Topic: internal state

Microsoft researcher Alexia Jolicoeur-Martineau explains the Tiny Recursive Model and the reasoning behind her work on small networks that repeatedly refine an internal state and proposed answer. The conversation examines truncated gradients, puzzle-solving benchmarks and the differences from autoregressive language generation. It also considers molecular modelling, limits of data scaling and which research directions she would prioritize. Hosted by Ravid Shwartz Ziv and Allen Roush. Watch the full conversation on the publisher’s YouTube channel.

The nervous system is fundamentally a closed loop control device: the output of actions continually influences the internal state and subsequent actions. This is true at the single cell and even the molecular level, where “actions” take the form of signals that are fed back to achieve a variety of functions, including homeostasis, excitability and various kinds of multistability that allow switching and storage of memory. It is also true at the behavioural level, where an animal’s motor actions directly influence sensory input on short timescales, and higher level information about goals and i