The intersection of AI and cryptocurrency

The artificial intelligence (AI) industry has been making headlines lately for both the good and the bad. While we may be well aware of the recent buzz surrounding OpenAI and its capabilities, we may not have explored much about how artificial intelligence can interact with systems on the blockchain. In today's article, we will cover some of the applications that are currently trying to leverage both artificial intelligence and blockchain technology, along with some information regarding the future of these applications and the industry. artificial intelligence in the coming years.

What is AI and how does it relate to cryptocurrency?

Before getting into project specifics and technical issues, we need to cover some basics about artificial intelligence technology and how the teams and developers in The industry has brought us to where we are today.

Chances are you're familiar with ChatGPT, the popular and widely recognized AI application that has attracted the attention of the tech industry over the past year – so today we'll briefly explain the concepts that make the foundation for this technology as well as how it fulfills basic requests from users.

The core of the technology that powers ChatGPT and its user conversation-based models is the large language model (LLM). These complex pieces of AI technology are essentially a combination of deep learning techniques/algorithms and very large data sets that work together to create an artificial intelligence model with predictive capabilities. and summarize knowledge.

Interactions between humans and LLMs are handled through natural language, with most LLMs specifically built with natural language processing (NLP) in mind. The user asks the chatbot to answer some type of question in natural language, then the chatbot uses the underlying technology, training data, and capabilities to provide the best possible answer to the user.

LLM is built on the transformer model, commonly known as a transformer. This is a network that is excellent at predicting text and understanding the context behind phrases. Because LLM uses the transformer model that excels at NLP, they can work well for common tasks that people need on a daily basis, things like solving math problems, creating code, prototyping, or even Write short reports, suggest edits.

Because of this, chatbots like ChatGPT, Microsoft Bing AI, and Claude have achieved great success and almost single-handedly sparked the AI revolution. While many believe AI systems could eventually achieve greater capabilities and intelligence than humans, there is little evidence that this will happen any time soon. Yet the possibilities that come from these models, integration with human workflows, and existing features that promise AI are here to stay, whether we like it or not. But you're probably wondering how these models fit with cryptocurrency and the nature of blockchain, so let's explore the potential synergies of these two radical forms of technology.

How can cryptocurrency support AI applications?

Cryptocurrency is an industry that is constantly discussed on major news channels, media outlets and on social media platforms every day. It is often difficult for us to describe the inherent benefits of blockchain technology to those outside the industry, mainly because the traditional finance industry is very developed and people are already familiar with old things. In countries other than the United States, it is much easier to explain and demonstrate the power of blockchain ledgers for financial transactions, largely because corrupt financial institutions and governments still hold sway. holds power in every major region of the world. Currencies regularly lose value in countries across the globe, and much of the world's population remains unbanked.

Cryptocurrency is a bankless way of banking, a new technology that offers the opportunity for the average user to become the custodian of their own finances, even if they are holding cryptocurrency in a cold wallet or using many financial dApps available on the cryptocurrency ecosystem.

Blockchain's inherent characteristics of transparency, security, and decentralization can contribute significantly to how AI data is stored, shared, and used. This fusion of technologies promises to increase trust in AI systems by providing an immutable ledger of AI transactions and decisions, thereby reducing concerns about manipulation or data abuse.

One of the key aspects where cryptocurrencies can support AI (and vice versa) is in the area of data management and security. AI systems require huge amounts of data to learn and improve. By leveraging blockchain technology, this data can be shared securely and transparently across different platforms and stakeholders. This not only ensures data integrity but also opens up new avenues for collaborative AI research and development, breaking down data silos that often hinder innovation.

The integration between AI and blockchain could lead to the creation of legitimate DAO autonomous organizations. These DAOs, governed by smart contracts and powered by AI, can operate independently, making decisions and executing transactions without human intervention. Historically, DAO organizations in the cryptocurrency market have seemingly fallen short of their original ideals as human emotions and financial motivations often obscure their primary purpose. Implementing AI systems can revolutionize industries by automating processes and reducing the need for intermediaries, thereby increasing efficiency and reducing costs.

Another promising area is the use of blockchain as a means to encourage the creation and sharing of AI data. Through tokens, individuals and organizations can be rewarded for contributing valuable data to AI models, fostering a more inclusive and collaborative AI ecosystem.

DeFi is also a development direction with great potential for AI, capable of creating what is called decentralized AI (DeAI). This approach can democratize access to AI technology, allowing individuals and small organizations to access AI tools and services that were previously the preserve of large corporations.

The convergence of cryptocurrency and AI has the potential to transform not only the financial sector but also many aspects of our digital lives. By combining the power of both technologies, we can work towards a future where AI is not only accessible but also safer, more transparent, and even more effective. Speaking of which, let's analyze the current operations of AI and how it works!

Breaking down the opaque walls of artificial intelligence Comparing the overhaul of the financial system through cryptocurrencies with the intellectual revolution occurring through the production of artificial intelligence systems, we can draw some very relevant and demonstrable parallels. combination of both. Today, artificial intelligence companies like OpenAI, Google's Deepmind, Anthropic, and many others conduct their research and operations behind closed doors.

Above we covered some of the basics around the synergies between AI and cryptocurrency, now we can take a closer look at some of the leading projects in the field. While most of these are still actively working on launching their networks, trying to attract a loyal user base and attention from the crypto community, they are all working on at the forefront of the industry and represents this rapidly growing sector well.

Bittensor – network of decentralized artificial intelligence models:

Bittensor is by far the most popular and reputable project in the cryptocurrency & AI ecosystem. Bittensor is a decentralized network designed to democratize the field of artificial intelligence by creating a platform for multiple decentralized commodity markets or “subnets”, unified under one system. unique token system. Its mission is to build a network that rivals the capabilities of major AI mega-corporations, such as OpenAI, using unique incentive mechanisms and advanced subnetwork architecture. Bittensor's system can be thought of as a machine, powered by blockchains, for efficiently transferring AI capabilities on-chain.

The network is managed by miners and validators. Miners submit pre-trained AI models to the network and receive rewards for their contributions, while validators ensure the validity and accuracy of the model's output. This process creates a competitive environment in which miners are incentivized to continuously improve their models for better performance and greater rewards in TAO, the network's native token. Users interact with the network by sending queries to validators, which then distribute them to miners. The validator rates the output from these miners and returns the highest-rated response to the user.

Bittensor's approach to model development is unique. Unlike many AI labs or research organizations, Bittensor does not train models due to high cost and complexity. Instead, the network relies on a decentralized training mechanism. Validators are responsible for evaluating models created by miners using a specific data set and scoring each model based on certain criteria, such as accuracy. This decentralized evaluation ensures continuous improvement in model performance.

Bittensor's architecture includes the Yuma consensus mechanism, a unique combination of both Proof-of-Work (PoW) and Proof-of-Stake (PoS), distributing resources across subnets of the network. Subnetworks are closed economic markets, each focused on different AI tasks, like text prediction or image generation, and can opt in or out of the Yuma consensus depending on the functionality of them.

Bittensor represents an important step in decentralizing AI, providing a platform where diverse AI models can be developed, evaluated, and improved in a decentralized manner. Its unique structure not only encourages the creation of high-quality AI models but also democratizes access to AI technology, potentially changing the way AI is developed and used in various fields .


Bittensor TAO token price chart. Source: Coingecko

Akash – open source super cloud platform:

Akash is an innovative, open source Supercloud platform, designed to buy and sell computing resources securely and efficiently. It was built with the vision of providing users with the ability to deploy their own cloud infrastructure as well as buy and sell unused cloud resources. This flexibility not only democratizes the use of cloud resources, but also provides cost-effective solutions for users who need to scale their operations.

The core of the Akash system is a reverse auction mechanism, where users can submit bids for their computing needs and vendors compete to provide the service, often resulting in significantly lower prices. compared to traditional cloud systems. The system is underpinned by trusted and well-established technologies such as Kubernetes and Cosmos, ensuring a secure and reliable platform for application hosting. Akash's community-driven approach ensures users have a voice in the development and governance of the network, making it a public and user-centric service.

Akash's infrastructure is defined using the easy-to-use, YAML-based Stack Definition Language (SDL), allowing users to create complex models across multiple regions and vendors. This feature, combined with Kubernetes, the leading container orchestration system, ensures not only deployment flexibility but also security and high reliability in application hosting. Furthermore, Akash offers persistent storage solutions that ensure data retention even after reboots, which is especially beneficial for applications that manage large datasets.

Overall, Akash Network stands out as a decentralized cloud platform that offers a unique solution to the proprietary nature of current cloud service providers. The model uses underutilized resources across millions of data centers globally to not only reduce costs but also improve the speed and efficiency of cloud-native applications. With no proprietary language rewrites and no need for vendor lock-in, Akash delivers a flexible and accessible platform for a variety of cloud-based applications.



Akash Network's AKT token price chart. Source: Coingecko

Render – platform to expand access to computing:

Render is a blockchain-based platform designed to address the growing computational needs in media production, especially in areas such as augmented reality, virtual reality, and AI-enhanced media. . The core advantage of Render Network is its integration with AI. AI plays an important role in both content creation and process optimization. The network supports AI-related tasks, allowing artists to use AI to create content and improve digital artwork. This integration enables the creation of ultra-high-resolution 3D worlds and optimized rendering pipelines, such as AI denoising. Additionally, Render Network's use of AI extends to managing large-scale art collections and optimizing rendering workflows, thereby expanding capabilities across creative processes.

Render's ecosystem operates as a marketplace for GPU resources, serving various stakeholders such as artists, engineers, and node operators. It democratizes access to computing power, allowing creators and major studios to take on complex projects affordably. Transactions in this ecosystem are facilitated using the RNDR token. As AI continues to reshape digital content creation, the Render network is poised to become a key player in facilitating new forms of creative expression and technological innovation in the digital media landscape. digital.



Render Network's RNDR token price chart. Source: Coingecko

Gensyn – decentralized computing platform:

Gensyn is an AI and cryptocurrency project focused on solving the computational challenges and resource constraints inherent in modern Artificial Intelligence (AI) systems. The project aims to overcome barriers to the development of AI due to the huge resource requirements needed to build the underlying models. Gensyn's approach is to create a decentralized, blockchain-based protocol that effectively utilizes global computing resources.

Gensyn's platform highlights the increasing computational complexity of AI systems, which is outpacing available computing power. For example, training large models like OpenAI's GPT-4 requires significant resources, creating high hurdles for all parties involved. This dynamic has led to the need for a system that can effectively utilize all available computing resources, addressing the limitations of current solutions such as being too expensive or not having enough resources for the most demanding tasks. the need for AI at scale.

Gensyn aims to solve this problem by creating a decentralized protocol to connect and verify off-chain deep learning in a cost-effective way. The protocol faces many challenges such as privacy concerns and the need to effectively parallelize deep learning models. The protocol intends to build a trustless computational network with economic incentives for user participation and a method to verify that computational work has been performed as promised.

The Gensyn protocol is a layer-1 trustless protocol for deep learning computation that rewards participants for contributing computational time and executing ML tasks. It uses a combination of techniques to verify completed work, including Proof-of-Learning, graph-based pinpointing protocols, and Truebit-style incentive games. This system consists of various participants such as Sender, Resolver, Validator and Whistleblower, each playing a specific role in the computation process.

In practice, the Gensyn Protocol consists of several stages, from task submission to contract arbitration and settlement. It aims to create a transparent, low-cost market for ML computing, enabling scalability and efficiency. The protocol also offers an opportunity for miners with powerful GPUs to reuse their hardware for ML computation, possibly at a lower cost than mainstream providers. This approach not only solves the computational challenges of AI but also aims to democratize access to AI resources.

Fetch.ai – an open platform for the artificial intelligence economy:

Fetch.ai has been around longer than some of the previously mentioned projects, with a plethora of services offered on its website. At its core, Fetch is an innovative project at the intersection of artificial intelligence (AI) and cryptocurrency, created to revolutionize the way economic activities and processes are carried out. The foundation of Fetch's services are AI agents, designed as modular building blocks that can be programmed to perform specific tasks. These agents have the ability to automatically connect, search and transact, thereby creating dynamic markets and changing the landscape of traditional economic activities.

One of the key services offered by Fetch is the ability to make legacy products AI-ready by integrating their API with Agent Fetch.ai, a process that is quick and requires no application changes. basic business use. AI agents can be combined with other agents in the network, opening up possibilities for new use cases and business models. Furthermore, these agents have the ability to negotiate and transact on behalf of users, allowing them to monetize their deployments. Additionally, these agents can provide inferences from machine learning models, allowing users to monetize their insights and enhance their own machine learning models.

Fetch also launched Agentverse, a no-code managed service that simplifies the deployment of AI agents. Just as traditional no-code platforms are gaining traction and services like Github's Copilot are making it easy for the masses to code, Fetch is working to further democratize web3 development in ways its own uniqueness.

Through Agentverse, users can launch their first agent easily, which significantly reduces the barrier to entry using advanced AI technologies. In terms of AI Engine and Agent Services, Fetch uses large language models (LLMs) to discover and direct task execution to appropriate AI agents. The system not only monetizes AI applications and services but also serves as a comprehensive platform for agency services including building, listing, analytics and hosting.

The platform enhances its utility with features like Search & Explore and Analytics. Agents can be registered in Agentverse for active discoverability on Fetch.ai's platform, which uses LLM-based search. Analytical tools are available to improve the effectiveness of agents' semantic descriptors, thereby enhancing their detection capabilities. Furthermore, Fetch.ai incorporates an IoT Gateway for offline agents, allowing them to collect messages and process them in batches upon reconnection.

Finally, Fetch.ai offers hosting for managed agencies, providing all the features of Agentverse in addition to hosting. The platform also launches an open network for address discovery and agent naming, leveraging Fetch.ai's Web3 network. This aspect represents a new approach to DNS Web addressing, integrating blockchain technology into the system. Overall, Fetch.ai presents a flexible platform that combines AI and blockchain technology, providing tools for developing AI agents, monetizing machine learning models, and a groundbreaking approach to search and exploration in the digital economy. This combination of AI agents and blockchain technology paves the way for automating and optimizing various processes in a decentralized and efficient manner.


Fetch.ai FET token price chart. Source: Coingecko

Next steps and predictions for both industries

The seamless integration between artificial intelligence and blockchain technology represents a key advancement in both fields. This combination is not just a simple combination of two cutting-edge technologies but a transformational synergy that redefines the boundaries of digital innovation and decentralization. The potential applications of this integration, as explored in various projects such as Fetch.ai, Bittensor, Akash Network, Render Network and Gensyn, demonstrate the immense capabilities and significant benefits of combining the computing power of AI with the secure and transparent framework of blockchain.

As we look to the future, it is clear that the convergence of AI and blockchain will play a key role in shaping various industries. From enhancing security and data integrity to creating new models of DAO organizations, this merger promises to bring about more efficient, transparent, and accessible technologies. Especially in the DeFi sector, the emergence of decentralized AI (DeAI) can democratize access to AI technologies, breaking down barriers that have traditionally favored large corporations. This could lead to a more inclusive digital economy, where individuals and smaller organizations can take advantage of AI tools and services that were previously out of reach.

Furthermore, the integration of these technologies is poised to solve some of the most pressing challenges in both sectors. In AI, problems such as massive data warehouses and computational resources required to train large models can be mitigated through decentralized data management and shared computing power of blockchain. In the blockchain space, AI can improve efficiency, automate decision-making processes, and improve security mechanisms. As we move forward, it is important for developers, researchers, and stakeholders to continue to explore and exploit the synergy between AI and blockchain. By doing so, they will not only contribute to the development of these individual sectors but also drive innovation in the digital landscape, ultimately benefiting society as a whole.