---
title: "Slides: 20 days of compute vs 7 hours: rethinking what state-of-the-art means — Bertrand Charpentier, Pruna"
category: "slides"
video_id: "hqHC6Z_lXyo"
sourceLabels: ["Public YouTube video frames", "Public YouTube metadata"]
---

# Slides: 20 days of compute vs 7 hours: rethinking what state-of-the-art means — Bertrand Charpentier, Pruna

## Source Video
[20 days of compute vs 7 hours: rethinking what state-of-the-art means — Bertrand Charpentier, Pruna](https://www.youtube.com/watch?v=hqHC6Z_lXyo)

## 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/hqHC6Z_lXyo/slide-003.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/hqHC6Z_lXyo/slide-003.html)
- AI slide classifier: `content_slide` confidence `0.99`
- Text source: agent_vision.

Slide text:

> Method 1: Check Public Leaderboards
> Use-case: Find the most performant image editing AI model
> - Step 1: Find a leaderboard
> - Step 2: Select the top ranked model

![[assets/slides/hqHC6Z_lXyo/slide-004.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/hqHC6Z_lXyo/slide-004.html)
- AI slide classifier: `content_slide` confidence `0.98`
- Text source: advanced OCR `rapidocr-live/border-trim/contrast`.
- OCR decision: ready — small leaderboard screenshots and labels are better handled by OCR

Slide text:

> Problem 1: Each public leaderboard has a different ranking
> AIE
> (LM)Arena Design Arena Artificial Analysis
> Engineering the future of Al

![[assets/slides/hqHC6Z_lXyo/slide-005.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/hqHC6Z_lXyo/slide-005.html)
- AI slide classifier: `content_slide` confidence `0.98`
- Text source: advanced OCR `rapidocr-live/right-72/opencv-adaptive`.
- OCR decision: ready — chart text and small labels are better handled by OCR

Slide text:

> Problem 3:Leaderboard are not statistically significant for one use case
> Artificial Analysis ranking w! number of samples Win rate on (LM)Arena Win rate on Design Arena
> AlEngineer
> EUROPE

![[assets/slides/hqHC6Z_lXyo/slide-006.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/hqHC6Z_lXyo/slide-006.html)
- AI slide classifier: `content_slide` confidence `0.99`
- Text source: agent_vision.

Slide text:

> Method 2: Perform Internal Evaluation
> Use-case: Find the most performant image editing AI model
> - Step 1.a: Manual inspection

![[assets/slides/hqHC6Z_lXyo/slide-007.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/hqHC6Z_lXyo/slide-007.html)
- AI slide classifier: `content_slide` confidence `0.89`
- Text source: agent_vision.
- OCR decision: ready — Dense chart labels and small benchmark graphics are better handled by OCR.

Slide text:

> Problem 5: Benchmark results are not consistent

![[assets/slides/hqHC6Z_lXyo/slide-008.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/hqHC6Z_lXyo/slide-008.html)
- AI slide classifier: `content_slide` confidence `0.97`
- Text source: advanced OCR `rapidocr-live/border-trim/contrast`.
- OCR decision: ready — Multiple charts plus small bullet text make OCR the cheaper and more accurate path.

Slide text:

> Problem 5: Benchmark results are not consistent
> AIE
> Misaligned with target Benchmarkranking change Smal/largevariations Checkmeaningsofmetrics Use multiple metrics
> Engineering the future of Al

![[assets/slides/hqHC6Z_lXyo/slide-009.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/hqHC6Z_lXyo/slide-009.html)
- AI slide classifier: `content_slide` confidence `0.98`
- Text source: agent_vision.
- OCR decision: ready — Scatter plots and small axis labels are OCR-suitable.

Slide text:

> What Model is State-of-the-Art?

![[assets/slides/hqHC6Z_lXyo/slide-010.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/hqHC6Z_lXyo/slide-010.html)
- AI slide classifier: `content_slide` confidence `0.97`
- Text source: advanced OCR `rapidocr-live/bright-screen/contrast`.
- OCR decision: ready — The benchmark scatter plots and annotations are small enough that OCR will likely outperform manual transcription.

Slide text:

> What Model is State-of-the-Art?
> There are multiple SOTA Al models
> AIE Long Text Bench OeelGTertRenderieg
> 0:20
> 0.85
> 0.03
> 0.73
> 0.65 0.63
> 0.50 0.00
> 0.55 0.55
> Medin inference Time Mesinn IeterenceTime
> AI Engineer
> EUROPE

![[assets/slides/hqHC6Z_lXyo/slide-011.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/hqHC6Z_lXyo/slide-011.html)
- AI slide classifier: `content_slide` confidence `0.97`
- Text source: advanced OCR `rapidocr-live/border-trim/contrast`.
- OCR decision: ready — Endpoint cards and small brand/logo text are OCR-suitable.

Slide text:

> How To Reach SOTA Performance?
> Option 1:Use optimized Performance models
> AIE
> VideoEnipoints ImageEndpoints Text Endpoints AudioEndpoints
> Bopioote Koyed aws Runware Segmind WIRO
> Engineering the future of Al
> neer

![[assets/slides/hqHC6Z_lXyo/slide-012.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/hqHC6Z_lXyo/slide-012.html)
- AI slide classifier: `content_slide` confidence `0.97`
- Text source: advanced OCR `rapidocr-live/bright-screen/contrast`.
- OCR decision: ready — This slide has multiple small cards, labels, and links that are best left for OCR.

Slide text:

> How To Reach SOTA Performance?
> Option 1: Use optimized Performance models
> AIE
> VideoEndpoints Image Endpoints Text Endpoints AudioEndpoints
> Weplicoto Koyeb aws Runware Segmnd WIRO
> Option 2: Develop and apply inference optimization
> PrunoAI
> AI EfficiencyPackage AlEfficiencyMaterials AI Efficiency Courses
> aRaihub.comPnnaAwcoun
> AI Engineer
> JUUU


### Hidden Non-Slide Evidence
- [`slide-001.jpg`](/assets/slides/hqHC6Z_lXyo/slide-001.jpg) — `speaker_stage` confidence `0.98`; camera shot of speaker on stage with projected slide; not a clean slide frame
- [`slide-002.jpg`](/assets/slides/hqHC6Z_lXyo/slide-002.jpg) — `title_card` confidence `0.96`; title slide only; no substantive content

Classification audit: `raw/sources/slide-ai-classification/slides/hqHC6Z_lXyo/audit.json`

## 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.