---
title: "Slides: From 46% to 90%: Fine-Tuning Tiny LLMs for On-Device Agents — Cormac Brick, Google"
category: "slides"
video_id: "-TiET_K-E_g"
sourceLabels: ["Public YouTube video frames", "Public YouTube metadata"]
---

# Slides: From 46% to 90%: Fine-Tuning Tiny LLMs for On-Device Agents — Cormac Brick, Google

## Source Video
[From 46% to 90%: Fine-Tuning Tiny LLMs for On-Device Agents — Cormac Brick, Google](https://www.youtube.com/watch?v=-TiET_K-E_g)

## 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/-TiET_K-E_g/slide-001.jpg]]

OCR text:

> PLATINUM SPONSORS
> Braintrust
> WorkOS
> OpenAI

![[assets/slides/-TiET_K-E_g/slide-002.jpg]]

OCR text:

> TLMs:TinyLLMsand
> AgentsonEdgeDevices
> AIE
> Bringing state-of-the-artagenticskilstothe
> edgewithopenmodels
> Cormac Brick, Principal Engineer, Google Al Edge
> GoogleDeepMind

![[assets/slides/-TiET_K-E_g/slide-003.jpg]]

OCR text:

> n Agenda 00 Al Edge. SLMs & TLMs
> 10 Agent Skills locally on Android & iOS
> * Sd
> oY a a 20 TLM workflow
> ey 30 TLMsin Action
> Engineering the future of Al

![[assets/slides/-TiET_K-E_g/slide-004.jpg]]

OCR text:

> System level GenAl
> AIE
> Gemini Nano with AlCore Apple Intelligence Writing
> summarization on Android tools on iOs
> Engineering the future of Al
> A12

![[assets/slides/-TiET_K-E_g/slide-005.jpg]]

OCR text:

> NEW
> Agent Skills & Gemma 4 E2B &
> (‘System GenAl' uses AlCore when avail
> Pee 3 .
> ae B92 59 eam
> . ; Bebe Si.
> a a oes Poe S360
> nd ~*
> OO
> Masi ones
> Woy pp bore
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> WOES cone ve
> Tek Can
> BRE Gare:
> wre
> i
> . | Al Engineer |
> EUROPE

![[assets/slides/-TiET_K-E_g/slide-006.jpg]]

OCR text:

> Example Skills - Restaurant Roulette
> ere g ;
> a
> ul : | f
> Engineering the future of Al

![[assets/slides/-TiET_K-E_g/slide-007.jpg]]

OCR text:

> Example Skills-Restaurant Roulette
> Whar'snew inGemma4
> AIE What'snewin
> Gemma4
> Engineering the future of Al
> AIE

![[assets/slides/-TiET_K-E_g/slide-008.jpg]]

OCR text:

> FunctionGemma TuningLab:Fine-Tuning
> atou
> tdetalls
> Signin with Hugging Face
> AIE
> 2.Tral
> Tool Schema&Datalmport
> Idas
> Step 2:UpldDataIOptin
> To tral
> onyour
> data,up
> adaCSv
> DropFile Here
> Engineering the future of Al
> AIEn

![[assets/slides/-TiET_K-E_g/slide-009.jpg]]

OCR text:

> Wrap up.
> System GenAI
> In-App GenAI

## 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.