Introducing AI Actions

Introducing AI Actions

Our mission at Giza is to bridge the seemingly disparate worlds of AI and Web3. Such a mission comes with great challenges, sometimes technical, sometimes pedagogical in nature. The key to bootstrapping a flourishing Web3 / AI ecosystem, is streamlined workflows to integrate ML know-how into the design space of Web3.

Towards this vision we are introducing AI Actions, a solution designed to integrate machine learning (ML) with blockchain technology seamlessly. This introduction is aimed at providing a comprehensive overview of AI Actions, its significance, and the transformative potential it holds in the adoption of ZKML as trustless enablement technology of ML in the blockchain.

The Genesis

The inception of AI Actions by Giza is rooted in a series of in-depth explorations and discussions that revealed a significant gap in the integration of machine learning (ML) with blockchain technologies. As we engaged with various blockchain protocols and delved into potential use cases, it became evident that there were multiple areas of struggle hindering the effective fusion of these two powerful domains.

One of the most prominent challenges identified has been the lack of ML know-how within the blockchain ecosystem. Many protocols are adept at managing and interpreting data through providers like Dune or Nansen, gaining valuable insights into on-chain activity. However, they often fall short in leveraging this data to enact meaningful state changes within the protocols themselves, primarily due to a limited understanding of ML's potential and the associated complexities. This gap not only restricts the optimization of protocols but also limits their adaptability and efficiency in responding to dynamic market conditions.

Another critical issue encountered was the question of data curation and quality. While blockchain protocols are exceptionally rich in data, the absence of structured and labeled datasets poses a significant barrier to developing robust ML solutions. The data, often scattered across various platforms, suffers from inconsistencies and quality issues, making it challenging for ML models to extract actionable insights. Moreover, the importance of data provenance became increasingly clear, as protocols expressed a strong desire to trace the origins and authenticity of data feeding into ML models, whether it was sourced from APIs, subgraphs, or nodes. This need for traceability is crucial not only for the integrity of ML solutions but also for maintaining transparency and trust within the blockchain ecosystem.

These insights laid the foundation for AI Actions, shaping it as a tool designed to address these core challenges. By focusing on enhancing ML understanding within blockchain protocols, improving data curation and quality, and ensuring data provenance, AI Actions aims to bridge the gap between blockchain and ML, paving the way for more intelligent, responsive, and efficient smart contract systems.

The Pillars of AI Actions

At the heart of AI Actions are three foundational pillars designed to address the critical challenges in merging machine learning (ML) with blockchain technology. These pillars form the basis of AI Actions' approach to revolutionizing how decentralized protocols and applications leverage ML for enhanced efficiency and functionality.

The first pillar focuses on Data. Data quality and accessibility are paramount in ML, yet blockchain protocols often struggle with fragmented and uncurated datasets. AI Actions aims to transform this landscape by providing mechanisms for better data curation and quality assurance. This involves creating accessible, labeled datasets that are essential for training effective ML models. Additionally, AI Actions emphasizes the importance of data provenance, ensuring that the data's origin and journey are transparent and traceable. By addressing these data-related challenges, AI Actions will set the stage for more performant and reliable ML applications in the Web3 domain.

The second pillar centers on the Model aspect. One of the significant barriers in the integration of ML with Web3 is the lack of easy-to-use tools for building verifiable ML solutions that blockchain protocols can trust. Web3 is often unfamiliar with the nuances of ML, and there is a noticeable gap in experience when it comes to deploying ML solutions in production environments. AI Actions steps in to fill this gap by simplifying the process of creating and verifying ML models. By doing so, it not only makes ML more accessible to smart contract developers but also ensures that the solutions developed are reliable and fit for purpose in the Web3 context.

Finally, the third pillar addresses Integration challenges. Web3 protocols are typically reluctant to undergo significant changes or upgrades to incorporate ML solutions, mainly due to the high costs and potential security vulnerabilities involved. AI Actions tackles this issue by offering a way to integrate ML solutions without necessitating core changes to the protocols. This approach minimizes the overhead of auditing and testing, making it significantly easier for protocols to adopt and benefit from ML enhancements.

Together, these three pillars - Data, Model, and Integration - form the strategic framework of AI Actions. This framework is designed to overcome the prevailing challenges in the ZKML nexus, paving the way for scalable, reliable, and user-friendly ML solutions in the Web3 ecosystem. AI Actions represents a holistic approach to addressing each critical aspect from data management to model development and integration.

Democratizing ML in Blockchain

AI Actions is positioned not just as a technological solution but as a catalyst for democratizing machine learning (ML) within the blockchain ecosystem.

The core of this section focuses on Bridging Skill Gaps. The blockchain industry, while rich in data and potential, often lacks the in-depth ML expertise that is abundant in the broader AI developer community. AI Actions seeks to connect these two worlds, enabling AI developers to apply their skills and insights to Web3 challenges without necessitating deep knowledge of blockchain intricacies or cryptographic protocols. This bridging of skills and knowledge is pivotal in fostering innovation and advancing the capabilities of decentralized technologies.

Moreover, this section explores Market Statistics and Potential. It highlights the current landscape of the industry – a limited number of cryptographers and blockchain developers relative to a much larger pool of AI developers. With approximately 300,000 AI developers worldwide, a number that is rapidly growing, there exists a vast untapped resource that can be directed towards enhancing blockchain functionalities. AI Actions aims to tap into this reservoir of talent, bringing fresh perspectives and solutions to the blockchain domain.

AI Actions embodies the vision of making ML accessible and actionable within the blockchain ecosystem. It’s about creating a platform where AI developers can easily apply their skills towards improving decentralized applications, contributing to the development of new primitives and enhancing protocol efficiency. This democratization of ML in blockchain is crucial for the evolution of the technology, ensuring that the benefits of ML are not just confined to traditional markets but are also extended to the burgeoning world of blockchain.

The Vision and Mission of AI Actions

AI Actions is anchored in the vision of building trustworthy AI for Blockchain. The platform is not just about integrating ML capabilities into blockchain; it's about instilling a level of performance, trust and reliability in these integrations that has been previously unattainable. AI Actions is designed to ensure that ML solutions deployed in blockchain environments are not only effective but also verifiable and transparent. This trust factor is crucial in decentralized applications, where security, privacy, and accuracy are paramount. By emphasizing verifiable ML solutions, AI Actions aims to bring a new standard of trust and integrity to smart contract operations, ensuring that ML applications are as dependable as they are innovative.

Moreover, AI Actions aim to bootstrap a collaborative ecosystem. This mission is about more than just technology; it's about fostering a community where AI experts, blockchain enthusiasts, and developers can collaborate and innovate together by bridging needs to capabilities. AI Actions envisages a platform where knowledge sharing and collective problem-solving are the norms, bridging the gap between traditional markets and the blockchain world. By bringing together diverse expertise and perspectives, AI Actions aims to spur the development of novel blockchain primitives and smarter, more efficient protocols. This collaborative approach is key to unlocking the full potential of ML in blockchain, driving the technology forward in ways that are both inclusive and paradigm shifting.

Conclusion

It's clear that we stand at the threshold of a new era in blockchain and AI integration. AI Actions is not just a product; it's a pivotal movement towards transforming how blockchain technology leverages the power of machine learning. This initiative marks a significant step in bridging the gap between two rapidly evolving domains, paving the way for more advanced, efficient, and trustworthy blockchain ecosystems.

AI Actions is more than just a tool for innovation; it's a call to action for developers, AI experts, and blockchain enthusiasts. The potential for AI Actions to democratize ML in blockchain is vast, opening doors for AI developers worldwide to apply their skills in establishing the foundations of next generation digital infrastructure.



As AI Actions transform the intersection of Web3 and AI, Giza invites all relevant stakeholders to be part of this evolution, to engage with AI Actions, and help shape the future of blockchain technology. Stay tuned for more.