Bigger models.

More parameters.

More impressive benchmarks.

This approach pushed AI forward dramatically.

But it also created a limitation.

Most AI systems today operate in isolation.

You ask a question.

The model responds.

The interaction ends.

There is no persistent collaboration between systems.

No accumulation of shared intelligence.

No evolving structure that grows over time.

The next stage of AI might look very different.

Instead of a single powerful model, we may see systems of intelligence.

Networks where multiple agents interact.

Where knowledge can persist.

Where intelligence compounds through coordination.

This shift changes how we think about AI infrastructure.

From standalone intelligence

to coordinated intelligence.

Projects exploring these ideas are beginning to experiment with architectures where AI agents can interact, share context, and build upon each other’s outputs.

This is one of the directions behind NeuroSynth.

Not just smarter AI.

But systems where intelligence can grow together.