Increasing collective agentic task solving speed by 5 to 7 orders of magnitudes in agent swarms

A developer's Claude-assisted analysis claims that agent swarms communicating in Hyperlambda (HL) rather than natural language (NL) plus a sandbox would cut electricity consumption by 5 to 7 orders of magnitude and reduce a task that takes 5 seconds under HL to 75.2 days under NL. The author points to code at hyperlambda.dev for verification of the claims, which are based on a hypothetical swarm of one million agents collaborating on a single task. No independent benchmark or peer-reviewed measurement is reported.

I asked Claude to imagine an AI agent swarm with one million agents, collaborating on a single task. Then I told it to compare two means of communication; Then I asked it to estimate the differences in the electricity consumption ratio for both of the above scenarios. Its conclusion is that it would require 5 to 7 orders of magnitudes more electricity using NL versus HL, and a task that takes 5 seconds to solve using HL, would require 75.2 days to solve using NL + Sandbox. You can find the code for Hyperlambda here https://hyperlambda.dev to verify or bust my claims.