Samsara (NYSE: IOT) is the pioneer of the Connected Operations Cloud, which helps to digitize the world of physical operations, providing visibility and empowering entire sectors of our economy to become more safe, efficient, and sustainable. Founded in San Francisco in 2015, we now employ more than 2,000 people globally, have 2.3 million IoT devices deployed globally, and collect more than 85 billion minutes of video footage and 4.6 trillion data points annually. Working at Samsara means you'll help define the future of physical operations and be on a team that's shaping an exciting array of product solutions, including video-based safety, vehicle telematics, apps and driver workflows, equipment monitoring, and site visibility. As part of a newly public company, you'll have the autonomy and support to make an impact as we build for the long term. Recent awards we've won include: Every year, we partner with our customers to deliver outcomes like conserving millions of gallons of fuel, saving millions of dollars, and creating positive environmental change.

Guy, a recognized industry thought leader, is the president of SmartSense, IoT solutions for the enterprise. In recent years, artificial intelligence (AI) and prescriptive analytics have been woven into the fabric of business operations across multiple verticals, ranging from retail and grocery to healthcare, pharmaceutical and more. Today, there is high demand for continuous streams of data from the physical world. IoT's accurate sensing capabilities coupled with its capacity to generate vast data resources make it a natural partner to the disciplines of pragmatic AI and prescriptive analytics. The ability of these businesses to integrate these related disciplines has the potential to transform their operations and increase profit margins.

Samsara (NYSE: IOT) is the pioneer of the Connected Operations Cloud, which allows businesses that depend on physical operations to harness IoT (Internet of Things) data to develop actionable business insights and improve their operations. Founded in San Francisco in 2015, we now employ more than 1,800 people globally and have over 1.5 million active devices. Samsara also went public in December 2021 and we're just getting started. Recent awards we've won include: We're driving change in industries that are yet to fully embrace digital transformation. Physical operations make up a massive slice of the global economy but haven't benefited from innovation and actionable information in the way that other sectors have.

Machine learning in context of physical systems merits a re-examination of the learning strategy. In addition to data, one can leverage a vast library of physical prior models (e.g. kinematics, fluid flow, etc) to perform more robust inference. The nascent sub-field of \emph{physics-based learning} (PBL) studies the blending of neural networks with physical priors. While previous PBL algorithms have been applied successfully to specific tasks, it is hard to generalize existing PBL methods to a wide range of physics-based problems. Such generalization would require an architecture that can adapt to variations in the correctness of the physics, or in the quality of training data. No such architecture exists. In this paper, we aim to generalize PBL, by making a first attempt to bring neural architecture search (NAS) to the realm of PBL. We introduce a new method known as physics-based neural architecture search (PhysicsNAS) that is a top-performer across a diverse range of quality in the physical model and the dataset.