Where I express personal thoughts in words
Bob Van Luijt is the CEO and co-founder of Weaviate, the business created around the open-source vector database Weaviate. Besides Weaviate, Bob frequently speaks on open-source, digital technology, software business, and business philosophy. He has spoken at 100s of events on the topics mentioned above all over the world, including a TEDx talk.
Douwe Maan is the founder and CEO of Meltano, an open-source DataOps platform. Before joining Meltano, he was hired as the tenth employee at GitLab, later becoming an Engineering Manager. While at GitLab, he spent six months traveling the world, visiting colleagues in 14 different countries. In 2019, he joined the internal Meltano project at GitLab and quickly became its General Manager. In early 2021, Douwe led Meltano in spinning out of GitLab to become an independent startup, raising seed funding from investors led by Alphabet's GV.
Mohamed Elgendy is a seasoned AI expert, who has previously built and managed AI organizations at Amazon, Rakuten, Twilio, and Synapse. In particular, he founded and managed Amazon's computer vision think tank. He is the author of the "Deep Learning for Vision Systems" book published by Manning in November 2020. Mohamed regularly speaks at many AI conferences like Amazon's DevCon, O'Reilly's AI, and Google's I/O.
Aparna Dhinakaran is the Chief Product Officer at Arize AI, a startup focused on ML Observability. She was previously an ML engineer at Uber, Apple, and TubeMogul (acquired by Adobe). During her time at Uber, she built several core ML Infrastructure platforms, including Michelangelo. She has a bachelor’s from Berkeley's Electrical Engineering and Computer Science program, where she published research with Berkeley's AI Research group. She is on a leave of absence from the Computer Vision Ph.D. program at Cornell University.
Willem Pienaar is the Engineering Lead at Tecton and the creator of Feast, a feature store for machine learning. Feast is an open-source project that Willem developed while leading the machine learning platform team at Gojek, the Indonesian ride-hailing startup. In a previous life, Willem founded and sold a networking startup and worked on industrial data systems.
Marcello La Rocca is a research scientist and a full-stack engineer. He works as a consultant, creating large-scale web applications and machine learning infrastructure. He has gained invaluable experience at Twitter, Microsoft, and Apple - working on applied research in academia and industry. His work and interests focus on graphs, optimization algorithms, genetic algorithms, machine learning, and quantum computing.
Dave Bechberger is known for his expertise in distributed data architecture and being a Graph Database SME. He is known for his pragmatic approach to data architectures and for implementing large-scale distributed data architectures for big data analysis and data science workflows using various SQL and NoSQL data technologies. He is the author of "Graph Database in Action" by Manning publications and has spoken both nationally and internationally at conferences on subjects related to distributed data and graph databases.
Dave spent 20+ years developing, managing, and consulting on software projects and is currently a member of the Amazon Neptune service team. He works with both customers and engineering teams to simplify and speed the adoption of graph technologies.
Carl Osipov is the Chief Technology Officer of CounterFactual.AI - a boutique machine learning consultancy he co-founded with his friend from IBM. Previously, he held engineering and technical leadership roles at Google and IBM, on programs and projects across both United States and Europe, in the areas of machine learning, computational natural language processing, cloud computing, and big data analytics.
Carl is also an inventor with six patents at USPTO and is an author of "Serverless Machine Learning in Action," a book from Manning Publishers, currently available as an ebook subscription and expected in print in early 2021.
Two weeks ago, I attended the inaugural MLOps: Production and Engineering World, which is a two-day virtual conference organized by the Toronto Machine Learning Society that explores the best practices, methodologies, and principles of effective MLOps. In this post, I would like to share content from the talks that I attended during this conference.
