The problem, as ever, is about filtering. For every quality piece there 50 amateurish things cobbled together from steel pipes and reclaimed wood (or worse: distressed "shabby chic" furniture made to look like something you'd find in an old B&B on the French Riviera). With all the AI being thrown around, can't someone build a "tastefulness" filter?
Especially in regards to furniture, buying online, sight unseen still isn't a great proposition. We don't expect it will ever be.
Perhaps though online could be a great first step filtering process. Find a bunch of stuff that fits the rough parameters of what you are looking for and looks good in your space then go someplace to try them out with a well kept appointment and ready to go same day follow you home delivery should you decide to buy something.
Maybe this already exists? I haven't had to buy any furniture is several years so not sure what the current state of the markets is.
I've long wanted an extension for Google Image Search, eBay, Etsy, etc. that simply filtered out all listings with images of items with pure white backgrounds. That would go a long ways toward a "tastefulness filter".
Huge indicator of handmade / vintage / used items sold by an individual seller vs. a new item being dropshipped from Amazon or China.
They talk about their curation algorithms here:
It turns out taste varies.
https://www.etsy.com/shop/PurpleHeartUK, https://www.etsy.com/shop/BigSwigDesign, https://www.etsy.com/shop/CraftyMamaGifts, etc.
Perhaps a set of AI filters could be built, and Netlix or Pandora style whichever one a person agrees with more often is selected and more results from it are presented to them.
Or perhaps a Convolution Network trained to filter per person or something equally wasteful if the allocations of Etsy's budget actually match the article. But of course those GPUs would be locally sourced and powered by renewable hamster wheels and 100% organic hamsters.