Are you arguing for analog computation? Like how the brain uses 20 watts, while an equivalent neural network on a 10 petaflop GPU cluster needs 1 megawatt? What technology would you use?
-- Matt Mahoney, [email protected] On Tue, Dec 16, 2025, 7:51 PM Dorian Aur <[email protected]> wrote: > This is a fascinating example of *self-replication* and imperfect copying > in living systems, and it directly resonates with principles of > Electrodynamic Intelligence (EDI). Concepts like instruction copying and > emergent complexity can be modeled and explored through EDI frameworks, > providing a deeper understanding of adaptive and evolving systems. > > Dorian Aur > > PS For those interested in a practical exploration of these ideas, there > are resources that illustrate EDI in action and bridge these abstract > biological concepts with computational models: > https://dorianaur.gumroad.com/l/udtedn > > On Tue, Dec 16, 2025 at 6:20 PM Matt Mahoney <[email protected]> > wrote: > >> Living organisms have the following properties that distinguish them >> from non living. >> 1. They reproduce. This implies that they carry the instructions for >> creating copies of themselves that contain copies of the instructions. >> 2. The instruction copying is not perfect, allowing them to evolve and >> gain complexity. >> >> These properties can be reproduced in software. The first property in >> pseudocode looks like this: >> >> Print the following twice, the second time in quotes. >> "Print the following twice, the second time in quotes". >> >> An example of a program with both properties can be found in >> https://mattmahoney.net/rsi.pdf >> >> On Tue, Dec 16, 2025 at 3:57 PM Dorian Aur <[email protected]> wrote: >> > >> > >> > Certain properties attributed to “biological intelligence” may instead >> occur from substrate-independent physical dynamics. >> > >> > I’m exploring whether some core properties commonly attributed to >> biological intelligence might instead reflect substrate-independent >> physical dynamics, rather than biology >> > >> > Concretely, in neural-scale measurements, we can interpret certain >> correlations as occuring from electrodynamic interactions that are not >> specific to any living tissue, and which may not be fully captured by any >> standard computational abstractions. >> > >> > Do you see a reason these dynamics must reduce to computation, and >> they represent additional physical constraints relevant for AGI >> architectures? >> > >> > I have a short written summary, and a longer text/audio treatment for >> those interested; I didn’t want to overload this list. >> > >> > Dorian Aur >> > >> > Artificial General Intelligence List / AGI / see discussions + >> participants + delivery options Permalink >> >> -- >> -- Matt Mahoney, [email protected] > *Artificial General Intelligence List <https://agi.topicbox.com/latest>* > / AGI / see discussions <https://agi.topicbox.com/groups/agi> + > participants <https://agi.topicbox.com/groups/agi/members> + > delivery options <https://agi.topicbox.com/groups/agi/subscription> > Permalink > <https://agi.topicbox.com/groups/agi/Tca9651e0e10920d5-M12b8ada5233b0e6c3ea60e32> > ------------------------------------------ Artificial General Intelligence List: AGI Permalink: https://agi.topicbox.com/groups/agi/Tca9651e0e10920d5-Me059507b463cda636a4dab6b Delivery options: https://agi.topicbox.com/groups/agi/subscription
