Update README

Author: Wei-Chen Wang

README.md

@@ -27,7 +27,7 @@ TinyEngine is a part of MCUNet, which also consists of TinyNAS. MCUNet is a syst
 - **(2022/11)** We release the source code of Tiny Training Engine, and include the [tutorial of our training demo](tutorial/training) for training a visual wake words (VWW) model on microcontrollers.
 - **(2022/11)** We release the source code of the algorithm and compilation parts of MCUNetV3 in [this repo](https://github.com/mit-han-lab/tiny-training). Please take a look!
 - **(2022/10)** Our new work [On-Device Training Under 256KB Memory](https://arxiv.org/abs/2206.15472) is highlighted on the [MIT homepage](http://web.mit.edu/spotlight/learning-edge/)!
-- **(2022/09)** Our new work [On-Device Training Under 256KB Memory](https://arxiv.org/abs/2206.15472) is accepted to NeurIPS 2022! It enables tiny on-device training for IoT devices \[[demo](https://www.youtube.com/watch?v=XaDCO8YtmBw)\].
+- **(2022/09)** Our new work [On-Device Training Under 256KB Memory](https://arxiv.org/abs/2206.15472) is accepted to NeurIPS 2022! It enables tiny on-device training for IoT devices.
 - **(2022/08)** Our **New Course on TinyML and Efficient Deep Learning** will be released soon in September 2022: [efficientml.ai](https://efficientml.ai/).
 - **(2022/08)** We include the [tutorial of our inference demo](tutorial/inference) for deploying a visual wake words (VWW) model onto microcontrollers.
 - **(2022/08)** We opensource the TinyEngine repo.