Ask HN: Lean Validation of AI Startups
For example, I think that a software for the construction industry that uses cameras to detect if the workers are using the proper security equipment would be a good and useful product. I can ask and then find someone from a potential company that could be interested in this kind of product.
The problem is what to show to this potential client in order to get a deal. I could develop a demo, but I think it's too expensive to build a good model. If I want to test another usecase (for example, house floor identification for real estate) I'd then have to build a model for that.
Do you have experience on this industry doing something similar to what I describe? What are you doing to validate quickly if an idea is good or not?
Maybe a good way would be to start working as a consultant/freelancer, validating demand for a product this way. But that is a slower path and you need time to work as a consultant/freelancer.
3 comments
[ 3.6 ms ] story [ 18.9 ms ] threadHence, your idea should come after the data, not before.
In this case, I would suggest going to companies that already have data (for example support tickets), which they do not use.
After you have data, I would use auto ml.
In any rate, unless you have a dataset of your own, the ML part does not matter.
I think that any ML project today, it more of a solution engineering type project, and not a product.