Original source: AgentLayer

At the AI ​​Apex Asia Capital Connect Forum, a panel of experts from fields such as AI Agent, Security Alignment, Intellectual Property and Compliance came together to discuss the complex environment facing AI companies preparing for an initial public offering (IPO). Moderated by James Liu, International Director of Alibaba Cloud, the roundtable provided crucial insights into the evolving regulatory environment and strategies for success.

Key points of discussion included:

1. AI companies face unprecedented challenges in data privacy, intellectual property protection, and regulatory compliance as they prepare for IPOs.

2. The pace of AI innovation often outstrips the development of regulatory frameworks, requiring companies to proactively address potential risks and communicate effectively with stakeholders.

3. Collaboration between AI companies and regulators is critical to developing a framework that promotes innovation while protecting the public interest.

4. The EU AI Act represents a major shift in AI regulation with global implications for companies operating or selling products in the European market.

5. Deep fake technology poses significant risks to copyright and identity protection, which require a combination of technical and regulatory solutions to address.

6. Purpose-built AI Agents offer a promising approach to enhance the safety and security of large language models (LLMs).

Professor Yang Liu, co-founder of AgentLayer, emphasized the evolving nature of AI security risks and proposed an innovative solution: “When you use any AI solution, you need to understand the possible new attacks. For example, we have seen some breakthroughs in jailbreaking AI models, which can bypass existing defense mechanisms with a 100% success rate. This poses a big challenge to any AI solution we are developing.”

Professor Liu further elaborated on a novel approach to address these challenges: “By enhancing LLMs with agent-based models as verifiers and managers, this approach adapts to the complexity within enterprises while focusing on creating automated LLM verifiers and managers. Rather than focusing solely on whether using LLMs is safe for the enterprise, purpose-built AI agents are used to verify and manage all LLM interactions. Even if the underlying LLM itself is not safe, the use of these special agents can help enterprises ensure the results of their interactions are safe.”

Hsu Li-Chuan, partner at Dentons Rodyk, stressed the importance of clear communication with regulators and investors: “The difficulty with AI is that it covers so many different regulatory areas, unlike e-commerce or even blockchain technology. AI may involve a wider range of regulatory, compliance and ethical areas. We need to keep this in mind when conducting any fundraising activities in the public markets.”

Yang Jingwei, technical director of Ant Security, stressed the need for strong technical solutions: “For data security, I have three suggestions: establish very strong data governance, have strict policies and normalization, be very careful about data transfer, and be transparent about data usage. For intellectual property, consult with intellectual property experts, seek patent protection, and have clear intellectual property ownership contracts.”

Moderator James Liu concluded: “The key takeaway is that communication with investors, the public, and regulators is critical in the pre- and post-IPO period. Since technology often evolves faster than regulation, self-regulation and frameworks are particularly important. As Professor Liu proposed, augmenting LLM with purpose-built AI Agents represents a promising direction to address current safety and security issues in the AI ​​industry.”

Experts agree that with the rapid development of AI, companies must stay ahead of governance issues to successfully complete the IPO process and maintain public trust. Ongoing dialogue between industry, academia, and regulators will play a key role in shaping a balanced approach to AI governance, while emerging technologies like AI Agents will play a central role in ensuring the safety and effective deployment of AI systems.

This article is contributed by a contributor and does not necessarily represent the views of BlockBeats.

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