She is also super fun to talk to!

We discussed:

– How to empower developers to understand and work with AI

– Lamini's technical approach to AI hallucinations (it's solvable!)

– Why benchmarks ≠ reality

– A notable industry use case and the importance of focusing on objective outputs: Subjective goals confuse it!

– And one of my favourite moments: Sharon crushes two of the hottest topics – agents and RAG. Turns out researchers don’t understand why there’s all this hype around these two.

– We also talked about open-source and its importance.

– And last but not least, Sharon (who teaches millions on Coursera) shared how to fight the lack of knowledge about AI. Her recipe: lower the barrier to entry, help people level up – plus memes!

Please give this video a watch and tell us what you think!

Likes and subscribing to the channel are hugely appreciated.

00:00 Intro & Sharon Zhou’s Early Days in GenAI

01:25 Maternal Instincts for AI Models

02:42 From Classics to Code: Language, Product, and AI

04:30 The Spark Behind Lamini

07:45 Solving Hallucinations at a Technical Level

09:20 Benchmarks That Matter to Enterprises

11:58 Staying Technical as a Founder

13:27 The Agent & RAG Hype: Industry Misconceptions

18:44 Use Cases: From Colgate to Cancer Research

20:07 The Power of Objective Use Cases

22:28 What Comes After Hallucinations?

23:21 Following AI Research (and When It’s Useful)

26:23 Open Source & Model Ownership Philosophy

28:06 Bringing AI Education to Everyone

32:36 AI Natives & Edutainment for the Next Gen

34:18 Outro

Lamini

Website - https://www.lamini.ai

Twitter - https://x.com/laminiai

Sharon Zhou

LinkedIn - https://www.linkedin.com/in/zhousharon/

Twitter - https://x.com/realSharonZhou/

Turing Post

Website - https://www.turingpost.com/

Twitter - https://x.com/TheTuringPost

Ksenia Se (publisher)

LinkedIn - https://www.linkedin.com/in/ksenia-se

Twitter - https://x.com/kseniase_

What needs to happen for natural, free-flowing multilingual conversations to become reality? Mati says: give it two or three years. Watch to learn more!

Guest:

Mati Staniszewski, co-founder and CEO at ElevenLabs

Website: https://elevenlabs.io/

Additional Reading:

https://www.turingpost.com/p/mati

Chapters

0:00 Real-time voice translation

0:11 Language barriers and AI

0:29 Why ElevenLabs started

0:36 Dubbing in Poland

0:45 Preserving emotion in translation

1:06 Tech challenges in real-time translation

1:17 Ideal device setup

2:32 Speaker diarization and emotional nuance

3:04 Speech-to-text to LLM to TTS pipeline

5:51 Concrete examples: healthcare & customer support

7:05 Real-time AI dubbing use cases

8:02 Lex Fridman podcast dubbing challenge

13:01 Audio model performance & latency

14:44 Conversational AI & multimodal future

16:57 Product vs research focus at ElevenLabs

20:42 Why ElevenLabs didn't open source (yet)

21:28 Strategy: creators, enterprises & brand building

Turing Post is a newsletter about AI's past, present, and future. Publisher Ksenia Semenova explores how intelligent systems are built—and how they’re changing how we think, work, and live.

Sign up: Turing Post: https://www.turingpost.com

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