Executive Summary: Clusterone is a deep learning platform that makes it simple and fast to run deep learning workloads of any scale and complexity on any infrastructure. Clusterone, funded by investors such as the
Allen Institute for Artificial Intelligence and Madrona Ventures, was created by machine learning scientists and engineers from Stanford, Google[x], and Intel to solve specific problems that data scientists and AI project managers
encounter when managing large GPU cluster configurations.
Clusterone helps organizations maximize the value of their data scientists by shielding them from the time sink of infrastructure management, and reduces project costs by maximizing the efficiency of resource allocation and
management. These efficiency gains result in an increased capacity to perform deep learning experiments and translate to faster research cycles and outputs.
In summary, Clusterone provides deep learning orchestration and resources to improve modeling, training, and analysis. Organizations can deploy Clusterone onto an on-premise or cloud-based infrastructure, create hybrid scenarios,
or use Clusterone as a hosted service.
Clusterone’s expertise in building a deep learning platform and delivering deep learning services tailored to the health and biotechnology industries is derived from a range of sciences, including astrophysics, nuclear
engineering, and bio-physics. In particular, with respect to bio-chemistry, Clusterone recently deployed the popular DeepChem libra- ry on Clusterone as an integrated SaaS, which is now used on mission-critical projects for customers
The Clusterone Applied AI team offers professional services in solutions design and research. They provide customers with the expertise needed to successfully execute complex machine learning projects and make the most
of the Clusterone deep learning platform.