AO Consensus and Holographic State

Author: Kevin Primicerio, Cofounder of Pianity

Translation: Xiaosong Hu

Learn how AO's holographic state revolutionizes blockchain scalability, using Arweave's immutable log to reach consensus without compromise. A new era of efficient, scalable decentralized computing is coming.

AO computers reach consensus through "holographic state" and use Arweave's immutable message log to break through traditional scalability limitations. This approach marks a significant evolution from existing systems such as proof-of-work and proof-of-stake, paving the way for a new era of efficient, scalable decentralized computing

Enter title for understanding traditional consensus mechanisms

Blockchains such as Bitcoin and Ethereum use consensus mechanisms to allow network participants to agree on the state of the ledger, including transaction verification, account balances, or smart contract execution results.

Bitcoin pioneered decentralized consensus through proof-of-work (PoW), where miners add new transaction blocks by solving puzzles. This consensus ensures the consistency of transaction history and makes unauthorized tampering almost impossible without significant computing power.

Ethereum uses proof-of-stake (PoS) to achieve consensus through staking transaction verification and block creation. The goal is to reduce the energy requirements of PoW.

By requiring all nodes to verify and agree on every transaction or contract execution, these mechanisms often limit the speed and throughput of the network, creating significant barriers to scalability.

L2 Solutions and Path Forward

Layer 2 (L2) solutions are critical to overcoming scalability and energy consumption barriers. While L2 solutions such as Rollups and sidechains aim to offload the transaction burden from the main blockchain to achieve higher throughput and efficiency, AO’s model leverages Arweave’s immutable storage capabilities to ensure scalability and reduce computational overhead. This strategic alignment with L2 principles, albeit at a fundamentally different architectural level, underscores AO’s commitment to enhancing decentralized computation.

Holographic States: A Paradigm Shift

Process state is not typically stored or agreed upon in AO systems. Instead, they are “holographically” implicit in the message log hosted on Arweave. This ensures consistency of output at the time of computation, even if network participants have not yet observed/computed it.

Hence, holographic states represent the state of a process, inferred from the immutable message log on Arweave, without the need for real-time computation or consensus.

This means that the cost of computation is delegated to users who can compute its state or request execution through compute units (CUs). The use of deterministic, metered VMs ensures that: no matter who performs the computation, given the same input (message log), its output (state) is always the same.

This concept leverages the lazy evaluation architectural principles of SmartWeave and Celestia to enable unconstrained use and scaling of resources in a process.

Why is this important?

The impact of this shift is significant. By decoupling the consensus mechanism from the computational state, the AO computer solves the scalability problems that plague traditional blockchain networks. This opens up new possibilities for decentralized applications, allowing them to run without the memory size, form, and speed constraints of current consensus models.

In addition, the holographic state model creates a more flexible and efficient computing environment. Developers can create and deploy processes on the AO computer without worrying about the computational load on the network. In turn, users can interact with these processes and be confident that the underlying state is verifiable and secure, thanks to the immutable message log on Arweave.

Frequently Asked Questions

Here are answers to some of the most common questions I get on Discord and Twitter

How does the holographic state mechanism in AO work?

Nodes in the network do not need to perform computations to reach consensus on program state transitions, but instead derive state from a log of interactions (messages) stored on Arweave.

This design leverages the Arweave network’s immutable storage to ensure that the message log is permanently available, allowing any network participant to compute state.

How are processes managed and executed distributedly?

Processes are managed and executed through a combination of Scheduler Units (SU), Compute Units (CU), and Messenger Units (MU).

These components work together to handle the distribution of messages to processes (SU), compute state transitions based on messages (CU), and relay messages between processes (MU).

This architecture allows processes to run independently on the network. For an in-depth explanation, see my detailed article on AO Architecture.

Article link:

https://thenextwave.blog/aos-modular-architecture-computing-model-part-ii/

Is the state of a process directly observable, or is it just implicit?

The state of a process is primarily implicit in the interaction log stored on Arweave. While the state is not stored, any participant can deterministically compute it. This approach ensures that the state of a process, while not directly observable, can be independently verified and remains consistent across the network.

How do deterministic, metered virtual machines contribute to the holographic state?

Computational units are deterministic, metered virtual machines (VMs). They ensure that given the same input (message log), the output (state) remains consistent, regardless of who or where the computation was performed. This consistency is critical to the holographic state model, enabling trustless verification of state transitions. The resource metering feature of the VM ensures that computations are constrained, preventing runaway processes and maintaining network efficiency.

What are Resource Metered VMs?

Resource Metered VMs are designed to precisely control and track the usage of computational resources, such as CPU runtime and memory. This capability ensures fair access to network resources, prevents abuse, and provides predictable operational costs, and is critical to maintaining network efficiency and scalability, as well as providing a transparent and manageable economic model for developers and users.

What is the scalability impact of the holographic state model?

The holographic state model has a significant positive impact on scalability. By decoupling the consensus mechanism from the actual state computation and leveraging a distributed network of participants to execute processes, AO can support many parallel processes without the typical constraints of traditional blockchain consensus mechanisms. This model allows for more significant scalability, as the network can handle more transactions and complex computations without a proportional increase in resource requirements or a decrease in performance.