the long game. Ultimately selling access to the database will make them money.
hgomersall 3y ago
That's specifically problematic: what was their location again? Uhm, it was purple flying something.. some kind of big cat.. lion or tiger.. Large conceptual distance between close physical locations is a feature not a bug.
thelittlenag 3y ago
You should check out https://www.qalocate.com/solutions/geohashphrase/ https://www.qalocate.com/solutions/geohashphrase/
lhl 3y ago
I spent a few minutes exploring a similar. Using the EFF wordlist (7776 words designed to be unambiguous)[1] you should be able to get down to about 100m^2 blocks (good enough for SAR), the BIP39 word list (2048) is a bit too resolution, but is a lot easier to pronounce, maybe worth some encoding shenanigans to get it to work). For my POC, I also used a simple 1D hilbert curve. Running a simulation and plotting the words, you actually get pretty decent resolution, and it's even alphabetical by distance. Output from simple demo w/ BIP39 (math might not be correct): https://ibb.co/MnmcRFk https://ibb.co/MnmcRFk but you can see that the word order actually make sense (although "winner" and "winter" are too phonetically similar, but still, gets the point across). [1] https://www.eff.org/deeplinks/2016/07/new-wordlists-random-passphrases https://www.eff.org/deeplinks/2016/07/new-wordlists-random-p...

Gys 3y ago

It is not like that by design. Remember, this is backed by VCs that already put in a lot of money and in some future will want to make a lot of money. The 3 words idea is patented and the basic idea is to have a drm protected database that is needed to find the actual location. The play the long game. Ultimately selling access to the database will make them money.

hgomersall 3y ago

That's specifically problematic: what was their location again? Uhm, it was purple flying something.. some kind of big cat.. lion or tiger.. Large conceptual distance between close physical locations is a feature not a bug.

thelittlenag 3y ago

You should check out https://www.qalocate.com/solutions/geohashphrase/ https://www.qalocate.com/solutions/geohashphrase/

lhl 3y ago

I spent a few minutes exploring a similar. Using the EFF wordlist (7776 words designed to be unambiguous)[1] you should be able to get down to about 100m^2 blocks (good enough for SAR), the BIP39 word list (2048) is a bit too resolution, but is a lot easier to pronounce, maybe worth some encoding shenanigans to get it to work). For my POC, I also used a simple 1D hilbert curve. Running a simulation and plotting the words, you actually get pretty decent resolution, and it's even alphabetical by distance. Output from simple demo w/ BIP39 (math might not be correct): https://ibb.co/MnmcRFk https://ibb.co/MnmcRFk but you can see that the word order actually make sense (although "winner" and "winter" are too phonetically similar, but still, gets the point across). [1] https://www.eff.org/deeplinks/2016/07/new-wordlists-random-passphrases https://www.eff.org/deeplinks/2016/07/new-wordlists-random-p...