Part 3 of 3: Customer work changed the hiring story. Alexandr Wang describes how automotive and autonomous-driving projects brought momentum and helped grow the team. Final part of the series.

Part 3 of 3: Thousands of simulated robots train in parallel. The demo then evaluates the policy before deploying it to the real MicroDuck. Final part of the series.

Part 2 of 3: A recruiting coffee is not the same as a recruit. Alexandr Wang describes the pitches that went nowhere, and why people who knew him were different. Next: how customer momentum helped hiring.

Part 2 of 3: Before a robot can learn, it needs a world to learn in. The demo builds objects, materials, physical properties and a simulation. Next: training, testing and the real robot.

Part 1 of 3: Why did Alexandr Wang hire people he knew from school? They trusted him. This series follows the early team, failed recruiting coffees and the momentum that helped hiring. Next: why those coffees went nowhere.

Part 1 of 3: Ask an agent to build an agent. Jensen’s opening line, then the whole journey: plan, simulate, train, deploy. Next: how the simulated world gets built.

More jobs in ten years? Daron Acemoglu disagrees with the prediction. Which side of this debate makes the stronger case? Source: 60 Minutes / @60minutes. No endorsement implied.

The speed of the transition matters, not just what AI can do. Daron Acemoglu explains why he sees this shift differently. Source: 60 Minutes / @60minutes. No endorsement implied.

New jobs can exist without replacing every job lost. Daron Acemoglu challenges the AI-training-jobs argument. What do you think? Source: 60 Minutes / @60minutes. No endorsement implied.

What I’m doing while all my agents work.