---
title: "Slides: Voice AI: when is the \"Her\" moment? — Neil Zeghidour, CEO, Gradium AI"
category: "slides"
video_id: "P_RI1kCkRbo"
sourceLabels: ["Public YouTube video frames", "Public YouTube metadata"]
---

# Slides: Voice AI: when is the "Her" moment? — Neil Zeghidour, CEO, Gradium AI

## Source Video
[Voice AI: when is the "Her" moment? — Neil Zeghidour, CEO, Gradium AI](https://www.youtube.com/watch?v=P_RI1kCkRbo)

## Relationship To World's Fair 2026
These slides are extracted from a public AI Engineer YouTube video connected to World's Fair 2026. Speaker-matched clips are supporting context unless later confirmed as exact session recordings; official livestream recordings are day-level/event-level source material.

## Related Scheduled Sessions
- No individual scheduled session mapping has been assigned yet; treat this as an event livestream deck.

## Extracted Slides
![[assets/slides/P_RI1kCkRbo/slide-001.jpg]]

OCR text:

> PLATINUM SPONSORS
> Braintrust WorkOS OpenAI

![[assets/slides/P_RI1kCkRbo/slide-002.jpg]]

OCR text:

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![[assets/slides/P_RI1kCkRbo/slide-003.jpg]]

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![[assets/slides/P_RI1kCkRbo/slide-004.jpg]]

OCR text:

> From ResearchtoProduction
> Kyutai Breakthrough
> Paris-basedopenscience Al lab. Founded2023withE300M. Moshi:firstspeech-native Research
> AIE Team from MetaFAIR,Google DeepMind,and Inria. Hibiki-Zero:real-time
> speech-to-speech translation.
> moshi.chat by/kyutai Buito bringresearchtoproduction.$70Mraised in2025. Gradium:Scaling Impact Pocket-TTS:CPUmodelforTTS
> AIEngineer
> AIEngineer EUROPE

![[assets/slides/P_RI1kCkRbo/slide-005.jpg]]

OCR text:

> AIE
> AI Engineer
> Engineering the future of AI

![[assets/slides/P_RI1kCkRbo/slide-006.jpg]]

OCR text:

> AIE
> Engineering the future of AI
> AIEngineer

![[assets/slides/P_RI1kCkRbo/slide-007.jpg]]

OCR text:

> In real life...
> AIE
> AI Engineer
> EUROPE

![[assets/slides/P_RI1kCkRbo/slide-008.jpg]]

OCR text:

> In real life...
> ai-PULSE
> AIE
> byScdewoy
> Engineering the future of Al
> AIEngineer
> COROFL

![[assets/slides/P_RI1kCkRbo/slide-009.jpg]]

OCR text:

> Engineering the future of AI

![[assets/slides/P_RI1kCkRbo/slide-010.jpg]]

OCR text:

> Whatismissing?
> Latency
> Contextual Fillers
> User
> AIE
> Agent
> STT
> LLMFillers
> TTS
> Tool Calling
> TTS
> Engineering the future of Al
> AIEngineer

![[assets/slides/P_RI1kCkRbo/slide-011.jpg]]

OCR text:

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> _ €3 Braintrust €) WorkOS OpenAl

![[assets/slides/P_RI1kCkRbo/slide-012.jpg]]

OCR text:

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![[assets/slides/P_RI1kCkRbo/slide-013.jpg]]

OCR text:

> lie glayed:
> AIE
> /.kyutai
> Engineering the future of Al
> AIEngineer

![[assets/slides/P_RI1kCkRbo/slide-014.jpg]]

OCR text:

> Moshi Lessons Learned
> What Works Well
> Full-Duplex Conversation: Natural, uninterrupted
> dialogue flow
> Real-time Interaction: Truly conversational AI, user and
> AI speak simultaneously
> Challenges
> A research prototype, not a real agent
> Lack of observability and reliability
> Does not convey or understand empathy well
> Engineering the future of AI

![[assets/slides/P_RI1kCkRbo/slide-015.jpg]]

OCR text:

> GradiumPhonon Real-Time InferenceonCPU
> CPUInference Weights WER SpeakerSim
> Faster than real-time with no perceptible delay Phonon ~100M 1.48% 56.37%
> AIE Kani TTS 2 450M 4.97% 40.73%
> Personalization NeuTTS Air 552M 2.18% 47.51%
> Multilingual+canreproduce any voicefroma short referenceclip,noretrainingrequired Kokoro NeuTTSNano 229M 100M 1.71% 0.90% 40.15%
> SOTAperformance
> Benchmarkon seed-tts→
> Engineering the future of Al
> AIEngineer

![[assets/slides/P_RI1kCkRbo/slide-016.jpg]]

OCR text:

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![[assets/slides/P_RI1kCkRbo/slide-017.jpg]]

OCR text:

> AI Engineer
> EUROPE
> HTTPS://AI.ENGINEER

## Slide-Derived Subjects To Review
Subject extraction uses video title, related session titles/descriptions, transcript context, and OCR text when available. OCR is best-effort and should be reviewed against the embedded slide images.