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Content provided by Tejas Kumar. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Tejas Kumar or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.
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Chinar Movsisyan: How to Deliver End-to-End AI Solutions

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Manage episode 493171456 series 3676184
Content provided by Tejas Kumar. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Tejas Kumar or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

Links

- Codecrafters (sponsor): https://tej.as/codecrafters

- Feedback Intelligence: https://www.feedbackintelligence.ai/

- Chinar on X: https://x.com/movsisyanchinar


Summary


In this podcast episode, we talk to Chinar Movsisyan, the CEO and founder of Feedback Intelligence. They discuss Chinar's extensive background in AI, including her experience in machine learning and computer vision. We discuss the challenges faced in bridging the gap between technical and non-technical stakeholders, the practical applications of feedback intelligence in enhancing user experience, and the importance of identifying failure modes. The discussion also covers the role of LLMs in the architecture of Feedback Intelligence, the company's current stage, and how it aims to make feedback actionable for businesses.


Chapters


00:00 Chinar Movsisyan

02:08 Introduction to Feedback Intelligence

03:23 Chinar Movsisyan's Background and Expertise

06:33 Understanding AI Engineer vs. GenAI Engineer

09:08 The Lifecycle of Building an AI Application

13:27 Data Collection and Cleaning Challenges

16:20 Training the AI Model: Process and Techniques

24:48 Deploying and Monitoring AI Models in Production

27:55 The Birth of Feedback Intelligence

31:58 Understanding Feedback Intelligence

33:26 Practical Applications of Feedback Intelligence

42:13 Identifying Failure Modes

45:58 The Role of LLMs in Feedback Intelligence

51:25 Company Stage and Future Directions

57:24 Making Feedback Actionable

01:01:30 Streamlining Processes with Automation

01:03:18 The Journey of a First-Time Founder

01:05:48 Wearing Many Hats: The Founder Experience

01:08:22 Prioritizing Features in Early Startups

01:13:09 Learning from Customer Interactions

01:16:38 The Importance of Problem-Solving

01:21:51 Handling Rejection and Staying Motivated

01:27:43 Marketing Challenges for Founders

01:29:23 Future Plans and Scaling Strategies


Hosted on Acast. See acast.com/privacy for more information.

  continue reading

88 episodes

Artwork
iconShare
 
Manage episode 493171456 series 3676184
Content provided by Tejas Kumar. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Tejas Kumar or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

Links

- Codecrafters (sponsor): https://tej.as/codecrafters

- Feedback Intelligence: https://www.feedbackintelligence.ai/

- Chinar on X: https://x.com/movsisyanchinar


Summary


In this podcast episode, we talk to Chinar Movsisyan, the CEO and founder of Feedback Intelligence. They discuss Chinar's extensive background in AI, including her experience in machine learning and computer vision. We discuss the challenges faced in bridging the gap between technical and non-technical stakeholders, the practical applications of feedback intelligence in enhancing user experience, and the importance of identifying failure modes. The discussion also covers the role of LLMs in the architecture of Feedback Intelligence, the company's current stage, and how it aims to make feedback actionable for businesses.


Chapters


00:00 Chinar Movsisyan

02:08 Introduction to Feedback Intelligence

03:23 Chinar Movsisyan's Background and Expertise

06:33 Understanding AI Engineer vs. GenAI Engineer

09:08 The Lifecycle of Building an AI Application

13:27 Data Collection and Cleaning Challenges

16:20 Training the AI Model: Process and Techniques

24:48 Deploying and Monitoring AI Models in Production

27:55 The Birth of Feedback Intelligence

31:58 Understanding Feedback Intelligence

33:26 Practical Applications of Feedback Intelligence

42:13 Identifying Failure Modes

45:58 The Role of LLMs in Feedback Intelligence

51:25 Company Stage and Future Directions

57:24 Making Feedback Actionable

01:01:30 Streamlining Processes with Automation

01:03:18 The Journey of a First-Time Founder

01:05:48 Wearing Many Hats: The Founder Experience

01:08:22 Prioritizing Features in Early Startups

01:13:09 Learning from Customer Interactions

01:16:38 The Importance of Problem-Solving

01:21:51 Handling Rejection and Staying Motivated

01:27:43 Marketing Challenges for Founders

01:29:23 Future Plans and Scaling Strategies


Hosted on Acast. See acast.com/privacy for more information.

  continue reading

88 episodes

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