- A Nature paper on single-molecule kinetics (https://www.nature.com/articles/s41467-024-54677-1) was shared as evidence that classical Arrhenius behavior can be measured at the individual-reaction level, informing bottom-up models of biological computation.

- A new review, “The Multiscale Wisdom of the Body” (https://onlinelibrary.wiley.com/doi/epdf/10.1002/bies.202400196), was highlighted for framing collective cellular intelligence as a tractable interface for next-generation biomedicine.

- Participants estimated that the ~10 m² of synaptic membrane in a human brain is dwarfed by the ~2 000 m² of total cellular membrane area, suggesting vast untapped capacity for non-neural information storage via lipid composition, ion-channel positioning, or cell-wall thickness modulation.

- A Cell Reports Physical Science paper (https://www.cell.com/cell-reports-physical-science/fulltext/S2666-3864(24)00436-3) was cited showing that electro-active polymer hydrogels can exhibit emergent memory when embodied in a simulated game environment, reinforcing the idea that memory-like behavior can arise from physical materials without traditional neural architectures.

- Discussion emphasized that cytoskeletal networks couple membrane-level changes to nuclear mechanics, potentially enabling mechanical or bioelectric “writing” and “reading” of distributed cellular memory states.

- A 2011 Hubler paper on “Fabrication and programming of large physically evolving networks” (https://diyhpl.us/~bryan/papers2/ai/physical-intelligence/Fabrication%20and%20programming%20of%20large%20physically%20evolving%20networks%20-%20Hubler%20-%202011.pdf) was re-circulated as foundational reading for building macro-scale, self-modifying physical computers.

- The polycomputing.ps archive (https://diyhpl.us/~bryan/papers2/ai/physical-intelligence/) was recommended for further exploration of non-digital, substrate-independent computation.

- A 2023 Gershman review, “The molecular memory code and synaptic plasticity” (https://diyhpl.us/~bryan/papers2/ai/The%20molecular%20memory%20code%20and%20synaptic%20plasticity:%20A%20synthesis%20-%20Gershamn%20-%202023.pdf), was offered as a unifying framework linking molecular-level plasticity rules to higher-level memory phenomena, supporting the view that neuronal capabilities are elaborations of more ancient cellular learning mechanisms.