Andrew Ng – The Rise of Agentic Workflows in AI

AI Governance Expert

The rapid advancements in AI technologies like RAG and iterative workflows present significant governance challenges. Ensuring ethical AI use requires established guidelines that prioritize data transparency and user privacy. As AI becomes integrated into everyday services, the potential for bias in retrieval processes must be monitored, ensuring equitable access and fairness in generated outputs. Countries and organizations will need to collaborate on setting a global standard for responsible AI systems to navigate these complexities.

AI Behavioral Science Expert

The shift towards making AI more accessible through iterative and generative workflows could facilitate significant changes in user behavior, making complex tasks more manageable. The ability to customize AI responses through iterative prompts encourages active user engagement, leading to enhanced learning and task performance. This change in interaction patterns has potential implications for education and healthcare, where AI can support personalized learning and patient care, improving outcomes and user satisfaction in real-life scenarios.

Retrieval Augmented Generation (RAG)

This technique enhances the AI's ability to generate better responses based on relevant data.

Generic Workflows

This method enables AI to adapt and produce results through several cycles instead of generating a single draft.

ChatGPT

It serves as an example of how iterative prompts can enhance AI's output quality.

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Claude

Claude's capabilities illustrate the evolution of generative AI technologies.

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Gemini

Gemini exemplifies advancements in AI response generation.

Mentions: 2