Merge branch 'main' into BOLT_merge

Author: GayathriNarayana19

.wordlist.txt

@@ -4184,4 +4184,55 @@ subgenre
 submodule
 subword
 techcrunch
-transformative
+transformative
+Aude
+Gian
+Iodice
+SmolLM
+VME
+Vuilliomenet
+cpus
+fLO
+invalidations
+libtensorflowlite
+macos
+multithreaded
+Wix's
+ngrok's
+qs
+qu
+Mbps
+SVMATCH
+abd
+bitvector
+bitvectors
+iperf
+normals
+svcntb
+svmatch
+tc
+Alexa
+BLERP
+Cepstral
+Datagram
+Edudzi
+GDPR
+Gbit
+Gershon
+HIPAA
+HVAC
+Kordorwu
+MCUs
+MFCC
+Mbit
+PDM
+Situnayake
+accelerometers
+iPerf
+libcrypto
+libray
+libssl
+misclassification
+retransmission
+subquery
+uninstrumented

content/install-guides/aws-q-cli.md

@@ -206,6 +206,33 @@ based distributions like Ubuntu, which is your preference.
 
 Give it a try by asking questions like "How do I install the AWS CLI?" and verify that the answers match the provided context.
 
+## How do I change the model Amazon Q uses?
+
+When you start `q chat` the model is printed:
+
+```output
+🤖 You are chatting with claude-3.7-sonnet
+```
+
+You can use the `/model` command to list other available models.
+
+```console
+/model
+```
+
+The model options are displayed:
+
+```output
+? Select a model for this chat session ›
+❯ claude-4-sonnet
+  claude-3.7-sonnet (active)
+  claude-3.5-sonnet
+```
+
+Use the arrow keys and select the model you want to use. 
+
+You can ask Amazon Q to set the default model for future sessions.
+
 ## Install an MCP server
 
 As an example of using MCP with Amazon Q, you can configure the Github MCP server. 

content/learning-paths/automotive/openadkit1_container/3_setup_openadkit.md

@@ -32,7 +32,7 @@ Docker version 28.0.4, build b8034c0
 Clone the demo repository using:
 
 ```bash
-git clone https://github.com/autowarefoundation/openadkit_demo.autoware.git
+git clone https://github.com/odincodeshen/openadkit_demo.autoware.git
 ```
 
 The project is containerized in three Docker images, so you do not need to install any additional software.

content/learning-paths/cross-platform/mcp-ai-agent/intro-to-mcp-uv.md

@@ -17,7 +17,7 @@ The Model Context Protocol (MCP) is an open specification designed to connect La
 
 - **Security by design:** MCP encourages running servers inside your own infrastructure, so sensitive data stays within your infrastructure unless explicitly shared.
 
-- **Cross-ecosystem momentum:** recent roll-outs from an official C# SDK to Wix’s production MCP server and Microsoft’s Azure support show the MCP spec is gathering real-world traction.
+- **Cross-ecosystem momentum:** recent roll-outs from an official C# SDK to Wix's production MCP server and Microsoft’s Azure support show the MCP spec is gathering real-world traction.
 
 ## What is uv?
 

content/learning-paths/cross-platform/mcp-ai-agent/mcp-server.md

@@ -115,7 +115,7 @@ INFO:     Uvicorn running on http://0.0.0.0:8000 (Press CTRL+C to quit)
 
 You will now use ngrok to expose your locally running MCP server to the public internet over HTTPS.
 
-1. Add ngrok’s repo to the apt package manager and install:
+1. Add ngrok's repo to the apt package manager and install:
 ```bash
 curl -sSL https://ngrok-agent.s3.amazonaws.com/ngrok.asc \
   | sudo tee /etc/apt/trusted.gpg.d/ngrok.asc >/dev/null \

content/learning-paths/embedded-and-microcontrollers/_index.md

@@ -10,7 +10,7 @@ key_ip:
 maintopic: true
 operatingsystems_filter:
 - Android: 1
-- Baremetal: 29
+- Baremetal: 30
 - Linux: 28
 - macOS: 6
 - RTOS: 9
@@ -29,7 +29,7 @@ subtitle: Learn best practices for microcontroller development
 title: Embedded and Microcontrollers
 tools_software_languages_filter:
 - AI: 1
-- Arduino: 1
+- Arduino: 2
 - Arm Compiler for Embedded: 7
 - Arm Compiler for Linux: 1
 - Arm Compute Library: 1
@@ -51,6 +51,8 @@ tools_software_languages_filter:
 - DetectNet: 1
 - Docker: 9
 - DSTREAM: 2
+- Edge AI: 1
+- Edge Impulse: 1
 - ExecuTorch: 2
 - Fixed Virtual Platform: 9
 - FPGA: 1
@@ -61,6 +63,7 @@ tools_software_languages_filter:
 - GitHub: 3
 - GitLab: 1
 - Himax SDK: 1
+- Hugging Face: 3
 - IP Explorer: 4
 - Jupyter Notebook: 1
 - K3s: 1
@@ -87,7 +90,7 @@ tools_software_languages_filter:
 - STM32: 2
 - TensorFlow: 3
 - TensorRT: 1
-- tinyML: 1
+- tinyML: 2
 - Trusted Firmware: 3
 - TrustZone: 2
 - TVMC: 1

content/learning-paths/embedded-and-microcontrollers/edge/_index.md

@@ -0,0 +1,64 @@
+---
+title: Learn How to Run AI on Edge Devices- Arduino Nano RP2040
+
+draft: true
+cascade:
+    draft: true
+
+minutes_to_complete: 90
+
+who_is_this_for: This learning path is for beginners in Edge AI and TinyML, including developers, engineers, hobbyists, AI/ML enthusiasts, and researchers working with embedded AI and IoT.  
+
+learning_objectives:
+    - Understand Edge AI and TinyML basics. 
+    - Collect and preprocess audio data using Edge Impulse. 
+    - Train and deploy an audio classification model on Arduino Nano RP2040 
+    - Interface with LEDs to switch them on and off . 
+
+prerequisites:
+    - Explore this [learning path](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/arduino-pico/) if you are an absolute beginner.
+    - An [Edge Impulse](https://edgeimpulse.com/) Studio account. 
+    - The [Arduino IDE with the RP2040 board support package](https://learn.arm.com/install-guides/arduino-pico/) installed on your computer 
+    - An Arduino Nano RP2040 Connect [board](https://store.arduino.cc/products/arduino-nano-rp2040-connect-with-headers?_gl=1*9t4cti*_up*MQ..*_ga*NTA1NTQwNzgxLjE3NDYwMjIyODk.*_ga_NEXN8H46L5*MTc0NjAyMjI4Ny4xLjEuMTc0NjAyMjMxOC4wLjAuMjA3MjA2NTUzMA..). 
+
+author: Bright Edudzi Gershon Kordorwu
+### Tags
+skilllevels: Introductory
+subjects: tinyML
+armips:
+    - Cortex-M
+   
+tools_software_languages:
+    - Edge Impulse
+    - tinyML
+    - Edge AI
+    - Arduino
+operatingsystems:
+    - Baremetal
+    
+
+
+
+further_reading:
+    
+    - resource:
+        title: TinyML Brings AI to Smallest Arm Devices 
+        link: https://newsroom.arm.com/blog/tinyml
+        type: blog
+    - resource:
+        title: What is edge AI? 
+        link: https://docs.edgeimpulse.com/nordic/concepts/edge-ai/what-is-edge-ai
+        type: blog
+    - resource:
+        title: Edge Impulse for Beginners 
+        link: https://docs.edgeimpulse.com/docs/readme/for-beginners
+        type: doc 
+
+
+
+### FIXED, DO NOT MODIFY
+# ================================================================================
+weight: 1                       # _index.md always has weight of 1 to order correctly
+layout: "learningpathall"       # All files under learning paths have this same wrapper
+learning_path_main_page: "yes"  # This should be surfaced when looking for related content. Only set for _index.md of learning path content.
+---

content/learning-paths/embedded-and-microcontrollers/edge/_next-steps.md

@@ -0,0 +1,8 @@
+---
+# ================================================================================
+#       FIXED, DO NOT MODIFY THIS FILE
+# ================================================================================
+weight: 21                  # Set to always be larger than the content in this path to be at the end of the navigation.
+title: "Next Steps"         # Always the same, html page title.
+layout: "learningpathall"   # All files under learning paths have this same wrapper for Hugo processing.
+---

content/learning-paths/embedded-and-microcontrollers/edge/connect-and-set-up-arduino.md

@@ -0,0 +1,71 @@
+---
+title: Board Connection and IDE setup
+weight: 4
+
+### FIXED, DO NOT MODIFY
+layout: learningpathall
+---
+
+### Arduino Nano RP2040
+
+To get started with your first **TinyML project**, a great option is the **Arduino Nano RP2040 Connect**. Built by Arduino, it uses the powerful **RP2040 microcontroller** and is fully supported by the Arduino core package. The board comes with built-in Wi-Fi, Bluetooth, and an onboard IMU—features that make it ideal for deploying machine learning models at the edge.
+
+![example image alt-text#center](images/nano.png "Arduino Nano RP2040")
+
+Its compatibility with popular tools like Edge Impulse and the Arduino IDE makes it a beginner-friendly yet powerful choice for TinyML applications. You can learn more about the Arduino Nano RP2040 Connect on the [official Arduino website](https://store.arduino.cc/products/arduino-nano-rp2040-connect-with-headers?_gl=1*1laabar*_up*MQ..*_ga*MTk1Nzk5OTUwMS4xNzQ2NTc2NTI4*_ga_NEXN8H46L5*czE3NDY1NzY1MjUkbzEkZzEkdDE3NDY1NzY5NTkkajAkbDAkaDE1MDk0MDg0ODc.).
+
+## Put everything together
+
+### Step 1: Connect the LED to the Arduino Nano RP2040
+
+To visualize the output of the voice command model, we will use a simple LED circuit.
+
+### Components Needed
+
+- Arduino Nano RP2040 Connect
+- 1x LED
+- 1x 220Ω resistor
+- Breadboard and jumper wires
+
+#### Circuit Diagram
+
+- **Anode (long leg) of the LED** → Connect to **GPIO pin D2** via the 220Ω resistor
+- **Cathode (short leg)** → Connect to **GND**
+
+![example image alt-text#center](images/led_connection.png "Figure 14. Circuit Connection")
+
+![example image alt-text#center](images/led_connection_schematic.png "Figure 15. Circuit Schematic Connection")
+
+### Step 2: Set Up the Arduino IDEs
+
+To program and deploy your trained model to the Arduino Nano RP2040, you first need to configure your development environment.
+
+Follow the detailed setup instructions provided in the following learning path:
+
+[Arduino Nano RP2040 Setup Guide](https://learn.arm.com/install-guides/arduino-pico/)
+
+This guide will walk you through:
+
+- Installing the Arduino IDE
+- Adding the board support package for the Nano RP2040
+
+{{% notice Note %}}
+**Note:** Follow every instruction in the guide **except** `How do I set up the Raspberry Pi Pico W?`, as it is not needed for this project.
+{{% /notice %}}
+
+### Step 3: Select Your Board and Port in the Arduino IDE
+
+First, open the **Arduino IDE**.
+
+To select your board:
+
+1. Go to **Tools** > **Board**.
+2. From the list, choose **Arduino Nano RP2040 Connect**.
+
+To select your port:
+
+1. Connect your Arduino board to your computer using a USB cable.
+2. Go to **Tools** > **Port**.
+3. Select the port labeled with your board’s name, e.g., `COM4 (Arduino Nano RP2040 Connect)` or `/dev/cu.usbmodem...` on macOS.
+
+*Your Arduino IDE is now ready to upload code to the Arduino Nano RP2040.*