The Cognitive Revolution · Saturday, July 4, 2026
Liquid AI is refining its network architecture search process by evaluating models on actual hardware and downstream tasks, moving away from potentially misleading proxy metrics. Ramin Hassani explained that for specific use cases and limited compute resources, their search is more likely to discover novel, exotic architectures.
“Perhaps most interesting is the network architecture search process that Liquid uses to develop networks for particular use cases and runtime environments.”
“Having found that proxy metrics too often lead the process astray, they now evaluate models on real downstream tasks on the actual target hardware that their customers intend to use.”
“But the more specific your use case and the more limited the compute resources you have available, the more likely their search process is to land on an exotic architecture.”