While some people spend millions for a robot to gracefully lift a cup of coffee, others have decided to go a more boring but sure way. The real estate and infrastructure giant Brookfield Asset Management colluded (sorry, strategic partnership) with the startup Figure AI. The goal is to create a giant "tutorial" for robots, known as the Pre-Training Dataset. And no, this is not a collection of quotes from Shakespeare, but trillions of fragments of data about how this strange human world works.

The idea is simple to the point of genius, and therefore causes a slight sarcasm. Brookfield owns countless warehouses, offices, and factories — the very places where robots will work in the first place. Instead of waiting for artificial intelligence to guess by poking that it is better to stack the boxes rather than randomly, the company will provide it with real data from its facilities. In fact, they are going to feed Figure AI algorithms with information captured from thousands of cameras and sensors. It's like giving a child not a toy sorter, but access to the archive of all operations of the largest logistics center.

What will be in this "encyclopedia for androids"? Presumably, everything from the simplest movements (how to push a cart without dropping the load) to complex tasks (how not to get entangled in a maze of shelves). Figure AI, known for its humanoid robot Figure 01, hopes that this array of data will become for their creation what kindergarten, school and institute are for us, only without vacations and fun changes.

It sounds encouraging, but it can't do without a healthy dose of irony. Big business has finally realized that robots need not only iron bodies, but also "brains" filled with practical experience. And who, if not the owner of giant warehouses, knows what routine work looks like? However, it remains a mystery whether data about how an employee hides from his superiors in the back room or searches for the right box for fifteen minutes will be included in the dataset. For a complete immersion in the atmosphere — just the thing.

If this project is successful, we may see robots that will understand logistics better from the first day of work than a person who has worked in a warehouse for ten years. However, then a new philosophical question will arise: won't they start sarcastically discussing the inefficiency of their human colleagues? But this is already a topic for the next partnership.