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  <title>Optimizing Python for Speed and Compatibility</title>
  <description>In the penultimate episode of season one, host Peter Wang and Carl Meyer, Software Engineer at Instagram (owned by Meta), discuss considerations around making Python faster while maximizing compatibility and performance. &amp;amp;nbsp; Several years ago, Carl and his team started working on a project called Cinder in an effort to improve CPU efficiency across Meta’s servers by “[optimizing] things at the level of Python runtime.” While initially meant to serve as a stop gap, Cinder yielded impressive wins that transformed it into a premier and ongoing project at Instagram. &amp;amp;nbsp; In addition to Cinder, Peter and Carl discuss: - Carl’s experiences with various programming languages like TI-Basic, Perl, and PHP - Challenges around innovating on an established language with 30+ years of history - The potential evolution of Python use cases and best practices - And more! &amp;amp;nbsp; Peter Wang -&amp;amp;nbsp;https://www.linkedin.com/in/pzwang/ Carl Meyer - https://www.linkedin.com/in/carljm/ Instagram - https://www.linkedin.com/company/instagram/ Cinder - https://github.com/facebookincubator/cinder &amp;amp;nbsp; If you enjoyed today’s show, please leave a 5-star review. For more information, visit https://www.anaconda.com/podcast. &amp;amp;nbsp; #Computing #AI #Data #DataScience #Analytics </description>
  <author_name>Numerically Speaking: The Anaconda Podcast</author_name>
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