Episode 39: Serverless Machine Learning In Action with Carl Osipov

Show Notes
(2:22) Carl talked about his early exposure to programming and his Bachelor’s degree in Computer Science at the University of Rochester in the late 90s.
(5:12) Carl implemented his first fully connected, two-hidden-layer artificial neural network using the C programming language back in 2000 when using neural networks wasn’t nearly as cool as it is today.
(8:00) Carl started his career as a software engineer at IBM, writing software for large-scale distributed systems and voice-dialog management system.
(13:31) The first production machine learning system that Carl worked on is called Conversational Interaction Manager, which is a dialog management system for conversational mixed-initiative natural language applications. He brought up the challenges in DevOps and data quality.
(20:05) The second production machine learning system that you worked on is called Smarter Campus, which is a project that enables staffing recommendations based on social networking, optimization, and text analytics.
(27:16) Carl unpacked the evolution of his career at IBM, working on various leadership roles. In particular, he worked on IBM Bluemix, IBM’s cloud platform-as-a-service, with over 1 million registered users. He emphasized the importance of talking to customers and finding product-market fit.
(33:01) Carl discussed his decision to pursue a Master’s degree in Computer Science at the University of Florida in the mid of his career.
(35:24) Carl explained his research paper, which combines game theory and machine learning called “AmalgaCloud: Social Network Adaptation for Human and Computational Agent Team Formation.” The paper focuses on the relationship between network adaptation for candidate group participants and the performance of problem-solving groups.
(40:50) Carl discussed his patent on learning ontologies for machine learning - which maps ontologies from data warehouses to computer systems.
(47:00) Carl unpacked his 4-part blog series dated in 2016 that discusses server-less computing via tools such as Docker and Apache OpenWhisk.
(52:58) Carl emphasized the importance of learning Docker to be productive as a Machine Learning practitioner.
(55:02) Carl became a program manager at Google Cloud and helped manage the company’s efforts to democratize machine learning via the Advanced Solutions Lab in 2017.
(59:07) Carl recalled his experience as an instructor at various machine learning boot camps.
(01:01:44) Carl went over the growing popularity of semi-structured data, referring to his talk at Google’s 2018 Data Cloud Next event.
(01:06:29) Currently, Carl is the CTO of CounterFactual AI, which works with various clients using tools such as PyTorch and AWS. He brought up an example of a food delivery application.
(01:09:13) Carl went over his experience leading a workshop on Server-less Machine Learning with TensorFlow at the Reinforce AI Conference in Budapest last year.
(01:10:52) Carl is writing a book with Manning called Server-less Machine Learning In Action. He explained that server-less tools help minimize the efforts to do MLOps.
(01:13:47) Carl talked about the rise of PyTorch as a production-ready deep learning framework, as well as his preference for the PyTorch’s language design philosophy.
(01:17:10) Carl shared his opinions on choosing different cloud platforms to host and run the server-less ML pipeline.
(01:19:37) Carl described the data and tech community in Orlando, Florida.
(01:21:53) Closing segment.
His Contact Information
Website
LinkedIn
Twitter
GitHub
Google Scholar
His Recommended Resources
“An Introduction to Natural Computation” by Dana Ballard
IBM’s semiconductor facility FAB
IBM Bluemix
“Pattern Recognition and Machine Learning” by Christopher Bishop
Docker
PyTorch
PyTorch Lightning
Jurgen Schmidhuber (the father of LSTM)
Solomon Hykes (Founder, CTO, and chief architect of Docker)
Dana Ballard (professor of Computer Science at UT-Austin)
Gang of Four Design Patterns (engineering book with object-oriented design theory and practice)
Serverless Machine Learning In Action
Check out the book at this link: https://www.manning.com/books/serverless-machine-learning-in-action?a_aid=khanhnamle1994&a_bid=fa913283
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