Machine Learning (Silicon Labs AI/ML) Extension SDK Version 2.1.1 (July 23, 2025) - Release Notes#

Simplicity SDK Version 2025.6.1

The Machine Learning Extension is also known as "Silicon Labs AI/ML" and is provided as an extension to the Simplicity SDK. It enables AI/ML development on Series 2 and SiWG917 devices using the Tensorflow Lite for Microcontrollers (TFLM) framework.

Click here for earlier releases.

Release Summary#

Key Features | API Changes | Bug Fixes | Chip Enablement

Key Features#

Added in 2.1.1#

  • Added a new Image Classifier (Rock-Paper-Scissors) application and tutorial for xG24 and xG26 devices.

  • Fixed errors when creating projects using the "Copy Contents" feature in Simplicity Studio.

Added in 2.1.0#

  • Source code moved to an Extension.

  • AI/ML Extension is now Generally Available (GA), it was released as an alpha build earlier.

  • Added support for SiWG917 chip family through software optimizations.

  • Machine Learning (AI/ML) developer documentation has been re-organized.

API Changes#

Changed in 2.1.1#

None.

Changed in 2.1.0#

  • New APIs for model invocation and execution for SiWG917 chip family.

  • New variables for interacting with the ML models.

Bug Fixes#

Fixed in 2.1.1#

Fixed errors when creating projects using the "Copy Contents" feature in Simplicity Studio.

Fixed in 2.1.0#

Fixed memory leak of mic when model does not load correctly.

Chip Enablement#

Added in 2.1.1#

None.

Added in 2.1.0#

  • EFR32xG2x

  • SiWG917

Key Features#

New Features | Enhancements | Removed Features | Deprecated Features

Note: See Feature Matrix for a list of any appliable APIs, examples, software variants, modes, hardware, and host interfaces applicable for each feature.

New Features#

Added in 2.1.1#

Image Classifier (Rock-Paper-Scissors) application and tutorial for xG24 and xG26 devices, see Image Classification

Added in 2.1.0#

Enhancements#

Added in 2.1.1#

Fix errors when creating projects using the "Copy Contents" feature in Simplicity Studio.

Added in 2.1.0#

Only new features have been added in this release. No enhancements were made to existing features.

Removed Features#

None.

Deprecated Features#

None.

API Changes#

New APIs | Modified APIs | Removed APIs | Deprecated APIs

New APIs#

Added in 2.1.1#

None.

Added in 2.1.0#

New API Signature

Deprecated API replaced by this (if any)

sl_status_t sl_ml_<model_name>_model_init()

None

sl_status_t sl_ml_<model_name>_model_run()

None

static TfliteMicroModel <model_name>_model

None

static sl_status_t <model_name>_model_status

None

uint8_t* <model_name>_model_flatbuffer

None

const int <model_name>_model_flatbuffer_length

None

Modified APIs#

None.

Removed APIs#

None.

Deprecated APIs#

None.

Bug Fixes#

Fixed in 2.1.1#

ID Issue Description GitHub / Salesforce Reference (if any) Affected Software Variants, Hardware, Modes, Host Interfaces
1479968 Fix errors when creating projects using the "Copy Contents" feature in Simplicity Studio. None
  • Standard
  • EFR32xG2x, SiWG917
  • SoC

Fixed in 2.1.0#

ID Issue Description GitHub / Salesforce Reference (if any) Affected Software Variants, Hardware, Modes, Host Interfaces
1452807 Memory Leak in sl_ml_audio_feature_generation_init() due to Missing Resource Cleanup. None
  • Standard
  • EFR32xG2x
  • SoC

Chip Enablement#

Added in 2.1.1#

None.

Added in 2.1.0#

Chip Family OPNs / Boards / OPN Combinations Supported Software Variants (if applicable) Supported Modes Supported Host Interfaces
Chip
  • OPN: EFR32xG2x, SiWG917x
  • Boards: BRD2601b, BRD2608a, BRD2605a, BRD2705a
  • External Hosts: N/A
 Standard
  • SoC

Application Example Changes#

New Examples | Modified Examples | Removed Examples | Deprecated Examples

New Examples#

Added in 2.1.1#

Example Name Description Supported Software Variants (if applicable) Supported Modes Supported OPNs / Boards / OPN Combinations Supported Host Interfaces

Image Classifier(Rock-Paper-Scissors)

See readme.md

 This application uses TensorFlow Lite for Microcontrollers to run image classification machine learning models to classify hand gestures from image data captured from external camera. The detection is visualized using the LED's on the board and the classification results are written to the VCOM serial port. Standard
  • SoC
  • OPN: EFR32xG2x
  • Boards: BRD2601b, BRD2608a
  • External Hosts: N/A

Added in 2.1.0#

Example Name Description Supported Software Variants (if applicable) Supported Modes Supported OPNs / Boards / OPN Combinations Supported Host Interfaces

Audio Classifier for SiWG917

See readme.md

 This application uses TensorFlow Lite for Microcontrollers to run audio classification machine learning models to classify words from audio data recorded from a microphone. The detection is visualized using the LED's on the board and the classification results are written to the VCOM serialport. Standard
  • SoC
  • OPN: SiWG917x
  • Boards: BRD2605a
  • External Hosts: N/A

Voice Control Light for SiWG917

See readme.md

 This application uses TensorFlow Lite for Microcontrollers to detect the spoken words "on" and "off" from audio data recorded on the microphone. The detected keywords are used to control an LED on the board. Standard
  • SoC
  • OPN: SiWG917x
  • Boards: BRD2605a
  • External Hosts: N/A

Modified Examples#

None.

Removed Examples#

None.

Deprecated Examples#

None.

Known Issues and Limitations#

ID Issue or Limitation Description GitHub / Salesforce Reference (if any) Workaround (if any) Affected Software Variants, Hardware, Modes, Host Interfaces
1463269 Blink app behaves differently when running on Series 2, compared to SiWG917. The LED has a baseline brightness on SiWG917 while blinking but it turns off completely on Series 2. This is due to the different LED driver implementations on the two chip families. None A workaround has not been implemented yet. The issue is under investigation to transition from a software PWM to a hardware PWM implementation for the LED driver on SiWG917.
  • SiWG917M111MGTBA
  • BRD2605a
  • SoC
1463268 Audio feature generation component shows config error for SiWG917. None This issue is cosmetic and a fix is under investigation for a future release. This issue does not affect Series 2 projects.
  • SiWG917M111MGTBA
  • BRD2605a
  • SoC
1464105 API calls for model invocation and execution are different on Series 2 and SiWG917 chip families. None The Series 2 uses sl_ml_model_init(), and sl_tflite_micro_get_interpreter()->Invoke() for model invocation and execution, respectively, whereas SiWG917 uses sl_ml_<model_name>_model_init(), sl_ml_<model_name>_model_run().
  • SiWG917M111MGTBA
  • BRD2605a
  • SoC

Impact of Release Changes#

Impact Statements | Migration Guide

Impact Statements#

Added in 2.1.1#

None.

Added in 2.1.0#

Change Impact Affected Software Variants if applicable Affected Modes Affected OPNs / Boards / OPN Combinations Affected Host Interfaces

Source code moved into AI/ML Extension
  • Components moved from "Machine Learning" to "Silicon Labs AI/ML v2.1.0 > Machine Learning"
 Standard
  • SoC
  • OPN: EFR32xG2x, SiWG917x
  • Boards: BRD2601b, BRD2608a, BRD2605a, BRD2705a
  • External Hosts: N/A

Migration Guide#

Using This Release#

What's in the Release? | Compatible Software | Installation and Use | Help and Feedback

What's in the Release?#

Added in 2.1.1#

This patch release includes a new Image Classifier (Rock-Paper-Scissors) application and tutorial for xG24 and xG26 devices, and fixes errors when creating projects using the "Copy Contents" feature in Simplicity Studio.

Added in 2.1.0#

This is the first version where AI/ML software is provided as an extension to the Simplicity SDK. It supports the Series 2 and SiWG917 family of Silicon Labs devices using the Tensorflow Lite for Microcontrollers (TFLM) framework. The highlight of this release are the performance improvements to the SDK, bringing support for SiWG917 chip family, which has a vastly different SoC architecture compared to the Series 2 devices. SiWG917 is a high-performance, low-power Wi-Fi chip that is ideal for AI/ML applications. Hence, your AI/ML applications can now leverage Wi-Fi connectivity for cloud-based AI/ML applications and services.

Compatible Software#

Added in 2.1.1#

Software Compatible Version or Variant
Software Development Kit (SDK)

Added in 2.1.0#

Software Compatible Version or Variant
Software Development Kit (SDK)

Installation and Use#

Added in 2.1.1#

To upgrade your existing software with this release, update Simplicity Studio to the latest, SiSDK to v2025.6.1, WiSeConnect SDK to v3.5.1, and AI/ML Extension to v2.1.1 from Studio installation manager, or download the SDKs from the respective links listed in Compatible Software section above. To update AI/ML Extension, please refer to AI/ML Extension Setup guide.

Added in 2.1.0#

To upgrade your existing software with this release, update Simplicity Studio to the latest, SiSDK to v2025.6.0, WiSeConnect SDK to v3.5.0, and AI/ML Extension to v2.1.0 from Studio installation manager, or download the SDKs from the respective links listed in Compatible Software section above. To update AI/ML Extension, please refer to AI/ML Extension Setup guide.

To run your first demo, see our Getting Started

To kick start your development, see our Developer's Guide

For information about Secure Vault Integration, see Secure Vault.

To review Security and Software Advisory notifications and manage your notification preferences:

  1. Go to https://community.silabs.com/.

  2. Log in with your account credentials.

  3. Click your profile icon in the upper-right corner of the page.

  4. Select Notifications from the dropdown menu.

  5. In the Notifications section, go to the My Product Notifications tab to review historical Security and Software Advisory notifications

  6. To manage your preferences, use the Manage Notifications tab to customize which product updates and advisories you receive.

To learn more about the software in this release, dive into our online documentation

Help and Feedback#

Feature Matrix#

Supported Features | Unsupported Features

Supported Features#

Added in 2.1.1#

None.

Added in 2.1.0#

Feature Name Description Quality Related API Names Supported Software Variants, Hardware, Modes, Host Interfaces Related Example Names
Model specific APIs Model specific APIs for invoking and executing AI/ML models on the device. Experimental
  • Standard
  • SiWG917
  • SoC
Audio Applications Audio applications enabled on SiWG917 through software optimizations Experimental
  • Standard
  • SiWG917
  • SoC

Unsupported Features#

Added in 2.1.1#

None.

Added in 2.1.0#

  • SiWG917 does not use the built-in TensorFlow component directly; instead, support is provided through automatic code generation handled by configurators.

  • Series 2 devices do not support new software optimizations but, due to their architecture, they are still as efficient as SiWG917, if not more.

SDK Release and Maintenance Policy#

See our SDK Release and Maintenance Policy.