In this episode of Blockcrunch Podcast, which took place on April 25, Jason and Sam discuss the founding story of Arweave, solving infinite scalability, smart contract transferability, and breaking down actor-oriented computing. Read our notes below to learn more.
Background
- Jason Choi (Host) – Angel at Tangent
- Sam Williams (Guest) – CEO of Arweave
- Arweave – information store network
The history of AO
- Sam says that the approach of lazy evaluation in computer science is relevant to smart contracts. Lazy Ledger (later Celestia) was one of the early adopters of this concept in 2020, emphasizing the potential for improved scalability in computational systems. Introducing asynchronous messaging between smart contracts using Arweave as a message bus enables parallel computation, offering a solution for scalability challenges.
- He adds that current smart contracting systems operate on global synchronized states with a single leader writing to the network over time, limiting scalability.
- Sam says that the system developed facilitates arbitrary numbers of parallel virtual machines with an asynchronous message bus for inter-process communication, enhancing computational capacity. Unlike traditional networks such as Ethereum or Solana where adding more computation power does not increase output proportionally, this system scales output with added computation capacity.
Infinite scalability
- Sam draws inspiration from the history of computation, Arweave’s design results in a decentralized computing network resembling a single computer, offering enhanced scalability and efficiency. Compared to Ethereum’s limitation where adding validators does not speed up the network due to a single block proposer structure, this new design leverages infinite scalability by increasing actors within the network leading to faster processing speeds.
- He adds that the process involves sending a token to a contract which then triggers messages such as credit notices to the receiver and debit notices to the sender. This communication occurs asynchronously without synchronization.
- Sam says that Ethereum is like a giant machine where interactions between smart contracts feel seamless, creating a sense of using one massive system.
- He adds that AO allows for building programs within a shared environment akin to everyone sharing a scientific calculator, enabling communication and composability between different actors.
- Sam says that in AO programming, coordination happens through message passing rather than shared memory, offering an intuitive approach for large-scale systems compared to traditional shared memory systems.
- He adds that in AO programming, every computation is viewed as an actor capable of communicating with others through messages, fostering an intuitive way of handling interactions within the system.
ELI5: Actor Oriented computing
- Sam says that individuals possess unique skills and tasks in a decentralized system. They communicate by exchanging notes or messages. Act-oriented programming mirrors human behavior in a decentralized computing system.
- He adds that act-oriented programming mirrors how individuals and collectives achieve tasks similarly to human interactions.
Composability trade-offs
- Sam says that act-oriented programming allows for interactions with different applications without shared memory limitations.
- He adds that each pair runs on its asynchronous process, enhancing scalability within act-oriented programming.
- Sam says that centralized exchanges scale by creating multiple order books for increased capacity similar to act-oriented programming’s approach.
- He adds that blockchain systems now support large-scale computations alongside traditional DeFi composability features.
- Sam says that hyper parallel computing models like Solana offer efficient scaling solutions by distributing computation across multiple nodes.
- He adds that parallel computation mechanisms optimize memory usage by resolving transactions into blocks efficiently.
- Sam says that distributed computation enables long-running computations without intermingled memory, ideal for AI use cases.
- He adds that future advancements may lead to autonomous finance where intelligence complements settlement layers within financial systems.
Removing on-chain AI training restraints with AO
- Sam says that Autonomous Finance envisions embedding intelligence into financial systems beyond mere settlement layers. Intelligence is embedded within a system, offering smart contract-like guarantees.
- He gives an example in which personal finance processes in AO can intelligently manage portfolio rebalancing based on specific criteria like token percentages or stablecoins. Advanced Use Case: Algorithmic trading fund entirely on-chain for autonomous operation with smart contract guarantees.
- Sam says that on-chain training and execution are feasible, unlike current blockchains limited by scale constraints. Challenges with existing systems due to tying execution with consensus, hindering scalability.
Security trade-offs
- Sam says that AO functions as a data protocol built atop AIV, ensuring process integrity and message authenticity. Utilization of a proof-of-authority system for consensus in subnets ensures secure transaction handling.
- He adds that the implementation of a decentralized proof-of-stake network safeguards subnets for secure transaction flow.
The blockchain trilemma
- Sam says that the blockchain trilemma involves balancing security, scalability, and decentralization in blockchain design. Different blockchain designs offer varying trade-offs within this trilemma framework. The concept of the trilemma serves as a base layer framework for implementing diverse security systems with individual trade-offs rather than being prescriptive.
- He adds that a developer from the ICP community created a graphic illustrating how ICP, Bitcoin, Ethereum, and others relate to each other compared to AO’s expansive design space. Depending on user requirements and processes, selecting an appropriate spot in the design space allows for tailored solutions within AO’s flexible framework. Despite initial surprise from some members of the ICP community regarding AO’s capabilities, there was openness to understanding the differences and advantages offered by AO.
AO’s extensibility
- Sam says that the interactive nature of using AO allows for activities like chatting with friends inside the machine while building projects interactively. Other languages used for smart contracts are derived from systems programming languages focused on efficiency rather than interactivity or forgiveness found in AO.
- He emphasizes the need to reset expectations about programming at a high level and instead focus on computational abstracts without worrying about memory allocation.
- Sam describes the concept of “high-level abstraction” in programming as simplifying the mind from managing computer tasks, allowing focus on problem-solving without distractions.
- He highlights AO offers simplicity and flexibility akin to JavaScript but without complexities like memory management, contrasting it with the intricate nature of writing at the assembly level in Solidity for gas optimization.
- Sam compares writing in Solidity to handling complex tasks like memory management and assembly-level programming for gas optimization, which can distract developers from app development.
- He warns against mixing efficiency-driven coding practices with financial primitives due to potential catastrophic outcomes, drawing parallels between low-level development challenges and driving a car while simultaneously tweaking its engine.
AO ecosystem builders
- Sam envisions a future where decentralized markets evolve from fun games with bots into fully decentralized intelligent markets on-chain, highlighting how building better bots can lead to token earnings similar to market dynamics.
The AO roadmap
- Sam says that the team prioritizes security-sensitive matters and avoids rushing into decisions. He talks about not labeling a project as being in “mainnet” until they are confident that core specifications won’t change.
- He adds that the line between centralized startups, products, and protocols has blurred significantly. He emphasizes that a protocol should serve as a neutral language for multiple participants to achieve tasks. Constant changes in protocols can lead to users losing rights within economic systems like Ethereum during transitions such as proof-of-stake switchovers. This undermines the essence of real protocols offering user protection.
- Sam acknowledges Ethereum’s achievements in smart contracts and decentralized finance but questions its ability to provide users with substantial rights akin to true protocols outside the crypto realm or Bitcoin itself.
Check out these important links
- Listen to the original episode
- Follow Jason Choi on Twitter
- Follow Sam Williams on Twitter
- Follow Arweave on Twitter
Show Information
- Medium: Youtube
- Show: Blockcrunch Podcast
- Show Title: AO: The Hyper Parallel Computer You Need to Know – Sam Wiliams, Ep. 255
- Show Date: April 25, 2023