>(A) it's really hard to work on machine learning without a lot of data, and it's often hard to get that data without actual users using the product in roughly

>(A) it's really hard to work on machine learning without a lot of data, and it's often hard to get that data without actual users using the product in roughly the way it's supposed to work, and Delusional; if it's really hard to get it to work then it's really hard to get it to work; investors should not believe "if only we get the data" >(B) the company can prove there's commercially significant demand for the user experience that they hope to be able to eventually do with some algorithms/AI technology, and thus can attract investor capital for making the thing actually work (potentially years later). In some cases, the human-powered product might actually be really good, and the economics might work in. Delusional - if the economics work then everyone would be doing it, there's no money in it, the investors should only invest if they understand that rooms full of transcribers will be needed - with all the management, recruitment and security issues that brings. This is what the last wave of voicemail transcription companies tried; they all went bust with scores of millions of loss. Be warned.