Anytime:)
HN user
aldamiz
Chicisimo CEO
Good job! We built something in the space, discussed it in detail here https://news.ycombinator.com/item?id=21703297
thanks rurp - fixed.
I wouldn't say our "Product people" are very traditional product people, you have our bios and focus in the team link in the post and below. Hope it helps
https://docs.google.com/document/u/1/d/1r0IIViwp5MuNcWXZqNI2...
Yes. I wouldn say our "Product people" are not very traditional product people, you have our bios and focus in the team link in the post and below. Hope that clarifies the doubts. I've also clarified it in the text, and it now reflects the reality better.
https://docs.google.com/document/u/1/d/1r0IIViwp5MuNcWXZqNI2...
thanks sofia :)
thanks theicfire :) maybe in the future!
:)
Hey AndrewKemendo, such a great comment, so many points to think about. Thanks for sharing!
In our case, size is a property in the ontology.
For some players (second hand for example) size is the number one "personalization" requirement. Imagine you see a feed of products, and none of it is your size...
:)
You are right, the fashion taste api website does not intend to be stylish. It tries to convey a message to business and tech teams, and we know it could have a better design. Take a look at the consumer product https://www.youtube.com/watch?v=EMMmdCB1-Wg hopefully you like the design better :)
Thanks bumblebee4 - fashiontasteapi.com is a the b2b side of the company and the value prop is that we can help retailers automatically classify clothes and understand/classify people. It is for technical and business people, not the end consumer. This is a line of business we were just starting, and hopefully will continue.
The consumer website is chicisimo.com :)
Yes you are right, it is an excerpt from one of our patents. I completely agree that it is very confusing as a caption, and I've taken it out. Doing it in a hurry didn't help. Thanks for the heads up.
I hope you can read the post and be more positive. Thanks!
Facebook always linked to great news!
Thanks Andrew. They are an amazing team with a great ontology, I agree. Thanks for the heads up!
Thanks for your interest Goldemerald. A couple of comments:
- We do use DL. I didn't mention it because it is not relevant in the context of the post;
- How we use DL. One of the jobs of the graph is to tell the DL algorithm what content needs what type of descriptors. The graph can do this thanks to the different levels in our ontology, and because it understands our content in its context: it understands people's interaction and tagging. DL is a small part in our entire infrastructure;
- The DL market. Lots of companies use DL to identify attributes in an image, and the level they achieve is impressive. Having had long discussions with the best of these companies, I can tell you that building the correct ontology is nearly impossible without the entire infrastructure. We are happy building the intelligence that tells DL what to do, and then attaches descriptors correctly to outfits and taste profiles;
- Our patents. They cover a few relevant aspects in the online fashion market: a system to tag fashion images with shoppable products; a system and method to capture/understand how people mix and match clothes in outfits and closets; and more.
I wonder how much will this impact in conversion to trials
Hey Andrew, we started building it in 2012. The concept is similar as you say. The most relevant difference is the ontology: our ontology is very specific to what-to-wear needs, theirs isn't. Thanks
FB will use artificial intelligence to determine when someone has died
Everything about Facebook looks terrible
Totally agree with this "The product mindset is a complicated definition". I'd say it is about understanding that building a product people really love and engages with, is key to success. Not the only factor of course, but that's what many business oriented people do not understand.
If I understand well, you are using both product tags from retailers, and generating your own tags using image search? I'm curious: how many tags have your trained your system for... how large in your taxonomy?
I would totally use this!
"The best way to check for a two-way mirror is by using your fingertip. On most mirrors, if you place your fingertip on the mirror, the reflection of it will not touch. Instead, it will leave a quarter inch gap or so"
Went to check all mirrors at home, and placed my fingertip on them. In all, the reflection of my finger touches my finger.
I'm gonna need to have a serious conversation with my wife now.
Worked for me as well, iPhone X. Very cool!
walk
Thanks. I've been looking at the guidelines, but I cant find any reference to this issue: https://developer.apple.com/app-store/review/guidelines/ https://developer.apple.com/library/content/documentation/Ne...
I'm a man:) Sorry I don't know about fashion apps for men. I feel teams are building the infrastructure focusing on the big opportunity (women's fashion). Then, expanding to other categories will be way easier.
Yep. The main idea of the app is to help people decide how to wear their existing clothes. Many people feel they have nothing to wear when their wardrobe is full - truth is, sometimes the decision of combining some clothes is not an easy one and you simply stop using them. Or even deciding what to wear every single day can be a pain.
About clothing apps, here are some ideas.
There are teams focusing on the social aspect and grow via influencers. I’d think about utilities (help me do something):
- Help me decide what to wear: Chicisimo, Pinterest and (believe me) Google Images;
- Help me manage my wardobre: Stylebook, Glamoutfit;
- Help me be seen by others: Wear app, Lookbook and Chictopia (this last two worked really well on desktop);
- Help me decide what to buy: ecommerce apps obvsly, or Liketoknowit; or the second-hang category of which several are working really well, and are more widely known.
- Help me get feedback from my friends, no one really working I think, or feedback from the system (Echo Look -> Spark). And a new related category popping up: get feedback from a stylist with an in-app purchase model or even subscription; Wishi, Daam are some examples. This last category will be interesting to follow.
- Polyvore - outfits ensembling;
- Rent the Runway, Stitch Fix, Instagram obvsly. And I'm sure I'm missing many, but just trying to give you ideas of how to find inspiring apps.
I wonder if online fashion is like online music in 2005/6/7... with lots of noise, some tech focused products, and the spotify's of the world starting to be built. Fun times.