<instructions>Your goal is to analyze the following comment and estimate how highly it will be upvoted by the Hacker News community.</instructions><comment><author>revskill</author><text>You&amp;#x27;re my favorite Python developer. Very intuitive API design.</text><parent_chain><item><author>kerasteam</author><text>Francois from the Keras team here -- happy to answer questions!</text></item></parent_chain></comment><story><title>Keras 3.0</title><url>https://keras.io/keras_3/</url></story>
<instructions>Your goal is to analyze the following comment and estimate how highly it will be upvoted by the Hacker News community.</instructions><comment><author>daturkel</author><text>Hey Francois, congrats to you and the team on the launch! I&amp;#x27;ve generally chosen Pytorch over Tensorflow for my day to day, but now that Keras is framework agnostic I&amp;#x27;m excited to revisit it.&lt;p&gt;One thing I&amp;#x27;m wondering about is if it&amp;#x27;s possible (or necessary?) to use Keras in concert with Pytorch Lightning. In some ways, Lightning evolved to be &amp;quot;Keras for Pytorch,&amp;quot; so what is the path forward in a world where both exist as options for Pytorch users—do they interoperate or are they competitors&amp;#x2F;alternatives to each other?</text><parent_chain><item><author>kerasteam</author><text>Francois from the Keras team here -- happy to answer questions!</text></item></parent_chain></comment><story><title>Keras 3.0</title><url>https://keras.io/keras_3/</url></story>