Qubic’s Layer 2 solutions, feeless transactions, quorum-based consensus, and AI innovations

Qubic's groundbreaking approach to merging blockchain and AI took center stage in Episode 21 of #LetsTalkCrypto. Eric, APAC lead of growth, and Albert, Representative LATAM, from Qubic, shared insights into their innovative Useful Proof-of-Work system that powers AI training, their quorum-based governance model fostering community-driven decisions, and the integration of their Layer 2 solution, Aigarth. Here are the takeaways from this epic AMA session.

John from LetsExchange: Could you elaborate on how Qubic's quorum-based consensus protocol differs from traditional blockchain consensus mechanisms and what advantages it offers regarding security and scalability?

Eric: Qubic's quorum-based consensus protocol functions as a voting system where significant network decisions require approval by at least 66% of the miners. This structure differs from traditional blockchain mechanisms that often rely solely on proof-of-work or proof-of-stake validations. The quorum model supports enhanced security as it ensures broad agreement before enacting changes, reducing the risk of network disruptions or centralized control. Scalability benefits stem from its adaptive nature, allowing the network to incorporate necessary changes efficiently while maintaining decentralized control.

John from LetsExchange: Qubic utilizes a Useful Proof-of-Work system where mining contributes to AI training. How does this process work, and what are the tangible benefits for both the network and the AI models being trained?

Eric: Qubic's Useful Proof-of-Work (uPoW) system harnesses mining power not just for traditional validations but to contribute computational power toward training AI models. In this system, mining solves complex tasks that directly support developing and enhancing the AI model, ARIA. The tangible benefits include maximizing the use of computational energy for dual purposes: maintaining blockchain security and advancing AI training. This setup promotes efficient resource use, ensures energy expenditure leads to meaningful advancements, and incentivizes miners with rewards linked to AI training contributions.

John from LetsExchange: Can you provide more details about Aigarth, Qubic's Layer 2 solution? Specifically, how does it integrate with the main network, and what enhancements does it bring to the platform's capabilities?

Eric: Aigarth is our advanced AI system built atop the Qubic network. It leverages the computational power of miners to drive AI advancements, aiming to democratize access to sophisticated AI capabilities. By integrating seamlessly with our main network, Aigarth enhances our platform's ability to process complex tasks and evolve over time.

John from LetsExchange: Qubic offers feeless transactions, which is relatively uncommon in blockchain platforms. How is this achieved, and what impact does it have on network sustainability and user adoption?

Eric: Our feeless transaction model is made possible through our unique consensus mechanism and efficient network design. By eliminating transaction fees, we lower barriers to entry, encouraging broader user adoption and fostering a more inclusive ecosystem.

Koin Brainiac (community question): Qubic employs a democratic governance model. Could you explain how decisions are made within the community?

Eric: Qubic’s governance model is indeed democratic and relies on a quorum-based system. For any major changes or decisions regarding tokenomics or AI development, we need at least 66% approval from the network's miners. This ensures the community has a significant say in the project's direction. For example, we had an instance where the community proposed an 80% supply cut, and once it was put to a vote and passed, we implemented it. This process highlights the power of collective decision-making and keeps the ecosystem transparent and community-driven.

Tolga (community question): Is Qubic using pre-existing AI models or training from scratch?

Eric: At Qubic, we build our AI models entirely from scratch. We chose this path because existing large language models (LLMs) and AI frameworks cannot achieve true artificial general intelligence (AGI). Starting from the ground up allows us to create a system that can develop sentient intelligence without the limitations of pre-existing structures. This approach sets us apart and pushes the boundaries of what’s possible in the AI and blockchain space.

These are just the main highlights of the AMA session. To learn more about Qubic, listen to the full AMA.