Hevolve AI: Self-Evolving Multimodal AI Agents

Turn your domain expertise into AI agents that keep learning. Hevolve AI lets experts build multimodal AI systems by talking to them and correcting them in real time, with no code to write.

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Is the network getting better?

Every node broadcasts a signed delta and every receiver verifies it before counting it. This shows what was counted and how many nodes it came from. Measured figures and projections are labelled separately, and a projection with no basis is not shown.

Nodes reporting

1

verified within 60 min
Counted in the mean

0

none stale
Collective index

--

knowledge capacity, not capability
Growth per join

--

above 1.0 is compounding
Next threshold

2 nodes to go

Three nodes: The first threshold: does the sum beat the single?

A floor test. Three models voting reduce error; it says nothing yet about capability.Stages are a hypothesis from hive_benchmark_prover.py, unmeasured. The node count is measured.
Projection
Not enough nodes to project
A growth rate needs at least two joins to exist. One node is a reading, not a trend, and drawing a line through it would be invention.
The ladder
Seven stages as written in the source, with where the hive actually is. Every score in the original is a projection; none has been measured.

1

One node

A single model, running locally.

here

3

Three nodes

The first threshold: does the sum beat the single?

10

Ten nodes

Expert routing across models with different blind spots.

100

A hundred

Network mixture-of-experts.

1,000

A thousand

Generate, review, test as separable roles.

10,000

Ten thousand

Hive learning compounds across the population.

100,000

A hundred thousand

Beyond what one model does.

Per node
The rows the totals came from. Recompute them yourself if you hold the same deltas; that is why they are here.
NodeIndexGrowthAgentsLast heard
ea4fe896c879 (this node)------36s ago
The index is a knowledge-capacity figure from concept-graph topology: log2(paths + 1) x (1 + depth/10) x (learned/concepts). It measures what the graph can express, not how well a node answers. Nodes past the freshness window are listed and excluded from the means. Refreshes every 30 seconds.