AI application companies need edge case data to continuously improve their models, but it is not easy to collect the edge cases only. So, they cast a wider net (collect or generate large data set), hoping they can find enough edge cases. But it is time-consuming (multiple weeks to months) and expensive ($1 - $20 per data point).
If this sounds familiar to you, we can help you. Bobidi is a project (soon to be a company) run by an ex-Facebook Product Manager and an ex-Google ML engineer with a mission to make every byte meaningful and help AI companies make something awesome.
It’s widely understood that the hardest part of building AI is how it deals with situations that happen uncommonly, i.e. edge cases. In fact, the better your model, the harder it is to find robust data sets of novel edge cases. Additionally, the better your model, the more accurate the data you need to improve it. Bobidi helps solve this problem leveraging a global community that runs competitions to find the edge cases.
Please contact us for a quick consultation if you are interested in radically improving your model faster, 10x more efficient, and in a safer way.