Topic: trajectory data

Aakanksha Chowdhery examines changes to pre-training that could support reasoning, planning and multi-step agent workflows. Drawing on large-model training experience, she discusses next-token prediction, attention and loss functions, trajectory data, context retrieval, error recovery and the role of scale in learning tool use.

Dictyostelium Discoideum (DD) are a fascinating single-cellular organism. When nutrients are plentiful, the DD cells act as autonomous individuals foraging their local vicinity. At the onset of starvation, a few (<0.1%) cells begin communicating with others by emitting a spike in the chemoattractant protein cyclic-AMP. Nearby cells sense the chemical gradient and respond by moving toward it and emitting a cyclic-AMP spike of their own. Cyclic-AMP activity increases over time, and eventually a spiral wave emerges, attracting hundreds of thousands of cells to an aggregation center. How DD cells