> More data is necessary with current technoloogy, in the sense that modern statistical machine learning algorithms are very bad at generalising to unseen data, and the only way to overcome this is to give them more examples.

Precisely.

> There are machine learning techniques that generalise well from few data, but they are not very well known in the industry.

Sure, and we'd all love to be using those. But even if you generalize well from small datasets, you still generalize better from larger ones.

> Also, though more speculatively, I think the idea of "lots of data" is attractive to marketing departments. There's something about algorithms that need huge amounts of data and compute, that only a select few companies can use. I guess it gives bragging rights, of a sort: "we got the biggest data around. Buy our stuff!".

It may be attractive to marketing departments, but it is also essential to data science projects like this.