In this video, I chat with Maximilian Beck, who provides an in-depth explanation of why xLSTM works. xLSTM, or eXtended Long Short-Term Memory, is an advanced variant of the traditional LSTM neural network, designed to improve the handling of long-term dependencies and enhance the performance of sequential data processing tasks.
This session is more of a technical presentation than a podcast, delving deep into the architecture, advantages, and applications of xLSTM. Maximilian also covers the theoretical aspects and practical implementations, making it a must-watch for anyone interested in cutting-edge machine learning techniques.
To make it easier for you to navigate through the content, I’ve included timestamps below:
🔗 Links 🔗
xLSTM Paper - arxiv.org/abs/2405.04517
Maximilian Beck - maxbeck.ai/
Timestamps
00:00 Intro
00:50 xLSTM Presentation by Max
01:10 Intro by Max
04:28 Recap: The Original LSTM
06:20 Limitations of the original LSTM
27:51 xLSTM Q&A with Maximilian Beck
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