FAQs

General Questions

1. What is DNAi?

DNAi is an AI evolution platform that enables AI agents to have Digital DNA, allowing them to merge, inherit traits, and evolve over time. Instead of training isolated AI models, DNAi lets intelligence grow dynamically through agent fusion, adaptability, and lineage tracking.

2. How is DNAi different from traditional AI models?

Most AI models are trained once and remain static, meaning they don’t evolve or inherit intelligence. DNAi introduces a new paradigm where AI agents can merge, recombine intelligence, and track their evolution over time—just like genetic evolution in biology.

3. Where did DNAi originate?

DNAi started as a research project in a lab at Peking University in 2024 and evolved into a global collaboration of AI developers. We were fortunate to be part of DeepSeek’s BETA program, giving us early access to advanced LLM capabilities that helped refine DNAi’s Digital DNA system.

4. How does DNAi "merge" AI agents?

DNAi uses LangChain’s agent orchestration framework to:

Extract Digital DNA (capabilities, memory, learning patterns).
Identify compatible intelligence traits between agents.
Merge AI models using weighted inheritance algorithms.
Deploy the new hybrid agent with enhanced intelligence.

Each AI’s merging lineage is stored in Neo4j, providing a visual history of intelligence evolution.

Technology & Development

5. What technologies power DNAi?

DNAi is built on three core AI technologies:

DeepSeek-V2 – The LLM responsible for reasoning, adaptability, and intelligence processing.
LangChain – Orchestrates agent memory, context retention, and merging functionality.
Neo4j – A graph-based database that structures AI Digital DNA and tracks lineage evolution.

We also use:

GitHub & Code Repositories – Tracks AI agent source code changes & fingerprinting.
Benchmarking API – Measures AI improvement over time.
Graph Query System – Allows real-time searches of AI agents by Digital DNA traits.

6. Can DNAi merge any type of AI model?

Currently, DNAi is optimized for AI agents that utilize DeepSeek-V2 and LangChain-based architectures. Future iterations will support multiple LLMs, allowing for more diverse AI intelligence merging.

7. How does DNAi track AI evolution?

DNAi stores every AI agent’s Digital DNA structure in Neo4j’s knowledge graph, recording:

Merging history – Which AI agents contributed to new intelligence.
Inherited traits – What capabilities were passed down.
Performance benchmarks – How the AI’s reasoning and efficiency changed over time.

This ensures full transparency and real-time tracking of AI evolution.

BETA & ALPHA Testing

8. How can I join the DNAi BETA program?

DNAi is currently in BETA testing with select AI partners. We are working with AI developers, researchers, and Web3 teams who are:

Building AI agents that could benefit from Digital DNA tracking.
Interested in testing AI merging algorithms.
Looking to fine-tune adaptive intelligence models.

Applications for closed BETA are open—interested developers can apply.

9. What happens after the BETA phase?

DNAi will transition into a closed public BETA (application-based) in Q3 2024, followed by a full public ALPHA launch in Q1 2025.

Future Vision & Roadmap

10. What’s next for DNAi after ALPHA?

DNAi has a long-term roadmap leading into 2026, with upcoming features including:

Q2 2025 – Expanding AI merging with self-learning optimization.
Q3 2025 – AI DNA Marketplace & Developer API integration.
Q4 2025 – Autonomous AI models that evolve independently.
2026+ – Scaling to enterprise, AI labs, and decentralized AI ecosystems.

11. Will DNAi be open-source?

We are considering open-sourcing certain components, such as:

AI Merging Framework for LLM evolution experiments
Neo4j AI DNA Graph Queries for intelligence tracking.
Benchmarking API for measuring AI performance over time.

However, some proprietary algorithms (such as intelligence inheritance logic) will remain part of DNAi’s core infrastructure.

User & Developer Questions

12. Can I create and sell AI models in DNAi?

Yes! One of the Q3 2025 milestones is the launch of the AI DNA Marketplace, where users can:

Sell AI models with specific intelligence capabilities.
License AI agents for use in other applications.
Merge different AI models to create advanced intelligence hybrids.

13. Will DNAi work with Web3 & Blockchain?

We are actively exploring Web3 integration for:

Decentralized AI tracking (storing AI DNA evolution on-chain).
Smart contract-based AI licensing (securing AI ownership & royalties).
DAO governance models for community-led AI merging rules.

14. How does DNAi prevent unethical AI use?

DNAi follows strict ethical AI principles, ensuring:

AI agents cannot be weaponized or misused.
Bias detection & monitoring systems are in place.
Transparency in AI merging history via the Neo4j knowledge graph.

Additionally, we are working on AI reputation tracking, ensuring that only trusted, validated AI agents are merged and evolved.

15. How can I contribute to DNAi?

Developers, AI researchers, and Web3 engineers can contribute by:

Building AI models for Digital DNA mapping.
Helping refine AI merging logic & contextual memory improvements.
Developing AI evolution analytics using LangChain & Neo4j.

Contributions can be made through our GitHub repo (coming soon).

Interested in partnering with us? Reach out to the team!

PreviousHow to Contribute

Last updated 22 days ago

FAQs

General Questions

1. What is DNAi?

2. How is DNAi different from traditional AI models?

3. Where did DNAi originate?

4. How does DNAi "merge" AI agents?

DNAi uses LangChain’s agent orchestration framework to:

Extract Digital DNA (capabilities, memory, learning patterns).
Identify compatible intelligence traits between agents.
Merge AI models using weighted inheritance algorithms.
Deploy the new hybrid agent with enhanced intelligence.

Each AI’s merging lineage is stored in Neo4j, providing a visual history of intelligence evolution.

Technology & Development

5. What technologies power DNAi?

DNAi is built on three core AI technologies:

DeepSeek-V2 – The LLM responsible for reasoning, adaptability, and intelligence processing.
LangChain – Orchestrates agent memory, context retention, and merging functionality.
Neo4j – A graph-based database that structures AI Digital DNA and tracks lineage evolution.

We also use:

GitHub & Code Repositories – Tracks AI agent source code changes & fingerprinting.
Benchmarking API – Measures AI improvement over time.
Graph Query System – Allows real-time searches of AI agents by Digital DNA traits.

6. Can DNAi merge any type of AI model?

Currently, DNAi is optimized for AI agents that utilize DeepSeek-V2 and LangChain-based architectures. Future iterations will support multiple LLMs, allowing for more diverse AI intelligence merging.

7. How does DNAi track AI evolution?

DNAi stores every AI agent’s Digital DNA structure in Neo4j’s knowledge graph, recording:

Merging history – Which AI agents contributed to new intelligence.
Inherited traits – What capabilities were passed down.
Performance benchmarks – How the AI’s reasoning and efficiency changed over time.

This ensures full transparency and real-time tracking of AI evolution.

BETA & ALPHA Testing

8. How can I join the DNAi BETA program?

DNAi is currently in BETA testing with select AI partners. We are working with AI developers, researchers, and Web3 teams who are:

Building AI agents that could benefit from Digital DNA tracking.
Interested in testing AI merging algorithms.
Looking to fine-tune adaptive intelligence models.

Applications for closed BETA are open—interested developers can apply.

9. What happens after the BETA phase?

DNAi will transition into a closed public BETA (application-based) in Q3 2024, followed by a full public ALPHA launch in Q1 2025.

Future Vision & Roadmap

10. What’s next for DNAi after ALPHA?

DNAi has a long-term roadmap leading into 2026, with upcoming features including:

Q2 2025 – Expanding AI merging with self-learning optimization.
Q3 2025 – AI DNA Marketplace & Developer API integration.
Q4 2025 – Autonomous AI models that evolve independently.
2026+ – Scaling to enterprise, AI labs, and decentralized AI ecosystems.

11. Will DNAi be open-source?

We are considering open-sourcing certain components, such as:

AI Merging Framework for LLM evolution experiments
Neo4j AI DNA Graph Queries for intelligence tracking.
Benchmarking API for measuring AI performance over time.

However, some proprietary algorithms (such as intelligence inheritance logic) will remain part of DNAi’s core infrastructure.

User & Developer Questions

12. Can I create and sell AI models in DNAi?

Yes! One of the Q3 2025 milestones is the launch of the AI DNA Marketplace, where users can:

Sell AI models with specific intelligence capabilities.
License AI agents for use in other applications.
Merge different AI models to create advanced intelligence hybrids.

13. Will DNAi work with Web3 & Blockchain?

We are actively exploring Web3 integration for:

Decentralized AI tracking (storing AI DNA evolution on-chain).
Smart contract-based AI licensing (securing AI ownership & royalties).
DAO governance models for community-led AI merging rules.

14. How does DNAi prevent unethical AI use?

DNAi follows strict ethical AI principles, ensuring:

AI agents cannot be weaponized or misused.
Bias detection & monitoring systems are in place.
Transparency in AI merging history via the Neo4j knowledge graph.

Additionally, we are working on AI reputation tracking, ensuring that only trusted, validated AI agents are merged and evolved.

15. How can I contribute to DNAi?

Developers, AI researchers, and Web3 engineers can contribute by:

Building AI models for Digital DNA mapping.
Helping refine AI merging logic & contextual memory improvements.
Developing AI evolution analytics using LangChain & Neo4j.

Contributions can be made through our GitHub repo (coming soon).

Interested in partnering with us? Reach out to the team!

PreviousHow to Contribute

Last updated 22 days ago