What surprised you the most when you came back to it now?

I guess what surprised me is how much the centre of gravity has shifted and how little I recognised, how little was familiar in terms of the basic questions.

Who buys data for AI? What kinds of data matter most? Where is value being created? What kind of suppliers are in the market and how are they positioning themselves? All of these very basic questions had very different answers when I looked at them this year when we produced the report in 2019.

Back in 2019, the main question was scale.

So all of the focus was around these data annotation workforces producing data that was used to develop specialized task-specific models.

So we're all familiar with machine translation models, speech-to-text, and there were other areas that were generating a lot of demand, robotics, image recognition, and so on.

So going into this research, I kind of expected to find an evolved version of that market.

So why is evaluation becoming so important or is already so important?