Carahsoft, in conjunction with its vendor partners, sponsors hundreds of events each year, ranging from webcasts and tradeshows to executive roundtables and technology forums.
The U.S. Navy uses machine learning (ML) models for underwater target threat detection by unmanned underwater vehicles (UUV). However, without a way to monitor and improve ML model performance at scale, models were slow to adapt to changing underwater conditions or enemy tactics - unable to “learn” based on recent field activity. The Navy partnered with the Defense Innovation Unit (DIU) as part of Project Automatic Target Recognition using Machine Learning Operations (MLOps) for Maritime Operations (AMMO).
The AMMO MLOps pipeline decreased the time needed for ML model updates from six months to a few days, enabling the Navy to quickly retrain and deploy automatic target recognition (ATR) models at the speed of operational relevance. Domino Data Lab’s modular, open, and extensible AI platform serves as the factory for integrating commercial technologies from Weights and Biases and Fiddler.ai - providing the governance and flexibility for distributed teams to deploy models faster with built-in observability and reduced time-to-impact.
Watch a recording of this webinar to learn how the US Navy:
Fill out the form below to view this archived event.
With their powers combined, Confluence and Jira Service Management beautifully integrate to save your team time and improve your customer experience by surfacing the information your customers or employees need to resolve their issue, fast.
Fill out the form below to view this Resource.