Return to the selections, revisit a useful lesson, or follow a thread into unfamiliar territory.
For the first edition, a tour of what it takes to make intelligent systems dependable after the demo: planning through world models, gathering and evaluating robot experience, serving a policy on-device, and measuring whether language agents remember and repeat what matters. A few older research pieces are here because their mechanisms illuminate the newer engineering reports.
