diff --git a/Using-TensorFlow-in-Freight-Frenzy.md b/Using-TensorFlow-in-Freight-Frenzy.md
index 893f166..dc01ac8 100644
--- a/Using-TensorFlow-in-Freight-Frenzy.md
+++ b/Using-TensorFlow-in-Freight-Frenzy.md
@@ -7,9 +7,9 @@ This season's TFOD model can recognize Freight elements._
 
 TensorFlow Object Detection (TFOD) has been integrated into the FTC control system software, to identify and track these game pieces during a match.  The FTC software (SDK version 7.0) contains TFOD Sample Op Modes that can recognize the Freight elements Duck, Box (or Cube), and Cargo (or Ball).
 
-Also, FTC teams can soon use a new tool to train their own TFOD models, to recognize their custom Team Shipping Element (TSE) and/or to improve recognition of Freight elements.  This training could take into account certain conditions of distance, angle, lighting and background.
+Also, FTC teams can use a new tool to train their own TFOD models, to recognize their custom Team Shipping Element (TSE) and/or to improve recognition of Freight elements.  This training could take into account certain conditions of distance, angle, lighting and background.
 
-This new tool, FTC Machine Learning Toolchain, was [announced 10/7/2021](http://firsttechchallenge.blogspot.com/2021/10/new-machine-learning-tool-beta-testing.html) for upcoming beta testing by interested FTC teams.
+This new tool is the **FTC Machine Learning toolchain**, [announced 10/7/2021](http://firsttechchallenge.blogspot.com/2021/10/new-machine-learning-tool-beta-testing.html).  Learn more at these links:  [[forum]](https://community.ftclive.org/) [[manual]](https://storage.googleapis.com/ftc-ml-firstinspires-prod/docs/ftc-ml_manual_2021.pdf)  [[source]](https://github.com/FIRST-Tech-Challenge/fmltc) [[guide]](https://github.com/FIRST-Tech-Challenge/fmltc/blob/main/doc/usage.md)
 
 ### How Might a Team Use TensorFlow in Freight Frenzy?
 
@@ -41,7 +41,7 @@ Click on the following links to learn more about these sample Op Modes.
 
 ### Using a Custom Inference Model
 
-Teams have the option of using a custom inference model with the FIRST Tech Challenge software.  As in the past, some teams may want to use the [TensorFlow Object Detection API](https://github.com/tensorflow/models/tree/master/research/object_detection) to create an enhanced model of the Freight elements or TSE, or to create a custom model to detect other entirely different objects.  Other teams might also want to use an available pre-trained model to build a robot that can detect common everyday objects (for demo or outreach purposes, for example).
+Teams have the option of using a custom inference model with the FIRST Tech Challenge software.  As noted above, the **FTC Machine Learning toolchain** is a streamlined tool for training your own TFOD models.  An alternate would be to use the [TensorFlow Object Detection API](https://github.com/tensorflow/models/tree/master/research/object_detection) to create an enhanced model of the Freight elements or TSE, or to create a custom model to detect other entirely different objects.  Other teams might also want to use an available pre-trained model to build a robot that can detect common everyday objects (for demo or outreach purposes, for example).
 
 The FTC software includes sample op modes (Blocks and Java versions) that demonstrate how to use a **custom inference model**:
 
@@ -50,8 +50,6 @@ The FTC software includes sample op modes (Blocks and Java versions) that demons
 
 These tutorials use examples from a previous FTC season (Skystone), but the process remains generally valid for Freight Frenzy.
 
-As noted above, soon FTC teams will have a streamlined tool for training their own TFOD models.  Watch for announcements regarding the FTC Machine Learning Toolchain, already scheduled for beta testing.
-
 ### Detecting Everyday Objects
 
 You can use a pretrained TensorFlow Lite model to detect **everyday objects**, such as a clock, person, computer mouse, or cell phone.  The following advanced tutorial shows how you can use a free, pretrained model to recognize numerous everyday objects.
@@ -61,4 +59,4 @@ You can use a pretrained TensorFlow Lite model to detect **everyday objects**, s
 _<p align="center">[[https://raw.githubusercontent.com/wiki/FIRST-Tech-Challenge/FtcRobotController/images/Using-a-TensorFlow-Pretrained-Model-to-Detect-Everyday-Objects/tfliteDemo.png]]<br/>TensorFlow can recognize everyday objects._
 <br/>
  
-_<p align="right">updated 10/21/21</p>_
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+_<p align="right">updated 11/19/21</p>_
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