As teams scale their AI platforms, they must decide which capabilities to build versus buy. Whether balancing standards and flexibility or differentiation and scale, there is a playbook teams should run to make these decisions effectively. Join SigOpt Co-Founder & CEO Scott Clark’s session at TWIMLcon to learn how AI leaders weigh these tradeoffs. During this talk, Scott will draw on experience implementing SigOpt with cross sections of large companies who represent over $500B in market capitalization and nimble algorithmic trading firms with over $300B assets under management. This talk will touch on the end-to-end modeling process, but focus on Experiment Management. In particular, Scott will apply this decision making framework to different parts of Experiment Management in a customer case study format and discuss tradeoffs in methodologies for technical tasks like cluster management, distributed tuning and hyperparameter optimization in greater detail.
