As artificial intelligence (AI) continues to become more widespread, there is growing interest in decentralized AI. Decentralized AI distances itself from the established dogma of centralized systems, embracing instead an approach that involves distributing AI processing and decision-making across a network of devices. This new way of thinking about artificial intelligence unlocks several characteristics and benefits that make it an attractive option for many applications.
Humans.ai has taken it upon itself to build the AIverse, a multifaceted ecosystem designed to help pave the way towards the decentralized AI future we are heading towards. The solution proposed by Humans.ai fuses artificial intelligence and blockchain, a technology that will play a pivotal role in the upcoming decentralized economy, to set the foundation for an ecosystem that will unite AI developers, researchers and consumers.
As AI is slowly consuming the world, enriching industries and businesses, Humans.ai has made it its mission to assist the transition of artificial intelligence, AI models and AI-based solutions from the centralized Web2 domain, where development is done behind closed doors where giants of the tech industry hold the reigns, to a decentralized paradigm, where AI becomes a democratized asset that is constantly monitored by real humans to ensure its ethical use.
To make its vision of an AI economy a reality, Humans.ai is developing its blockchain platform, a framework tailored to mitigate some of the most pressing issues that revolve around the execution, monetization and governance of AI. But this is just the tip of the technological iceberg, as the Humans Blockchain pushes beyond the limitations associated with blockchain technology like the lack of interoperability, to bring the execution and management of artificial intelligence into the Web3 era. Using Cosmos SDK as a foundation, the Humans Blockchain positions itself as the first interoperable blockchain infrastructure from the Cosmos ecosystem that can store, manage and ethically deploy AI.
A core component of the Humans.ai ecosystem is the Proof of Human (PoH) mechanism, a complex blockchain-based governance, consensus and verification system that ensures that every AI is backed by a human decision. Through PoH, people leverage their biometric data in order to prove that a specific AI is still under close biological supervision. Humans.ai empowers people to participate in the governance and management of any AI, essentially making sure that the objective of the AI is aligned with the human’s objective.
Proof of Human is a vital component of the Humans.ai blockchain, acting as a governance, consensus and verification system, which helps ensure that behind every AI, there is a human decision. Simply put, PoH is a complex and versatile mechanism that ensures three key functions related to decentralized AIs: governance, consensus and verification.
To ensure the governance of decentralized AI, Humans.ai utilizes Proof of Human to confirm that behind every request made towards an AI, there have been multiple digital signatures of real people. The digital signatures in question are generated through a mix of different data such as private keys and biometric data (fingerprints, heartbeats, retina scans, face recognition etc.)
With its technology, Humans.ai empowers people to be validators and participate in the governance, management and deciding the fate of any AI. This essentially makes the system ethically compliant, ensuring that the AI plays fair under the supervision of real humans and that its objective is aligned with the rules outlined by its creator or owner.
Proof of Human helps boost the accuracy and reliability of decentralized AI systems. By ensuring that the entities interacting with the system are indeed human, the ecosystem developed by Humans can avoid the risk of automated bots or other malicious actors manipulating AI. This feature improves the accuracy and reliability of the system, making it more effective for a wide range of applications.
One of the main characteristics of decentralized AI is that it enables privacy and security. In a centralized system, all data is stored in a single location, making it more vulnerable to hacking and other cybersecurity threats. In contrast, a decentralized AI system stores data across a network of devices, making it more difficult for hackers to hijack sensitive information because there is no single point of failure.
All the data is distributed across multiple systems and users. This design choice is particularly useful for applications that involve sensitive information, such as finance, healthcare and government records.
Another valuable characteristic of decentralized AI is that it is more efficient. With centralized AI systems, all processing takes place in a single location, which usually leads to bottlenecks and traffic congestion that results in slower response times. In contrast, a decentralized system distributes processing across a network of devices, enabling faster and more efficient processing, making it invaluable for applications that require real-time decision-making, such as autonomous vehicles.
In addition, decentralized AI is more scalable than centralized AI. With a centralized system, adding more processing power requires expensive hardware upgrades. This is known as vertical scaling, the process through which a system is upgraded with more powerful equipment to increase its performance. The main drawback is that high-tech equipment leads to a huge spike in costs. In contrast, a decentralized system scales more efficiently by simply adding more devices to the network. This is known as horizontal scaling, which is a more cost-effective and flexible option for applications that require varying levels of processing power.
One technology that can help make decentralized AI a reality is blockchain. Blockchain is a decentralized, distributed ledger that allows for secure and transparent transactions without requiring intermediaries. Using blockchain as a foundation, decentralized AI can benefit from increased transparency, security and enhanced scalability.
Blockchain lives up to the hype by positioning itself as a technology that acts as a foundation for the decentralized future. In the case of decentralized AI, blockchain ensures that AIs are distributed across a network of devices, ensuring a tamper-proof ecosystem that provides unparalleled levels of security and transparency.
Another feature that makes blockchain shine is its ability to facilitate the management of incentives in a decentralized AI system. By using blockchain, incentives can be managed transparently and securely, allowing for fair and democratic voting-based decision-making for all the stakeholders involved. This is particularly important for applications that involve multiple parties across a vast chain of operations, such as supply chain management or environmental monitoring.
Finally, blockchain can help with the scalability of decentralized AI systems. With a decentralized system, adding more devices to the network can increase processing power and enable more computationally complex applications. Blockchain streamlines the scalability of AI applications by allowing more people to join the network without compromising security or efficiency.
Overall, blockchain provides powerful benefits that make decentralized AI efficient and effective in the long run. As the use of AI continues to grow, we can expect to see more applications and use cases for blockchain-enabled decentralized AI in the future.
Decentralized AI ushers in a new way of thinking about artificial intelligence, making this powerful technology available to a wider audience.
Probably the most meaningful benefit of decentralized AI is that it is more democratic, meaning that anyone, including people that aren’t necessarily tech-savvy, can use this technology and become part of the emerging AI economy.
Decentralized system work by distributing control across a network of devices, making it more democratic and transparent. The enhanced levels of traceability facilitated by decentralized AI make it ideal for applications that involve multiple stakeholders, such as environmental monitoring or supply chain management.
From a security standpoint, decentralized AI outpaces its centralized counterpart. In a centralized system, a single point of failure can unleash a chain of events that can lead to delayed services, compromise of sensitive information and even an entire system shutdown.
By design, decentralized systems mitigate the single point of failure issues inherent to centralized systems. This is because decentralized AI systems are distributed across a wide network of devices. Even if one or multiple devices fail, the AI system will continue to run as there is no single point of failure. With enhanced levels of resilience, distributed AI systems can unlock a new area of opportunities for domains that require high levels of reliability, such as disaster response or emergency services.
To sum up, decentralized AI has many characteristics and benefits that make it an attractive option for many applications. It enables privacy and security and is more efficient, scalable, democratic, and resilient than centralized AI. It’s safe to assume that as the use of AI continues to grow, we can expect to see more applications and use cases for decentralized AI in the years to come.
As artificial intelligence continues to become more widespread, there is growing interest in decentralized AI. Humans.ai has taken it upon itself to build the AIverse, a multifaceted ecosystem designed to help pave the way toward the decentralized AI future.