From 18447fb07fbc312017da36c318526113945ea654 Mon Sep 17 00:00:00 2001
From: Maddy Underwood <167196745+madeline-underwood@users.noreply.github.com>
Date: Mon, 7 Jul 2025 20:48:14 +0000
Subject: [PATCH] Changed TFLite -> LiteRT in everything but code and file
 names

---
 .../ai-camera-pipelines/2-overview.md                         | 2 +-
 .../mobile-graphics-and-gaming/ai-camera-pipelines/3-build.md | 4 ++--
 .../ai-camera-pipelines/5-performances.md                     | 4 ++--
 3 files changed, 5 insertions(+), 5 deletions(-)

diff --git a/content/learning-paths/mobile-graphics-and-gaming/ai-camera-pipelines/2-overview.md b/content/learning-paths/mobile-graphics-and-gaming/ai-camera-pipelines/2-overview.md
index 1985a68688..4287f39064 100644
--- a/content/learning-paths/mobile-graphics-and-gaming/ai-camera-pipelines/2-overview.md
+++ b/content/learning-paths/mobile-graphics-and-gaming/ai-camera-pipelines/2-overview.md
@@ -46,7 +46,7 @@ The low-light enhancement pipeline is adapted from the LiveHDR+ method originall
 
 ![example image alt-text#center](lle_pipeline.png "Low-Light Enhancement Pipeline Diagram")
 
-The Low-Resolution Coefficient Prediction Network (implemented with TFLite) performs computations such as:
+The Low-Resolution Coefficient Prediction Network (implemented with LiteRT) performs computations such as:
 - Strided convolutions.
 - Local feature extraction using convolutional layers.
 - Global feature extraction using convolutional and fully connected layers.
diff --git a/content/learning-paths/mobile-graphics-and-gaming/ai-camera-pipelines/3-build.md b/content/learning-paths/mobile-graphics-and-gaming/ai-camera-pipelines/3-build.md
index 89128cfccb..04c311aaa9 100644
--- a/content/learning-paths/mobile-graphics-and-gaming/ai-camera-pipelines/3-build.md
+++ b/content/learning-paths/mobile-graphics-and-gaming/ai-camera-pipelines/3-build.md
@@ -74,9 +74,9 @@ Leave the container by pressing `Ctrl+D`.
 ## Notes on the cmake configuration options
 
 - `-DENABLE_SME2=$ENABLE_SME2` with `ENABLE_SME2=0`: SME2 (Scalable Matrix Extension 2) is disabled in this build (`0`).  
-- `-DARMNN_TFLITE_PARSER=0`: Configures the `ai-camera-pipelines` repository to use TFLite with XNNPack instead of ArmNN.
+- `-DARMNN_TFLITE_PARSER=0`: Configures the `ai-camera-pipelines` repository to use LiteRT with XNNPack instead of ArmNN.
 - `-DENABLE_KLEIDICV:BOOL=ON`: Enables KleidiCV for optimized image processing.
-- `-DXNNPACK_ENABLE_KLEIDIAI:BOOL=ON`:  Enables KleidiAI acceleration for TFLite workloads via XNNPack.
+- `-DXNNPACK_ENABLE_KLEIDIAI:BOOL=ON`:  Enables KleidiAI acceleration for LiteRT workloads via XNNPack.
 
 ## Install the pipelines
 
diff --git a/content/learning-paths/mobile-graphics-and-gaming/ai-camera-pipelines/5-performances.md b/content/learning-paths/mobile-graphics-and-gaming/ai-camera-pipelines/5-performances.md
index 4c11ee1168..1372ae1b5e 100644
--- a/content/learning-paths/mobile-graphics-and-gaming/ai-camera-pipelines/5-performances.md
+++ b/content/learning-paths/mobile-graphics-and-gaming/ai-camera-pipelines/5-performances.md
@@ -16,11 +16,11 @@ The application you built earlier includes a *benchmark mode* that runs the core
 These benchmarks demonstrate the performance improvements enabled by KleidiCV and KleidiAI:
 - KleidiCV enhances OpenCV performance with computation kernels optimized for Arm processors.
 
-- KleidiAI accelerates TFLite + XNNPack inference using AI-optimized micro-kernels tailored for Arm CPUs.
+- KleidiAI accelerates LiteRT + XNNPack inference using AI-optimized micro-kernels tailored for Arm CPUs.
 
 ## Performances with KleidiCV and KleidiAI
 
-By default, the OpenCV library is built with KleidiCV support, and TFLite+xnnpack is built with KleidiAI support. 
+By default, the OpenCV library is built with KleidiCV support, and LiteRT+xnnpack is built with KleidiAI support. 
 
 You can run the benchmarks using the applications you built earlier.