The Future of AI and Consumer Empowerment // MLOps podcast #244 with Shaun Wei, CEO & Co-Founder of RealChar.

A big thank you to LatticeFlow for sponsoring this episode! LatticeFlow - https://latticeflow.ai/

// Abstract

Explore the groundbreaking work RealChar is doing with its consumer application, Rivia. This discussion focuses on how Rivia leverages Generative AI and Traditional Machine Learning to handle mundane phone calls and customer service interactions, aiming to free up human time for more meaningful tasks. The product, currently in beta, embodies a forward-thinking approach to AI, where the technology offloads day-to-day burdens like scheduling appointments and making calls.

// Bio

Shaun Wei is a well-connected technology professional with a rich background in developing and analyzing artificial intelligence systems. In 2018, Shaun played a pivotal role in the advent and deployment of Google Duplex, a remarkable AI capable of handling natural conversations and performing tasks such as booking hair salon appointments and restaurant reservations via telephone. His involvement wasn't just limited to the developmental side; Shaun also uniquely positioned himself on the receiving end, gathering insights by interviewing users directly impacted by the technology. This dual perspective has enabled Shaun to grasp both the technical underpinnings and the human-centric applications of AI, making him a valuable asset in the tech industry.

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// Related Links

https://www.rivia.tech/

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Timestamps:

[00:00] Shaun's preferred coffee

[00:28] Takeaways

[03:30] Please like, share, leave a review, and subscribe to our MLOps channels!

[03:57] AI in Production: Challenges & Insights

[06:13] AI Scheduling and Assistance

[08:00] Technical Challenges in AI

[12:36 - 14:06] LatticeFlow Ad

[14:09] Handling Challenges in AI

[15:52] Learning driving and technical aspects

[19:04] Self-Driving Cars: Multimodal Integration

[23:41] Processing data with Transformers

[26:46] Real-time phone data gathering

[30:49] Real-time observability in AI

[35:09] Time to first token

[37:26] Preferred vs. Dynamic Model Selection

[40:12] Event-driven architecture basics

[42:06] Navigating challenges together

[44:02] Challenges with Inconsistent Responses

[45:40] Importance of product reliability

[47:47] Training Data and Model Performance

[50:02] Exploring AI in Customer Service

[51:34] Navigating challenges in AI

[53:15] Excited Launch Strategy Advice

[57:10] Wrap up