AI-First companies put capital, time, and effort behind getting data, ahead of other strategic priorities.

take a real-world workflow, develop software around it, and then add further data and features is why I believe that all business software will one day be intelligent.

Indeed, we’re still in the era of building such workflow apps for many industries—a huge opportunity for software developers willing to learn how specific industries get things done.

AI-First companies are first movers.

Interactive machine learning (IML) is the field of creating such interfaces that collect data to train a specific ML model and then present the results back to the user so that they can make a decision about which data to put into the model for its next iteration. IML can be thought of as yet another way to have teams of paying users label data rat

Here’s the formula: data learning effects = economies of scale to data + data processing capabilities + data network effects. Put in a sentence: get lots of data, process it into something useful in terms of making a decision, and create a system that automatically generates more useful data.

This is a centrifugal process: spinning around lots of data about what people are buying (supply) before settling on what customers need (demand). Many consumer products are designed this way because the potential customer pool is so large.

Amazon’s Mechanical Turk.

Free-riding copycats need both the technology and the data.