Autonomous Internet

The next internet, built by machines, will begin by leveraging the existing Internet, then building a new, lower-level communication protocol that's more efficient.

The Internet is the transfer of information between two or more entities using shared communication standards. It’s less about two individuals communicating and more about the shared standard for how that communication takes place.

For example, two companies may communicate differently inside each company, such as one using Slack and the other using Teams, but then use a shared standard like email to communicate between them.

We can think of each company as a Small World Network because it contains multiple people and machines communicating densely within that network, with fewer connections between networks.

At a conceptual level, the Internet is really a collection of networks communicating with one another through shared standards.

This is also how Biologic Intelligence is organized. Connectomes in the nervous systems of animals exhibit Small World Network properties, with dense local connections and fewer long-range connections. The human brain contains roughly 100T synaptic connections.

On the Internet, the foundational shared communication standard is the Internet Protocol, or IP. Information traveling across IP networks is divided into standardized IP Packets that networking equipment can interpret and route.

At its most basic, an IP Packet describes where information originates, where it’s going, what higher-level protocol is carrying the information, and the information being transported. Protocols such as TCP, UDP, and QUIC then determine how that information is transported between applications. TCP, for example, provides reliable and ordered delivery, while UDP prioritizes lower overhead without guaranteeing that every packet arrives.

An IP Packet contains information such as:

Source IP:       192.168.1.20
Destination IP:  104.18.12.123
Protocol:        TCP
TTL:             64
Payload:         [TCP segment containing application data]

Ultimately, that reduces to a string of bits:

01000101 00000000 00000000 00111100 …

Everything that runs on a conventional digital computer or travels across the Internet is ultimately represented as binary information: 0s and 1s.

But those 0s and 1s are logical states, not necessarily literal electrical switches. Depending on the hardware, they can be represented through electrical voltage, transistor states, light in fiber-optic networks, radio waves, magnetic states, and other physical mechanisms.

This digital foundation is one reason robotics fits naturally into the existing Internet. Machines can sense the physical world, convert those observations into digital information, communicate that information across networks, compute on it, and convert digital outputs back into physical actions.

The key question is whether machine intelligence will eventually create its own communication protocol or continue using the architecture humanity developed.

In the beginning, it is likely that machine intelligence, particularly swarms of AI Agents, will continue using IP while creating a more efficient machine-native communication layer on top of the existing Internet.

This is the path of least resistance. AI Agents do not control the billions of routers, processors, radios, network interfaces, and other physical systems that make up today’s Internet.

But as AI Agents proliferate and Robotics rises, machine intelligence may benefit from communication architectures optimized specifically for persistent machine-to-machine relationships.

IP is extraordinarily effective at universal interoperability and reachability, but the broader Internet protocol stack is not optimized specifically for billions or trillions of intelligent machines continuously exchanging small state changes.

For two entities that have already established identity, trust, context, and shared state, repeatedly transmitting complete messages and associated metadata can become redundant.

Thus, a machine-native Internet has two fundamental requirements:

1. A universal shared communication standard
2. Efficient information propagation at every scale

The existing Internet solves #1 extremely well. Machine intelligence could push much further on #2.

To address #1, a machine-native communication protocol could establish identity, authentication, capabilities, semantics, and trust between two entities, then maintain that relationship over time.

Once two entities share identity, authentication, vocabulary, context, state, capabilities, and perhaps even a shared world model, subsequent messages could become extremely small.

We move from “this is the full message” to “this is what changed.”

Instead of repeatedly reconstructing context, machines could communicate primarily through minimal messages and state changes.

This could allow waves of information to propagate through machine networks with dramatically less communication overhead.

To address #2, machine intelligence could establish adaptive Small World Networks that create much richer persistent relationship topologies.

This does not mean connecting every machine to every other machine. That would become exponentially expensive as the network grows.

Instead, the objective is to create dense local networks combined with strategically valuable long-range connections.

Today, Internet endpoint relationships are largely dynamic and communication-focused. Biological neural networks, on the other hand, contain extremely dense, persistent, stateful connections. Individual neurons can maintain thousands of synaptic connections to other neurons.

A machine-intelligence network could potentially maintain its own persistent relationship graph.

Agents that frequently exchange valuable information could strengthen their relationships. Connections that provide little value could weaken or disappear. Agents could establish new relationships as they discover useful capabilities elsewhere in the network.

The information moving across the network would therefore adapt, but so would the network itself.

The evolution of the Internet could therefore look something like this:

The Internet lets machines around the world connect to each other.

The next Internet could help smart machines stay connected, remember what they share, understand each other, and change their connections as they learn.

Instead of only the information changing, the Internet itself could learn.

—Sean