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Artificial Intelligence (AI) is a hot topic, revolutionizing the world at an unprecedented pace.
While some may fear its impact, others see it as a welcome change. Regardless of the perspective, there’s no denying that AI is dramatically altering our daily lives.
As it stands, the primary beneficiaries of the AI race are major corporations like Microsoft and Google.
Not only financial gain is a concern, but these gains come with concerns over security and unethical practices.
To counterbalance the dominance of these large corporations there is another development taking place called Decentralized AI.
This groundbreaking approach to AI is not just a minor improvement on existing systems; it represents a fundamental shift in how we conceptualize, develop, and interact with artificial intelligence.
Do not further a due let’s understand what Decentralized AI is, why it matters, and how it’s poised to transform industries across the board.
What is Decentralized AI?
As a name, the AI running a Decentralized database is simply called Decentralized AI.
Current AI tools like Chat GPT running on a centralized server controlled by the company itself. The same goes with Google Gemini and other tools.
However, Decentralized AI is running on blockchain. There is no single point of weakness.
Decentralized AI distributes data storage and computational power across a network of nodes.
In a decentralized AI system, users can leverage pre-trained AI models on their local devices, benefiting from AI-generated insights without relinquishing control of their data to a central authority.
This distribution enhances security, privacy, and democratizes access to AI technology.
Features of Decentralized AI
Distributed Computing
Unlike the other AI tools, which rely on the centralized database.
Computations are spread across multiple nodes in the network.
Data Privacy
Users maintain control over their data, deciding what to share and when, ensuring their privacy is preserved.
Resilience
The system is less vulnerable to single points of failure or attacks.
Transparency
AI decision-making processes become more visible and auditable, fostering trust in the system.
Open Participation
A wider range of individuals and organizations can contribute to and benefit from AI development.
Power Of Decentralized AI
Data Privacy
Decentralized AI solves the most concerning issue of data privacy by allowing users to maintain and control their data.
Here is how it does:
Local Processing
Users’ data is processed on the user’s device with only the insights or aggregated results being shared.
Encrypted Sharing
Decentralized AI uses the blockchain, which is encrypted and protected.
When data needs to be shared, it can be done using advanced encryption techniques.
Consensual Use
Users have control over how their data is used and can revoke access at any time.
Privacy protection not only helps individuals’ privacy but also helps companies comply with stringent data protection regulations like GDPR.
Transparency
Transparency is another issue with centralized AI, where there’s no clarity behind the project decision making process.
Decentralized AI aims to crack open this box, making AI decision-making processes more visible and understandable.
This is achieved through:
Open Source Algorithms
Decentralized AI projects make their code publicly available for scrutiny.
The distributed nature of the system allows for better tracking of how decisions are made.
Community Governance
Stakeholders collectively decide on the development and use of AI, ensuring a more democratic approach.
Reduce Monopoly
Currently, players like OpenAI and Google are dominating the Ai race with the resources to build and maintain massive AI systems. Decentralized AI levels the playing field by:
Lowering Barrier to Entry
Decentralized AI encourages and lets small companies and individual developers contribute to and benefit from AI development.
Preventing Data Hoarding
Preventing any big companies controlling the vast amount of data needed to train advanced AI models.
Encouraging Competition
By lowering the entry barrier and diversifying the AI ecosystem leads to increased innovation and better services.
Increased Innovation
By opening AI development to a large community. Decentralized AI encourages an environment for innovation in ways like:
Rapid iteration
Decentralized systems often adapt and improve more quickly than centralized ones.
Diverse Perspective
Different people from different backgrounds bring unique insights and approaches.
Specialization
Different nodes in the network can focus on specific tasks or domains, leading to more advanced and tailored AI solutions.
Challenges and Consideration
While Decentralized AI holds enormous potential, it is not without challenges:
User Adoption
Honestly, can you switch over to the decentralized AI project over to Open AI, Gemini?
Convincing users to switch from familiar centralized systems to decentralized alternatives can be difficult.
Technical Complexity
Centralized AI systems are complicated. Even more complicated ones are decentralized ones.
Regulatory Landscape
Still, it is not sure how every corner of the world welcomes the Decentralized AI developments. It may face regulatory hurdles in some sectors.
Performance
Distributed computing can sometimes be slower than centralized systems for certain tasks.
Standardization
Interoperability is challenging between different decentralized AI systems.
List of Decentralized AI Platforms
Numerai
Established in 2015, one of the first ever projects to integrate AI with Blockchain.
Numerai is an Ethereum based hedge fund. Using AI to create machine-learning models for stock market predictions.
For creating the models Numerai uses the weekly tournament.
First, users are given existing datasets that have been modified so that there is no way of knowing what assets they refer to. Then, these users participate in weekly tournaments by submitting predictions their data models generated.
These predictions are applied to new sets of market data by Numerai.
This approach relies heavily on AI-generated data predictions, making it one of the few hedge funds to do so.
They also expanded into decentralized finance (DeFi) with the introduction of Erasure, a decentralized marketplace that allows users to buy and sell predictions and data over the Ethereum blockchain.
Ocean Protocol
Ocean Protocol is built upon the Ethereum blockchain. Aiming to revolutionize data sharing.
In the technology era, data is the new fuel, and ocean protocol is enabling access to this fuel for individuals and businesses.
Protocol offers a blockchain ecosystem for businesses and individuals to come together to exchange data. Furthermore, they can also exchange data-driven services among themselves.
As an individual, you can convert in-depth analysis, research, etc to “datatokens”, which represent the ownership.
You can choose to list datatokens on the Ocean Market, where they can be traded for OCEAN (ocean protocol’s native cryptocurrency), monetizing their data while still ensuring security.
OCEAN tokens serve multiple functions within the ecosystem. It is used for purchasing datatokens, participating in governance decisions through voting, and staking by token holders.
The dataset available on the platform is helpful for the business and more for the AI developers, AI developers can take advantage of a wealth of datasets to train sophisticated models.
Render (RNDR)
Render is an Ethereum based platform using AI to decentralize GPU power.
GPUs are necessary for graphics, games, and even building AI models. The platform allows people to contribute their unused GPU power to a decentralized marketplace for people who want GPU power to rent.
For giving the GPU power, one gets the native token RNDR. The platform allocates idle GPU power from across the globe for 3D rendering tasks, creating a scalable peer-to-peer GPU cloud computing network.
Render blockchain is not only capable of handling all the complex work of the platform but also manages the digital rights to their work using on-chain traceability. This protects the intellectual property of creators while providing a level of transparency and security not possible with traditional systems.
Fetch.AI
Fetch.AI combines three powerful technological forces, blockchain, AI, and automation, to help businesses streamline the process.
By using the blockchain, Fetch.AI deploys bits of codes it calls “autonomous economic agents (AEA)” that can perform meaningful activities on the Fetch.AI network, such as transactions, negotiations, collaboration, chatbot development, industrial process automation, IOT network connectivity, DeFi, and much more.
It is the first open network for AI agents, which are modular building blocks that can be programmed with logic to perform specific tasks.
Applications of Fetch.ai span multiple industries, including supply chain and logistics, transportation, finance, and smart city.
Fetch.AI aims to provide the tools for developers to deploy and monetize applications by providing an autonomous machine-to-machine ecosystem.
In finance, developers could utilize Fetch.ai to create autonomous trading agents that execute trades based on AI predictive models, potentially improving market efficiency and liquidity.
Autonolas
Autonolas is different from the above platform, focusing on the development of autonomous applications on the blockchain that operate continuously and independently.
Autonolas positions its applications as off-chain services, yet secured on-chain. The innovative capabilities of the application strengthen its on-chain functionalities.
The project has various toolkits, for creation of a wide array of autonomous services.
Open Autonomy framework
This is a tool for developing agent services, which are off-chain autonomous services operating as a multi-agent system (MAS).
Autonolas Protocol
The Autonolas Protocol is a collection of smart contracts designed for managing and securing software on public blockchains.
Autonolas DAO
Inspired by Compound’s model and OpenZeppelin’s architecture. The Autonolas DAO employs a complex governance system based on smart contracts.
And the tockenomics surrounding the Autonolas artificial intelligence blockchain project supports the growth of the ecosystem.
Conclusion
Decentralized AI is not just a technology advancement. It is paving the way for a more equitable, innovative, and secure future by embracing principles of transparency, privacy, and collaboration.
Still, more to come, but it is worth exploring the new use cases, or rather an entirely new segment of blockchain.
The journey towards fully realized Decentralized AI may be long and complex, but the destination is undoubtedly exciting.
Decentralized AI: The Revolutionary Force Reshaping the Future of Artificial Intelligence was originally published in Coinmonks on Medium, where people are continuing the conversation by highlighting and responding to this story.