Ask HN: Please grill us on our YC idea
Hey, we're at Haus in SF right now and wondered if anyone out there would help us out and want to grill us on our YC idea adifyit.com, our interview is Monday.
14 comments
This is a very neat idea. A couple of questions come to mind:
Do you rely on an outside source for picture identification? If so, what's your plan if/when it fails? If not, do you plan to build your own in-house system?
Have you tested whether your code has any impact in page load speed (Y-Slow and company)?
Related to Q1, if you have your own in-house system, will you have your own database of pictures for feature extraction/matching, and how do you plan to make it large enough (and grow it fast enough) to accomodate the wide variety of pictures that people take and post?
I think that if you implement this well, you potentially have a real winner here. Best of luck to you!
Do you rely on an outside source for picture identification? If so, what's your plan if/when it fails? If not, do you plan to build your own in-house system?
Have you tested whether your code has any impact in page load speed (Y-Slow and company)?
Related to Q1, if you have your own in-house system, will you have your own database of pictures for feature extraction/matching, and how do you plan to make it large enough (and grow it fast enough) to accomodate the wide variety of pictures that people take and post?
I think that if you implement this well, you potentially have a real winner here. Best of luck to you!
Thanks for your reply. We are building the picture identification in-house, we have a crude working demo as a proof of concept that the tech is good enough.
We've used the Amazon product API to build our databsae, there are ~80m products in there. We're starting one vertical at a time (the algo works best for highly textured products such as watches/book/cd covers so we've started there). We build an in-memory index of image-descriptors which is queried when trying to match a product. As we start seeing other product type, we'll expand beyond amazon.
As for scaling, the index is the one component that isn't trivial to parallelise. Once we get to a stage where a single box can't store it in memory, the first step would be to shard it, with different indexes per product category. Query images will be run through a product-categorisation algo to determine which indexes they need to be run against. This is how we think we'll approach this, from previous experience, but will investigate properly (if) we get large enough.
In terms of affecting page load, our plugin will load async, as will the results returned from the image matching algorithm, so it should be fairly negligible impact.
We've used the Amazon product API to build our databsae, there are ~80m products in there. We're starting one vertical at a time (the algo works best for highly textured products such as watches/book/cd covers so we've started there). We build an in-memory index of image-descriptors which is queried when trying to match a product. As we start seeing other product type, we'll expand beyond amazon.
As for scaling, the index is the one component that isn't trivial to parallelise. Once we get to a stage where a single box can't store it in memory, the first step would be to shard it, with different indexes per product category. Query images will be run through a product-categorisation algo to determine which indexes they need to be run against. This is how we think we'll approach this, from previous experience, but will investigate properly (if) we get large enough.
In terms of affecting page load, our plugin will load async, as will the results returned from the image matching algorithm, so it should be fairly negligible impact.
Great concept - could be the future in advertising.
But like any ad network, how do you guys plan on keeping up with splogs (spam blogs) abusing your service ?
But like any ad network, how do you guys plan on keeping up with splogs (spam blogs) abusing your service ?
As our ads are affiliate links (CPA), it shouldn't be a problem as a user has to actually buy something for payments to go through.
Adify.it links are only shown when users engage and mouse-over a product.
What about mobile?
What about mobile?
For mobile as there's no concept of hover, we'd put an always-on button in a user-specified corner of the image. When the button is tapped our ad overlay would show.
The "Why trust us..." headline made me wonder if it works very well. Why wouldn't I trust you?
Thanks for your feedback. There is an element of trust involved as we are going to modify the look/feel of the host site. But if this causes potential customers to wonder if it works well, then we should probably reword it.
For what it's worth, here was my reaction: At first I was thinking "cool". then I read that headline, and thought, "I hadn't thought of this as something I need to trust people with. In fact, now that I think about it, I bet that's really hard to pull off." Then I thought about the crazy non-contextual intellisense stuff out there and was wondering if the whole mess is even possible without turning the website into a spamfest.
That's good to know. We've changed it to 'Why use adifyit...'. Right now if we are not confident that we have found a product match, we just don't show anything, so won't turn the site into a spamfest.
Close but no cigar
http://taggify.net
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If you haven't yet, you could try answering some of the questions here: http://news.ycombinator.com/item?id=3896121
Maybe answering them publically would get some feedback?
Best of luck.
Maybe answering them publically would get some feedback?
Best of luck.
How did your interview go?
Oh, and clickable: http://adifyit.com/
Go to this thread below and grill yourself with these 34 questions.
http://news.ycombinator.com/item?id=3896121
You perhaps will find yourself where you are in the application. By the way, the idea is cool. But does your algorithms advanced enough to distinguish between items that can be bought (commercials) compared to those can't (human face, nature photographs etc to example a few)?
You perhaps will find yourself where you are in the application. By the way, the idea is cool. But does your algorithms advanced enough to distinguish between items that can be bought (commercials) compared to those can't (human face, nature photographs etc to example a few)?
Thanks for your reply. Yes, the algorithm would match against product images, so most likely faces and nature photographs wouldn't match any images in our product database.
Here is an example of what the ads would look like on our site dump.ly:
http://dump.ly/y3uyGE2hpn2j
Here is an example of what the ads would look like on our site dump.ly:
http://dump.ly/y3uyGE2hpn2j