Rethink AI and Crypto: The Future Belongs to AGI
Written by
The Qubic Team
Nov 16, 2024
Right now, the intersection of artificial intelligence and cryptocurrency is, to put it bluntly, limited in its vision. While the possibilities of this pairing are vast, much of the current landscape is narrowly focused on training large language models (LLMs), optimising DeFi protocols, or creating trading bots. Valuable tools, yes - but they barely scratch the surface of what’s possible.
When AI and crypto first began to converge, it promised a world of transformative possibilities. But as it stands, we’re seeing AI-crypto applications focus most of their efforts on automated trading, speculation, and incremental model improvements. Is this the best we can do? Imagine a broader vision - one in which the fusion of AI and crypto is directed toward truly monumental challenges, with the potential to create outcomes that matter on a global scale. We need to move beyond bots and LLMs. The true potential lies in something much larger, more ambitious, and more meaningful for humanity: Artificial General Intelligence (AGI).
AGI promises not just an advanced AI but an intelligence that can learn, reason, and adapt across tasks with human-like versatility. At Qubic, we believe that the blockchain space should strive for AGI rather than focusing on limited AI solutions. This post explores why we need to expand our vision and how Qubic’s Aigarth initiative is developing a new standard.
The Current State of AI in Blockchain: Limited Applications
The majority of AI efforts in the blockchain space currently focus on specialised, narrow applications. While there are ambitious visions in the industry, practical deployments often prioritise immediate, task-specific needs. Listed below are some of the main areas where blockchain AI projects are concentrated:
Trading Bots: Many blockchain AI projects have focused on creating high-frequency trading bots that can seamlessly act on market movements with great speed and accuracy. Primarily, these bots serve a specialised function within financial markets and are aimed at maximising returns rather than exploring the broader potential of AI.
DeFi Optimization: Other projects put AI to use for optimising DeFi protocols, which involve tasks like yield farming, liquidity management, and asset allocation - all of which have value within DeFi but remain very narrow and specialised.
Data Processing and Task Automation: Some blockchain projects have incorporated Large Language Models, along with machine learning algorithms, into data processing, customer services, task automation, and predictive analytics. While useful, these tools fall short of the adaptive, multi-domain learning needed for Artificial General Intelligence (AGI).
However, some projects, like SingularityNET and Fetch.ai, have broader goals that go beyond narrow AI applications. SingularityNET envisions a future with AGI but currently focuses on providing individual AI services through a decentralised marketplace. Qubic’s Aigarth, in contrast, aims for a unified, evolving intelligence that transcends narrow applications. Fetch.ai is developing networks of autonomous agents for complex, multi-agent tasks across supply chains, energy grids, and mobility. These projects have long-term visions, hinting at AGI aspirations, but their current implementations still lean toward specialised functions.
For now the practical applications remain narrow and specialised, leaning towards more immediate utility rather than advancing toward AGI. Achieving AGI is about creating an intelligence capable of handling multiple, diverse tasks without human intervention. To achieve this, we need a different approach, one that combines decentralisation, community ownership, and the utilisation of resources in a meaningful way.
A New Vision for AI and Crypto: Aiming for AGI
Crypto has the potential to radically reshape how we approach AGI development. Here’s what a more ambitious AI-crypto vision could look like:
AI as a Public Resource: Imagine, instead of centralised AI capabilities within corporations, a decentralised network where computational power is shared for the development and training of AGI. Just like blockchain decentralised financial systems, we could do the same with AI, empowering communities around the world to make AGI accessible to all.
Decentralised AI Training: Useful Proof of Work (uPoW): Useful Proof of Work is a concept in which mining is redefined to direct computational resources to train AI rather than performing arbitrary calculations. It allows AI training at scale through a network of miners across the world, rather than just "wasting" energy, as with traditional Proof of Work models. It is not just a matter of creating a blockchain; it's about creating a system that furthers AI development in a decentralised manner, driven by community support rather than corporate interests.
Interdisciplinary AI Models Beyond LLMs: While LLMs are powerful, AGI would move beyond narrow applications by combining skills across multiple disciplines. Instead of just focusing on generating text or analysing financial data, AGI could tackle complex, real-world issues, from climate modelling to medical research. Through the combined power of crypto and AI, decentralised AGI could provide valuable insights to industries that need it most.
Enter Aigarth: Qubic’s Road to Decentralised AGI
Qubic’s Aigarth initiative is pursuing a decentralised, community-driven AGI. Instead of prioritising narrow applications, Aigarth is designed to build toward an intelligence that can grow and learn on its own.
Aigarth’s trinary computing architecture and its focus on training artificial neural networks (ANNs) in order to replicate the human evolutionary process distinguish it from other projects, enabling scalable, adaptive learning that evolves autonomously in its pursuit for AGI. This approach allows Aigarth to continuously improve its intelligence without relying on centralised oversight or task-specific constraints.
AGI development requires immense computational resources and extensive training. Centralised models often struggle with the sheer scale required, creating bottlenecks and consolidating control within single organisations. Qubic’s approach is fundamentally different, harnessing its Useful Proof of Work (uPoW) model to power AGI development through a global network of miners. By distributing the computational burden across its network, Qubic enables a more sustainable, inclusive path to AGI.
Comparative Look: How Current AI-Crypto Approaches Fall Short
To better understand why a shift toward AGI is essential, let’s compare today’s AI-crypto applications with what AGI could achieve:
This comparison makes it clear: the current focus of AI-crypto applications is far too narrow and misses the greater potential impact of combining these technologies. AGI offers the possibility of an intelligence capable of adapting, learning, and contributing across industries. Decentralised AGI could function as a public utility, directly impacting fields such as medicine, environmental science, and engineering.
Comparisons with Existing Blockchain AI Projects
Let’s explore how Aigarth’s decentralised approach compares to other blockchain-based AI projects:
SingularityNET: Known for its decentralised marketplace of AI services, SingularityNET allows developers to upload and monetize AI models. However, its focus remains on providing individual AI services rather than a unified AGI. Aigarth aims for an autonomous, evolving intelligence rather than a collection of narrow AI services.
Fetch.ai: This project is focused on autonomous agents that interact to achieve better performance in tasks such as supply chain or energy grid management. While Fetch.ai introduces intelligence on a decentralised level, its agents are still task-specific. Aigarth, on the other hand, focuses on creating general intelligence capable of learning and adapting to a wide variety of contexts.
Ocean Protocol: Ocean offers decentralised access to data for AI training but is not directly involved in the pursuit of AGI. Aigarth intends to utilise data for broader, more generalisable intelligence.
Tao (TAO Network): Tao builds infrastructure for decentralised AI applications, allowing developers to create and monetize individual AI models. While this provides a valuable platform for AI on the blockchain, it focuses on facilitating AI services rather than developing a unified general intelligence. Aigarth, in contrast, is focused on creating an AGI that grows and adapts autonomously.
Each of these projects has made significant contributions to AI and blockchain, but they all remain within the boundaries of narrow AI, specialised tools, or infrastructure support for individual models. Aigarth, by comparison, is pursuing an ambitious goal: a decentralised AGI that serves as a shared, community-driven intelligence.
Why Now? A Call to Move Beyond Short-Term Gains
The technology and infrastructure to move toward AGI are within reach. The computing power distributed across crypto networks could be applied to something far more meaningful than trading or narrow AI tasks. With developments in decentralised AI, such as Aigarth and the UPoW model, we have an opportunity to move away from financial speculation to scientific advancement.
Imagine a decentralised AGI that revolutionises global healthcare with real-time diagnostics, optimises energy usage for environmental purposes, or accelerates scientific discovery by autonomously generating and testing hypotheses. This vision transcends the limitations of current blockchain AI projects, highlighting the transformative power of a decentralised approach to AGI.
Time to Rethink the AI-Crypto Vision
If AI and crypto are to reach their full potential, they need to aim higher. We should no longer settle for incremental trading optimisations or limited language models. The future lies in AGI, an intelligence that transcends narrow applications and brings meaningful change across disciplines. By moving beyond proprietary tools and embracing decentralised AI, we can create a future where AI is not just powerful but also purposeful, collaborative, and beneficial for all.
Aigarth redefines what is possible with blockchain-based AI by setting its sights on creating a shared, community-driven intelligence. In an industry focused on trading algorithms and task-specific AI, Aigarth represents a shift - toward a more ambitious, meaningful goal. Qubic is the chain that creates AGI.
Join the Discussion
What is the global problem that you would want to see decentralised AGI address? How might decentralised AGI affect fields such as finance, science, or education? Ready to be a part of this transformation? Join our Aigarth and Qubic community on Discord and Telegram to ask questions, provide insights, and engage with other people interested in pushing the boundaries of what AI and blockchain can achieve together.