Summary

In this conversation, Chinar Movsisyan shares her journey in AI, particularly focusing on her work with Feedback Intelligence.

She discusses the challenges of integrating AI in healthcare, the importance of closing the feedback loop in AI applications, and the shift towards using large language models (LLMs) in business.

Chinar emphasizes the need for personalization in AI chatbots and the significance of implicit feedback over explicit feedback. She reflects on her motivations as a founder and the future of AI in solving real-world problems.

Takeaways

• Feedback Intelligence aims to close the feedback loop in AI applications.


• Personalization in AI chatbots is crucial for user satisfaction.

• The shift towards LLMs is driven by the need for efficiency in businesses.


• Founders often face ups and downs in their journey, which is part of the process.


• AI should be used to solve real problems, not replace humans.


• The healthcare sector faces significant challenges in integrating AI due to regulations.


• Companies are increasingly adopting AI to improve operational efficiency.


• Building a startup requires passion and a willingness to solve problems.

Chapters

00:00 Chinar Movsisyan's Journey in AI

04:32 Feedback Intelligence: The Problem and Solution

11:00 Closing the Feedback Loop in AI

15:16 Optimizing Information Retrieval in Organizations

19:20 The Importance of Implicit Feedback

22:55 The Evolution of Feedback Intelligence

26:34 The Shift Towards LLM Adoption

31:02 The Journey of a Founder

35:55 AI's Potential to Solve Real Problems