---
title: "Slides: Research to Reality: Bringing Frontier ML Research to Production - Vaidas Razgaitis, Higharc"
category: "slides"
video_id: "OXMMN-XbxwA"
sourceLabels: ["Public YouTube video frames", "Public YouTube metadata"]
---

# Slides: Research to Reality: Bringing Frontier ML Research to Production - Vaidas Razgaitis, Higharc

## Source Video
[Research to Reality: Bringing Frontier ML Research to Production - Vaidas Razgaitis, Higharc](https://www.youtube.com/watch?v=OXMMN-XbxwA)

## 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/OXMMN-XbxwA/slide-001.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/OXMMN-XbxwA/slide-001.html)
- AI slide classifier: `title_card` confidence `0.99`
- Text source: agent_vision.

Slide text:

> Research to Reality
> Turning frontier ML research into real, shipped features.
> Vaidas Razgaitis

![[assets/slides/OXMMN-XbxwA/slide-002.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/OXMMN-XbxwA/slide-002.html)
- AI slide classifier: `content_slide` confidence `0.91`
- Text source: advanced OCR `rapidocr-live/center-82/opencv-adaptive`.
- OCR decision: ready — Product/UI screenshot with small embedded text that is better handled by OCR.

Slide text:

> ESTMMATED IQIAL COST:
> 000'65,
> Buiding data model.
> Show mme suppies and cost.
> What wouid this cost to buld in the Northeast Division?

![[assets/slides/OXMMN-XbxwA/slide-003.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/OXMMN-XbxwA/slide-003.html)
- AI slide classifier: `content_slide` confidence `0.97`
- Text source: none.
- OCR decision: ready — Two-column diagram with small labels and dense text suitable for OCR.
![[assets/slides/OXMMN-XbxwA/slide-004.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/OXMMN-XbxwA/slide-004.html)
- AI slide classifier: `content_slide` confidence `0.98`
- Text source: agent_vision.

Slide text:

> Researchers ≠ production engineers

![[assets/slides/OXMMN-XbxwA/slide-005.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/OXMMN-XbxwA/slide-005.html)
- AI slide classifier: `content_slide` confidence `0.96`
- Text source: none.
- OCR decision: ready — Article-like screenshot with dense small text; OCR is more appropriate than manual transcription here.
![[assets/slides/OXMMN-XbxwA/slide-006.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/OXMMN-XbxwA/slide-006.html)
- AI slide classifier: `content_slide` confidence `0.94`
- Text source: advanced OCR `rapidocr-live/bright-screen/contrast`.
- OCR decision: ready — Architecture diagram with multiple small labels and low-confidence embedded text; OCR is appropriate.

Slide text:

> TOrCU
> Repo automations
> DDEP blodo
> Microservices
> MLNokebopke M.models MLstudties +nodels
> TBO Re-usable UI components
> MONOREPO

![[assets/slides/OXMMN-XbxwA/slide-007.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/OXMMN-XbxwA/slide-007.html)
- AI slide classifier: `content_slide` confidence `0.98`
- Text source: agent_vision.

Slide text:

> Getting research to reality is a systems & process problem.
> 01 Make research legible
> 02 A monorepo that can receive new research
> 03 Decomposition as a design problem

![[assets/slides/OXMMN-XbxwA/slide-008.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/OXMMN-XbxwA/slide-008.html)
- AI slide classifier: `content_slide` confidence `0.95`
- Text source: advanced OCR `rapidocr-live/bright-screen/opencv-adaptive`.
- OCR decision: ready — Dense product/UI screenshot with many small text rows and PR metadata; OCR is a better fit than manual transcription.

Slide text:

> product #20315:
> studloAskAgentV1 flag AI-664: Rename agent feature flags with alpha suffix and add
> VRazgsts listure/iront-v1/itudio-Asx/eo-foatur+-flar-ienming: + doveloo: 5 fasi +24 -11. Updated 4w spo
> + Suck: t 1of 10 D Copy tuct **+
> #21114 A-701: Ul p4 ghel To orz. Morpod'; 22d
> #21113 A-70z Ul compose ar4 traad $211i2 A-700: U1 m#stge buobs ta Gz. Mrged: 2?d Merpod 27d
> $21111 Al-69g: U1 primtvos n2d
> p21110 AI:698: UI tounduton
> $21101 A1·697: U1 rotout docs Coied: 23d
> W205 i5 AI-676: 8rahntrust telertety + aproxry fetlrerert Merged'
> N20436 Al-653: serrw runbme Co shn2 iorgeo?
> LO433 Al:6Sr agtr icomman'srt/cHonl ptckage bucke + pLtorm?wida agtnt docs Bou LAusovrrvoiprs poe pue xns tyoe 4hm sbey onreog uode eieuny:+99.IV sIe] C q4 iuarged. smo Muped?
> (nnk) -


Classification audit: `raw/sources/slide-ai-classification/slides/OXMMN-XbxwA/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.