We are entering a decisive era in the development of AI, in which the convergence of generative AI and blockchain is opening up new frontiers of digital innovation.
We delve into this paradigm shift, charting the journey from Web2’s established centralized AI framework to Web3’s decentralized innovation.
Web2 AI and Web3 AI stacks and track projects
Basics: Web2’s AI technology stack
The AI landscape in the Web2 era can be best understood through a layered approach, each representing a key aspect of AI development and deployment. This segmentation provides a clearer view of how the individual components interact with each other and contribute to the AI ecosystem as a whole. These layers include:
Compute engine
At the heart of AI capabilities are centralized cloud services like AWS and Azure. These platforms are the cornerstone of AI operations, providing the computing power necessary for complex data analysis and machine learning tasks at scale.
Base model
Centralized model training platforms, represented by entities such as OpenAI and Anthropic, have played a crucial role in democratizing AI. These platforms have made advanced AI capabilities available, triggering a widespread surge in AI applications in various fields.
Data management
The efficiency of AI in Web2 relies heavily on an effective data management system. Tools such as Scale AI and Mechanical Turk simplify data preprocessing to ensure it’s ready for analysis. At the same time, platforms such as Pinecone, Databricks, and Snowflake play a key role in managing and storing large data sets, facilitating easy access and operations.
Agents and applications
The versatility of AI in Web2 is on full display in its wide range of applications. From marketing tools like Jasper and copy.ai to groundbreaking innovations in healthcare brought about by Glass, the applicability of AI spans multiple domains, demonstrating its transformative potential.
Tools and frameworks
This layer has greatly shaped AI development in the Web2 era, with essential tools and frameworks for AI agent development like Langchain and LlamaIndex. Platforms such as BabyAGI, AutoAGI, and Camel are essential to enhance agent development, providing a dedicated environment for creation and refinement. Collectively, these elements enrich the sophistication and advanced capabilities of AI agents, marking key advancements in AI capabilities during this period.
Market mechanisms
The advent of platforms such as HuggingFace and GitHub has fostered a collaborative ecosystem that allows for the sharing and discovery of AI models and tools.
Evolution: Decentralized AI frameworks for Web3
Transitioning to Web3, our exploration of AI has entered a new dimension. Based on Web2’s layered approach, we take a deeper look to shed light on how decentralization and blockchain are redefining AI projects. The unique attributes of Web3 require additional layers, particularly privacy and authentication, to demonstrate how these transformative technologies can foster a more secure, transparent, and collaborative AI environment. This nuanced approach reveals the profound impact of decentralization on the development of AI, paving the way for a future where trust, ownership, and innovation thrive.
Computing collaboration
Blockchain technology is revolutionizing computing collaboration, moving from a centralized cloud service like AWS to a decentralized global network of resources. Projects such as Render, Akash, and Gensyn are testaments to this evolution, enabling participants to contribute computing power and foster a more inclusive ecosystem.
Model development
Unlike centralized platforms such as OpenAI, which dominates Web2, Web3 is embracing decentralized model building. This new approach, exemplified by the Bittensor network, fosters the collective contribution of the global community.
Democratize data
Web3 rewrites the rules. No more data is locked in the corporate vault. Instead, imagine a vibrant community collaboratively annotating data for breakthrough research, from medical analysis to autonomous vehicle training. Tools like IPFS and Filecoin ensure secure, distributed storage, enabling individuals to take control of their data and be rewarded for their contributions. It’s not just data – it’s a new social contract about ownership, collaboration, and shared progress.
Data Privacy
Blockchain becomes the shield of your information. Imagine training AI on sensitive medical data without exposing patient identities with advanced encryption and zero-knowledge proofs. Companies like Privasea and Modulus Labs are leading the way, shifting the paradigm away from intrusive, centralized models and privacy-first AI. That’s the promise of Web3: AI is able to learn and grow while keeping your data safe and under your control.
verify
Solutions like EZKL and Worldcoin provide secure, sovereign identity management without the need for a centralized platform to hold your login credentials. Imagine being able to log in to an AI app without relying on Facebook or Google, enhancing security and putting you in control of your digital identity.
AI-driven analytics
Platforms like Dune Analytics and NumerAI leverage cutting-edge AI algorithms to transform data analytics in Web3. Imagine seamlessly exploring complex DeFi protocols, identifying investment opportunities, and making informed decisions, all powered by AI in a transparent and community-driven ecosystem.
Agents
Web3 enables the development of agents such as Autonolas and Fetch.ai, which are able to navigate the decentralized web and perform tasks autonomously on your behalf. Imagine AI agents managing your investments, negotiating decentralized transactions, or optimizing your resource allocation across Web3 protocols, ushering in a new era of automation and personalization.
Final Thoughts
The synergy between blockchain and AI in the Web3 space heralds a new era of innovation, combining the benefits of blockchain in data ownership, transparency, and ethical governance with the advanced capabilities of AI. This integration paves the way for enhanced data ownership, increased transparency in AI systems, and facilitating direct data monetization. It also promises to minimize AI’s energy footprint and promote ethical AI development.