The digital world has already climbed the ladder from the read-only HTML pages of Web1 to the participative and social Web 2.0. Now, we are on the brink of Web 3.0 as the fusion of generative AI and blockchain forges a new frontier with superior UX.
This report charters the course from Web 2.0’s centralised AI frameworks to Web 3.0’s decentralised and blockchain innovations. We bring you up to speed on how Web 3.0 upgrades the layered tech stack of Web 2.0, and FLock’s part in it.
Web 1.0, Web 2.0, & Web 3.0: from read, to read-write- to read-write-own
In the era of Web 1.0, the internet was predominantly a read-only platform, where users could access and view information but had limited interaction.
Web 2.0 marked the transition to a read-write landscape. This enabled users not only to consume content, but also to create and share their own in an interactive web experience.
Web 3.0 introduces read-write-own, allowing individuals to manage their digital assets and information.
Web 2.0’s AI Tech Stack
The key traits of Web 2.0 are centralised ownership, data monetisation by companies, and privacy concerns.
When users generate data, e.g. through social media posts or browsing the web, it becomes the property of the platform they are using. User data is primarily owned by centralised corporations, who can monetise it through targeted advertising or selling it to third parties.
In this section, we explain the Web 2.0’s AI tech stack, each layer playing a role in AI applications, with example players.
Web 2.0: Computational Powerhouses
In Web 2.0, AI’s foundation was built on centralised cloud services like AWS and Azure, providing the computational power needed for complex data analysis and the execution of machine learning tasks at scale.
Web 2.0: Foundation Models
Centralised platforms like OpenAI and Anthropic were key in democratizing AI, making advanced capabilities widely accessible and fueling a surge in AI applications across different sectors.
Web 2.0: Data Management
Web 2.0 AI efficiency depended on robust data management systems. Tools like Scale AI and Mechanical Turk streamlined data preprocessing, while platforms such as Pinecone, Databricks, and Snowflake were crucial for managing and accessing large datasets.
Web 2.0: Broad range of agents and applications
From marketing tools like Jasper and copy.ai to groundbreaking innovations in healthcare with Glass, AI’s applicability spanned diverse domains
Web 2.0: Tooling and Frameworks
This layer introduced key tools and frameworks like Langchain and LlamaIndex for building AI apps. Platforms like BabyAGI, AutoAGI, and Camel enhanced agent creation and refinement, advancing AI sophistication and functionality significantly.
Web 2.0: The Marketplace Mechanism
The emergence of platforms like HuggingFace and GitHub has fostered a collaborative ecosystem, allowing sharing and discovery.
Web 3.0’s Decentralised AI Framework
Web 3.0’s key traits are: decentralised ownership, user control over data, and improved privacy and security. This is enabled by blockchain, smart contracts, and decentralised storage.
Users can control who has access to their information, under what conditions, and even monetise their own data if they choose to. Blockchain’s immutability and encryption protects user data from unauthorised access.
In this section, we explain Web 3.0’s key features in detail, with example Web 3.0 players.
Web 3.0: Computational Collaboration
Blockchain enables greater computational collaboration, with a shift from centralised services like AWS to decentralised networks.
Projects like Render, Akash, and Gensyn allow for shared computational contributions, promoting inclusivity.
FLock.io enables decentralised model inferencing on its blockchain network.
Web 3.0: Model Development
Web 3.0 moves away from Web 2.0’s centralised models like OpenAI, adopting decentralised model construction and encouraging global community contributions.
Companies like Bittensor encourage global community contributions.
FLock.io facilitates training and fine-tuning in this decentralised setting.
Web 3.0: Data Democratisation
No more data locked in corporate vaults. Instead, imagine a community collaborating to annotate data for groundbreaking research, from medical analysis to self-driving car training.
Web 3.0 tools ensure secure, distributed storage, empowering individuals to control their data and reap rewards for their contributions. This isn’t just data — it’s a new social contract of ownership, collaboration, and shared progress.
Tools in this space: IPFS and Filecoin.
Web 3.0: Data Privacy
Blockchain becomes the privacy-first, non-invasive shield for your information. One use case is training AI on sensitive medical data without exposing patient identities, thanks to advanced encryption and zero-knowledge proofs.
This is Web 3.0’s promise: AI that learns, yet keeps your data safe and under your control.
Companies in this area: Privasea and ModulusLabs.
Web 3.0: Authentication
Solutions like EZKL and Worldcoin offer secure, self-sovereign identity management, eliminating the need for centralised platforms to hold your login credentials.
Imagine logging into AI applications without relying on Facebook or Google, putting you in control of your digital identity.
Web 3.0: AI-Driven Analytics
Platforms like Dune Analytics and NumerAI utilise AI for Web 3.0 data analysis.
Imagine exploring complex DeFi protocols and identifying investment opportunities, all powered by AI in a transparent and community-driven ecosystem.
Web 3.0: Agents
Web 3.0 empowers the development of intelligent agents like Autonolas and Fetch.ai, capable of navigating decentralised networks and autonomously executing tasks on your behalf.
Imagine AI agents managing your investments, negotiating decentralised deals, or optimising your resource allocation across Web 3.0 protocols, unlocking a new era of automation and personalised services.
FLock.io is a key player in Web 3.0
FLock is excited to accelerate decentralised AI with a full-stack AI co-creation platform that enables model training and rewards for data contribution.
FLock.io is a decentralised and permissionless platform for co-owned AI models and Dapps. By harnessing the synergies of Federated Learning and blockchain technologies, we address the growing demands of models and potential data breach threats, guaranteeing secure model training without revealing underlying source data, and fair rewards to data contribution and community collaboration.
If anything sparks your interest, we warmly invite you to start a dialogue.
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