Claude gives 7 categories for consideration of time, and 9 categories for the physical definition of time. It gives this pseudocode for implementing an atomic clock.
def atomic_clock():
while True:
atoms = generate_atom_beam()
selected_atoms = state_selection(atoms)
excited_atoms = apply_microwaves(selected_atoms)
state_change = detect_state_changes(excited_atoms)
if state_change != expected_change:
adjust_microwave_frequency()
current_time = convert_frequency_to_time()
output_time(current_time)
wait(update_interval)
From: Friam <friam-boun...@redfish.com> On Behalf Of Jon Zingale
Sent: Sunday, July 28, 2024 10:19 AM
To: friam@redfish.com
Subject: [FRIAM] Clocks
Reflecting on recent conversations (both here and abroad), Michael Levin's
developments of polycomputing, and in preparation for my new role as career
coach to a GPT model, I have come to wonder:
How might one productively set out to architect an unsupervised learning
machine capable of discovering what all can be reliably used as a clock?
I am imagining a machine with sensory organs that is able to (though not
necessarily) generalize its learnings. I imagine it successful if it decides
to not rely on a broken clock, nor an image of a clock face, nor one
programmed to move its arms at random. I imagine it is successful if it learns
to track the sun, the circadian rhythms of animals or plants, if it recognizes
the masing pulses of water in star forming galaxies, cellular clocks, etc...
Would such a machine necessarily be/have a clock itself?
smime.p7s
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