SoulNet
  • ▶️Introduction
  • 1️⃣Market Background
  • 2️⃣SoulNet Overview
  • 3️⃣SoulNet Architecture
  • 4️⃣SoulNet Core Features
  • 5️⃣Application Scenarios
  • 6️⃣Token Economy Model
  • 7️⃣SoulNet Team
  • 8️⃣Roadmap
  • ⏹️References
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References

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Last updated 2 months ago

1. Park, H., & Song, M. (2023). Personalized AI Agents in Decentralized Systems: A Review and Taxonomy. IEEE Transactions on Artificial Intelligence.

2. OpenAI. (2023). GPT-4 Technical Report. OpenAI Research,

3. LeCun, Y., d’Autume, C. D., & Synnaeve, G. (2022). A Path Towards Autonomous Machine Intelligence. Meta AI Research Whitepaper.

4. Bai, Y., Kadavath, S., Kundu, S., et al. (2023). Constitutional AI: Harmlessness from AI Feedback. Anthropic AI, https://www.anthropic.com/index/2023/02

5. Xu, X., Liu, Y., & Zhang, H. (2023). Train-to-Earn: Blockchain-based Incentive Mechanism for Collaborative AI Training. arXiv preprint arXiv:2301.07368.

6. Li, S., Liu, J., & Wang, S. (2023). Decentralized AI Model Ownership and Verification on Blockchain. IEEE Access, 11, 102233–102248.

7. Andreassen, H., & Ramamoorthy, A. (2022). Giving AI a Soul: Towards Emotional and Ethical Embodiment in Virtual Agents. Journal of Human-Centered AI, 3(1).

8. Vaswani, A., Shazeer, N., Parmar, N., et al. (2017). Attention is All You Need. Advances in Neural Information Processing Systems, 30.

9. Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning. MIT Press.

10. Riedl, M. O., & Harrison, B. (2016). Human-Centered Artificial Intelligence and Interactive Storytelling. AI Magazine, 37(4), 67–77.

11. Silver, D., Schrittwieser, J., Simonyan, K., et al. (2021). Mastering the Game of Go Without Human Knowledge. Nature, 550(7676), 354–359.

12. Huang, Z., Zheng, J., & Zhang, Y. (2022). Soulful AI: Enhancing Digital Avatars with Personality Embedding. Proceedings of the AAAI Conference on Artificial Intelligence, 36(7), 7481–7488.

13. Bitton, M., & Ben-Sasson, E. (2022). ZKML: Applying Zero-Knowledge Proofs to Machine Learning Models. ZKProof.org Technical White Paper.

14. Cheng, Y., Tan, M., Wang, Y., & Yu, D. (2022). Federated Learning for Web3 AI Agents: A Scalable Approach. arXiv preprint arXiv:2210.12892.

15. Radford, A., Narasimhan, K., Salimans, T., & Sutskever, I. (2022). Language Models are Few-Shot Learners. OpenAI Blog,

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