DOWHAT DEV
INFRA
DoWhat - Infrastructure
The humanized, execution-driven cognitive model developed by DOWHAT.ME will bring groundbreaking impacts to AI applications, driving transformative advancements across the field.
Personal Digital Clone Protocol (PDCP)
The Personal Digital Clone Protocol (PDCP) is a standardized protocol designed to enable individuals to own and control their personal digital clones. It serves as the foundational framework for human-like AI automation, data sovereignty, and cross-platform intelligent services. PDCP facilitates the creation, management, and orchestration of personal digital clones, endowing them with “human-like reasoning and execution capabilities” while ensuring secure cross-platform functionality spanning both Web2 and Web3 ecosystems.
1. Primary Objectives of PDCP
Provide each user with a highly personalized and intelligent digital clone/digital proxy.
Enable the digital clone to autonomously handle a wide range of tasks, such as social interactions, scheduling, payments, on-chain operations, and data management, based on user intent.
Empower users to control their data, permissions, and the behavior of their digital clones through PDCP.
2. Key Features of PDCP
Chain of Thought (CoT): A core logical framework ensuring the digital clone operates with human-like “thinking-reasoning-decision-execution” workflows.
Unified Identity and Permissions: Enables the digital clone to manage multiple identities, wallets, and accounts with secure authorization.
Cross-Platform Capability: Allows seamless invocation of Web2 and Web3 services (e.g., social media, shopping, wallets, smart contracts).
Data Sovereignty: Users maintain full control over their personal data and the actions of their digital clone.
Programmability and Extensibility: The protocol supports third-party developers in creating new capabilities for the digital clone ecosystem.
3. Role of PDCP in DOWHAT.ME
PDCP functions as the operating system-level protocol for DOWHAT.ME, forming the backbone of its architecture. It enables each user's digital clone to emulate human-like decision-making, perform autonomous execution, and securely empower cross-platform services.
Chain of Thought (CoT)
The Chain of Thought (CoT) is a critical component of PDCP and serves as the intelligent reasoning framework of DOWHAT.ME. CoT refers to the AI’s ability to solve problems or execute tasks by breaking them into a series of logical steps, where each step is guided by structured reasoning, judgment, and actionable insights. In PDCP, CoT goes beyond basic reasoning, embodying an integrated “thinking-decision-action” process that mirrors human cognition.
Key Components of CoT
A. Perception and Input Understanding
Processes user instructions, environmental data, and historical records to generate structured perceptual representations.
B. Intent Parsing and Goal Setting
Extracts the user’s deep intent and establishes clear objectives or sub-goals.
C. Task Decomposition and Step Planning
Deconstructs complex goals into multi-step executable tasks. Combines historical preferences and context to identify the best pathway for each step. Supports various chain structures such as parallel, serial, and conditional branching.
D. Reasoning and Decision-Making
For each task, integrates personal habits, real-time environmental factors, and external variables to make human-like judgments and choices. Dynamically adjusts steps, priorities, and even allows for “skipping” or “rollback” actions as necessary.
E. Multi-Agent Collaboration
Automatically coordinates multiple agents and platforms when tasks span diverse ecosystems, ensuring synchronized state management.
F. Action and Execution
Invokes MCP services to automate operations across Web2 and Web3 platforms, such as placing orders, making payments, and sending notifications.
G. Feedback and Self-Correction
Continuously refines the CoT workflow based on execution outcomes, user feedback, and external changes, ensuring task completion.
H. Memory and Growth
Records every execution, its outcomes, and feedback to optimize future decision-making and refine task workflows.
Why CoT is Ideal for AI Execution？
A. Human-Like Decision-Making for Enhanced Intelligence
Human decision-making involves multi-step reasoning and dynamic adjustments. CoT equips AI with similar “think-judge-act-correct” capabilities for comprehensive intelligence.
B. Task Decomposition and Traceability for Complex Scenarios
Complex tasks (e.g., travel planning, cross-chain payments, automated workflows) require multi-step coordination. CoT naturally supports task decomposition, state tracking, and error recovery.
C. Adaptability and Robustness for Real-World Variability
The real world is full of uncertainties. CoT dynamically adjusts execution paths based on real-time feedback, significantly enhancing adaptability and resilience.
D. Cross-Platform and Multi-Agent Collaboration
CoT inherently facilitates the distribution of complex tasks across multiple platforms and agents, maximizing resource utilization across Web2 and Web3 ecosystems.
E. Personalization and Growth
CoT deeply integrates user preferences and historical behaviors, creating a highly personalized AI execution style. Continuous learning allows the system to evolve over time.
CoT's Role in Enhancing AI Execution
The CoT framework enables AI to perform dynamic reasoning and decision-making akin to human cognition, significantly enhancing its ability to handle complex tasks, adapt to changing environments, and evolve personalized execution styles. It serves as the ideal foundation for AI execution and is the central intelligence framework of DOWHAT.ME’s ERE-Bob.
DATAME (DOWHAT.ME's Proprietary Data Encryption Security System)
The technological paradigm of DOWHAT.ME (DATAME) integrates zero-knowledge proof, fully homomorphic encryption, blockchain, and other advanced technologies to construct a comprehensive system for data security and trustworthiness.
This paradigm not only protects user privacy and grants users control over their data but also provides technical support for the circulation and efficient utilization of industrial data, significantly enhancing the platform's value and competitiveness.
Key Components
A. User Data Capture Module
This module is responsible for collecting data from the user end while ensuring the integrity, accuracy of source, and legality of the data.
To prevent unauthorized data breaches, the module seamlessly integrates with subsequent security modules during the data capture process.
B.Zero-Knowledge Proof (ZKP) Framework
Zero-knowledge proof is a cryptographic technique that allows the verification of data authenticity or satisfaction of certain conditions without exposing the content of the data itself.
Under this framework, the authenticity or specific attributes of user data can be validated while the actual content remains completely hidden from external entities.
C.Fully Homomorphic Encryption Engine
Fully homomorphic encryption (FHE) is an encryption technique that enables computations to be performed directly on encrypted data.
In this system, FHE is employed to process encrypted user data, ensuring that the data remains in an encrypted state even during computation.
D.Blockchain Storage and Verification Module
The data-on-chain module is responsible for storing data on the blockchain after it has been verified via zero-knowledge proof and processed with fully homomorphic encryption.
The distributed and tamper-proof nature of blockchain guarantees data reliability and security while providing a foundation for subsequent verification.
E.Smart Contract Logic
Smart contracts automate processes on the blockchain, such as data usage authorization, verification, and associated rights distribution.
Technical Implementation
A.User Data Capture and Preprocessing
During the data capture phase, the system employs privacy-preserving protocols (e.g., local differential privacy or anonymization techniques) to preprocess the data, preventing direct exposure of sensitive information.
B.Zero-Knowledge Proof Generation and Verification
The system utilizes advanced ZKP protocols (e.g., zk-SNARK or zk-STARK) to generate proofs on the user side, with lightweight verification algorithms executed on the cloud or blockchain side.
For instance, users can demonstrate that "a certain piece of data is valid" or "complies with specific rules" without revealing the data itself.
C.Integration of Fully Homomorphic Encryption
The system leverages mainstream fully homomorphic encryption libraries (e.g., IBM's HELib or Microsoft's SEAL) to enable encrypted computation on user data.
This ensures that any data processing or analysis occurs without decrypting the data, maintaining encryption throughout its entire lifecycle.
D.On-Chain Data Storage and Optimization
When data is stored on-chain, a hybrid approach of distributed storage and off-chain storage is adopted:
Data Hashing: Encrypted data hashes are stored on-chain to validate data integrity.
Distributed Storage: Actual encrypted data is stored in distributed systems (e.g., IPFS) to reduce blockchain storage load.
Merkle Tree Structure: Data verification efficiency is optimized using Merkle trees.
E.Smart Contracts and Data Authorization
Using smart contracts, users can define rules for data authorization (e.g., access permissions, usage time limits, or specific purposes).
Smart contracts automatically record and execute authorization operations, eliminating manual intervention and preventing unauthorized usage.
Role in DOWHAT.ME
A.Ensuring User Privacy and Data Security
By integrating zero-knowledge proof and fully homomorphic encryption technologies, the system ensures end-to-end protection of user data during collection, storage, processing, and usage.
Even during data sharing or analysis, sensitive information leakage is avoided.
B.Enhancing Data Credibility and Value
Zero-knowledge proof ensures the authenticity of user data, eliminating the possibility of data falsification or tampering.
The combination of blockchain storage and smart contracts provides a trusted technological foundation for data transactions and sharing, further enhancing the market value of data.
C.Improving Compliance and User Trust
DOWHAT.ME's technological paradigm complies with increasingly stringent data privacy regulations (e.g., GDPR, CCPA).
A transparent privacy protection mechanism is provided to users, fostering trust in the platform.
D.Facilitating Efficient Data Circulation Across Industries
This paradigm enables enterprises to perform analysis or model training without directly accessing raw data, effectively addressing data silos and promoting cross-industry data collaboration.
The integration of encryption and smart contract technologies establishes a secure and compliant infrastructure for data usage and circulation.
