> 1 customer paying $5/mo
Sounds about right.
> 1 customer paying $5/mo
Sounds about right.
> Developers own the products they build for customers, and charge a monthly fee for access.
So, what you're seeing is what a single user is expecting to pay. This is not like a contracting / free-lance website where someone hires you under contract to do some development work.
Instead, you create the SaaS or whatever, and then you have at least x number of people that are willing to pay $y/month for said service; your market is not limited to the people who use this website, too.
I think it's really just a way for people to find what projects people want, and what a select few are willing to pay for it.
In many cases, you can use the model as-is (and likely pre-trained) for a use case outside of "match label to an image", with only some additional training with your specific dataset - which may only be tangentially related (or not even that!).
These models (and the surrounding tools) have become for many problems more like Lego in my opinion - which is a good thing! It means they are more approachable for everyone, rather than being something mysterious and complex. Ok - if you dig, things become complicated quickly, but for many problems, you don't have to worry about these internals.
Are there problems which don't fit neatly into using a modified ImageNet or LeNet or one of the other "standards"? Certainly. But I think a candidate who understands the standards and basics well is likely a better one than one who only understands a specific subset for a particular industry (if there even is such a thing, which I am sceptical of).
Furthermore - it would be even better when a candidate can say "you know what - your problem doesn't need a neural network of any kind, let me introduce you to <insert standard statistical machine learning method>" - because there are tons of problems out there which can still benefit, and be a robust, easy to understand, and fast (to implement, to maintain, to execute - whatever).
I love neural networks, certainly - but there's been so much hype in the news, everyone thinks they need one, which will probably lead to many investing money into worthless (or expensive) solutions, where simpler (but less "sexy") ones would have sufficed.
The candidate who could know and tell the difference would be even more ideal - being able to interview/walkthru that might be a way to get a better candidate.
It's sad that even the highest bidding project is $500/mo.
I know a company which paid around 1M euros to get such data ( and some software ) for just one industry.