REVIEW 1 cited by
Watts-Per-Intelligence: Part I (Energy Efficiency)
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
Signed reviews
read the original abstract
We present a mathematical framework for quantifying energy efficiency in intelligent systems by linking energy consumption to information-processing capacity. We introduce a watts-per-intelligence metric that integrates algorithmic thermodynamic principles of Landauer with computational models of machine intelligence. By formalising the irreversible energy costs of computation, we derive rigorous lower bounds on energy usage of algorithmic intelligent systems and their adaptability. We introduce theorems that constrain the trade offs between intelligence output and energy expenditure. Our results contribute to design principles for energy-efficient intelligent systems.
Forward citations
Cited by 1 Pith paper
-
Thermodynamics of Learning: A Typed Four-Component Accounting of Memory, Fit, and Value
A typed accounting separates record correlation from operational capital value in finite learning devices, with separation, capitalization-efficiency, and value-retention theorems.
Discussion (0). Continue with ORCID to comment.