Mike Del Balso is the co-founder of Tecton, where he is focused on building next-generation data infrastructure for Operational ML. Before Tecton, Mike was the PM lead for the Uber Michelangelo ML platform. He was also a product manager at Google where he managed the core ML systems that power GoogleÕs Search Ads business. Previous to that, he worked on Google Maps. He holds a BSc in Electrical and Computer Engineering summa cum laude from the University of Toronto.
Mike Del Balso is the co-founder of Tecton, where he is focused on building next-generation data infrastructure for Operational ML. Before Tecton, Mike was the PM lead for the Uber Michelangelo ML platform. He was also a product manager at Google where he managed the core ML systems that power GoogleÕs Search Ads business. Previous to that, he worked on Google Maps. He holds a BSc in Electrical and Computer Engineering summa cum laude from the University of Toronto.
Martin Casado is a general partner at the venture capital firm Andreessen Horowitz where he focuses on enterprise investing. He was previously the cofounder and chief technology officer at Nicira, which was acquired by VMware for $1.26 billion in 2012. While at VMware, Martin was a fellow, and served as senior vice president and general manager of the Networking and Security Business Unit, which he scaled to a $600 million run-rate business by the time he left VMware in 2016.
Martin started his career at Lawrence Livermore National Laboratory where he worked on large-scale simulations for the Department of Defense before moving over to work with the intelligence community on networking and cybersecurity. These experiences inspired his work at Stanford where he created the software-defined networking (SDN) movement, leading to a new paradigm of network virtualization. While at Stanford he also cofounded Illuminics Systems, an IP analytics company, which was acquired by Quova Inc. in 2006.
For his work, Martin was awarded both the ACM Grace Murray Hopper award and the NEC C&C award, and heÕs an inductee of the Lawrence Livermore LabÕs EntrepreneurÕs Hall of Fame. He holds both a PhD and Masters degree in Computer Science from Stanford University.
Martin serves on the board of ActionIQ, Ambient.ai, Astranis, dbt Labs, Fivetran, Imply, Isovalent, Kong, Material Security, Netlify, Orbit, Pindrop Security, Preset, RapidAPI, Rasa, Tackle, Tecton, and Yubico.
Martin Casado is a general partner at the venture capital firm Andreessen Horowitz where he focuses on enterprise investing. He was previously the cofounder and chief technology officer at Nicira, which was acquired by VMware for $1.26 billion in 2012. While at VMware, Martin was a fellow, and served as senior vice president and general manager of the Networking and Security Business Unit, which he scaled to a $600 million run-rate business by the time he left VMware in 2016.
Martin started his career at Lawrence Livermore National Laboratory where he worked on large-scale simulations for the Department of Defense before moving over to work with the intelligence community on networking and cybersecurity. These experiences inspired his work at Stanford where he created the software-defined networking (SDN) movement, leading to a new paradigm of network virtualization. While at Stanford he also cofounded Illuminics Systems, an IP analytics company, which was acquired by Quova Inc. in 2006.
For his work, Martin was awarded both the ACM Grace Murray Hopper award and the NEC C&C award, and heÕs an inductee of the Lawrence Livermore LabÕs EntrepreneurÕs Hall of Fame. He holds both a PhD and Masters degree in Computer Science from Stanford University.
Martin serves on the board of ActionIQ, Ambient.ai, Astranis, dbt Labs, Fivetran, Imply, Isovalent, Kong, Material Security, Netlify, Orbit, Pindrop Security, Preset, RapidAPI, Rasa, Tackle, Tecton, and Yubico.
Join Mike and Martin in this fireside chat where they'll discuss whether ML should be considered a subset or a superset of programming. ML can be considered a specialized subset of programming, which introduces unique requirements on the process of building and deploying applications. But, ML can also be considered a superset of programming, where the majority of applications being built today can be improved by infusing them with online ML predictions. Mike and Martin will share their thoughts and the implications for ML and Software Engineering teams.