669: Streaming, reactive, real-time machine learning

<p>In this episode, Jon Krohn welcomes Adrian Kosowski, Co-Founder and Chief Product Officer at Pathway, who shares insights on streaming data processing and reactive data processing, and how they&apos;re shaping the future of machine learning. Tune in now for an unforgettable episode.</p><p>This episode is brought to you by <a href='https:///posit.co/academy'>Posit</a>, the open-source data science company, and by <a href='https://aws.amazon.com/ec2/instance-types/inf2/'>AWS Cloud Computing Services</a>. Interested in sponsoring a SuperDataScience Podcast episode? Visit <a href='https://JonKrohn.com/podcast'>JonKrohn.com/podcast</a> for sponsorship information.<br/><br/></p><p>In this episode you will learn:<br/>• About Pathway&apos;s reactive data processing framework [04:45]<br/>• Reactive data processing use cases [17:08]<br/>• What is the difference between batch and streaming processing [33:18]<br/>• Transformers in data engineering and data streaming [53:44]<br/>• The benefits of Adrian&apos;s technical background as a CPO [1:04:17]<br/>• Adrian&apos;s responsibilities and favorite tools as a CPO [1:15:25]<br/>• Emerging ML approaches and tools for startups [1:28:49]<br/><br/></p><p>Additional materials: <a href='https://www.superdatascience.com/669'>www.superdatascience.com/669</a></p>