650: SparseGPT: Remove 100 Billion Parameters but Retain 100% Accuracy

<p>SparseGPT is a noteworthy one-shot pruning technique that can halve the size of large language models like GPT-3 without adversely affecting accuracy. In this episode, Jon Krohn provides an overview of this development and explains its commercial and environmental implications.</p><p>Additional materials: <a href='https://www.superdatascience.com/650'>www.superdatascience.com/650</a></p><p><br/>Interested in sponsoring a SuperDataScience Podcast episode? Visit <a href='http://jonkrohn.com/podcast'>JonKrohn.com/podcast</a> for sponsorship information.</p>