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Weights & Biases Receives Recognition from Department of Defense’s Defense Innovation Unit

Weights & Biases, the AI developer platform, today announced it received a memorandum of success from the Department of Defense (DoD) Defense Innovation Unit (DIU) for completing the Automated Mac...

Business Wire

Success memo from Department of Defense underscores Weights & Biases’ ability to accelerate AI delivery

SAN FRANCISCO: Weights & Biases, the AI developer platform, today announced it received a memorandum of success from the Department of Defense (DoD) Defense Innovation Unit (DIU) for completing the Automated Machine Learning for Mine Countermeasures Operations (AMMO) MLOps prototype. This recognition highlights Weights & Biases’ ability to deliver next-generation technologies to the public sector and its commitment to defense and intelligence work across the U.S. government.

“There is a need for an enterprise-grade MLOps platform in the federal government that will meet the requirements within the DoD,” said Chris Van Pelt, Co-Founder of Weights & Biases. “We’ve long been the partner of choice for the commercial sector, and this success memo validates that Weights & Biases is the right partner for government organizations looking to usher in the next generation of innovation. We’re proud to achieve this recognition for our ability to accelerate the delivery of AI.”

In the spring of 2022, the DIU, in collaboration with the Navy, sought solution briefs addressing the need for MLOps platforms in order to connect networks across joint forces. Weights & Biases was selected and developed a prototype MLOps pipeline for mine countermeasures model development and deployment.

The prototype was evaluated on several factors, including its interoperability with other Navy and Marine Corps. systems, and successfully met key requirements. Weights & Biases completed the initial deployment of their software into the government-provisioned AWS environment and all three phases of government acceptance testing, including functionality confirmation, security posture, and deployment automation.

“Working with multiple international partners, we demonstrated the ability to deploy and update our automatic target recognition models at the speed of operational relevance while simultaneously remaining confident in their performance. This embodiment of human-machine teaming gives our Sailors a powerful tool in their arsenal and increases confidence in their systems. I'm proud our warfare community could be the pathfinder and exemplar for machine learning ops, tooling, and processes that will improve many other Navy and joint service warfighting capabilities in the age of artificial intelligence,” said Commodore Shaun Lieb, Commander, Task Force (CTF) 75.

The Weights & Biases AI developer platform helps teams build, manage, and deploy models faster, and is used across the entire ML workflow to boost productivity, serve as the system of record for ML teams, and deliver productionzed ML at scale. As part of the engagement with the DIU, Weights & Biases delivered MLOps software that provided: data exploration and processing; data version control; and model management, version tracking, and storage.

“By helping organizations gain auditable end-to-end machine learning workflows for reproducibility and governance, Weights & Biases AI developer platform helps meet the unique needs of the federal government,” said Mark Kroto, Head of Federal Sales, Weights & Biases. “We’re committed to bolstering the government’s AI readiness, allowing for transparency, auditability, and fairness.”

To learn more about Weights & Biases and its work in the public sector, visit wandb.ai/site/solutions/public-sector.

About Weights & Biases

Weights & Biases is the leading AI developer platform supporting end-to-end MLOps and LLMOps workflows. Used by over 30 foundation model builders and 1,000 companies to productionize machine learning at scale including teams at OpenAI, Toyota, and Microsoft, Weights & Biases is part of the new standard of best practices for machine learning.

Fonte: Business Wire

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