Serial Number
98289655
Owner
AMAZON TECHNOLOGIES, INC.Attorney
Susan KayserFirst Use Date
Nov 29, 2023
Filing Date
Nov 29, 2023
SAGEMAKER HYPERPOD Trademark
Serial Number: 98289655 • Registration: 7845630
Trademark Classes
Owner Contact Info
Legal Representation
Correspondence Address
Susan Kayser Baker & Hostetler, LLP
1050 Connecticut Ave, N.W., Suite 1100
Washington Square
Washington, DC 20036-5403
United States
Trademark Details
Filing Date
November 29, 2023
Registration Date
June 24, 2025
First Use Anywhere
November 29, 2023
First Use in Commerce
November 29, 2023
Published for Opposition
July 9, 2024
Goods & Services
Downloadable computer software for machine learning and deep learning for training models using managed, persistent clusters; Downloadable computer software for machine learning and deep learning for experimentation, training, developing, building, testing, installing frameworks, and deploying software and applications; Downloadable computer software for machine learning and deep learning for training models with interactive debugging, start and stopping jobs with low latency, and retaining the same set of instance across training runs; Downloadable computer software for machine learning and deep learning for reducing foundation model training time; Downloadable computer software for machine learning and deep learning for streamlined distributed training for large training clusters; Downloadable computer software for machine learning and deep learning for a resilient training environment; Downloadable computer software for machine learning and deep learning for optimized utilization of cluster compute, memory, and network resources; Downloadable computer software for developing, deploying, updating and monitoring the performance of machine learning, deep learning and artificial intelligence applications
Software as a service (SAAS) services featuring software for machine learning and deep learning for training models using managed, persistent clusters; Software as a service (SAAS) services featuring software for machine learning and deep learning for experimentation, training, developing, building, testing, installing frameworks, and deploying software and applications; Software as a service (SAAS) services featuring software for machine learning and deep learning for reducing foundation model training time; Software as a service (SAAS) services featuring software for machine learning and deep learning for streamlined distributed training for large training clusters; Software as a service (SAAS) services featuring software for machine learning and deep learning for a resilient training environment; Software as a service (SAAS) services featuring software for machine learning and deep learning for optimized utilization of cluster compute, memory, and network resources; Providing online non downloadable software for machine learning and deep learning for training models with interactive debugging, start and stopping jobs with low latency, and retaining the same set of instance across training runs; Providing online non downloadable software using data science, namely, artificial intelligence (AI), machine learning, deep learning, statistical learning and data mining, for experimentation, training, developing, building, testing, installing frameworks, and deploying software and applications; Software as a service (SaaS) services featuring software for developing, deploying, updating and monitoring the performance of machine learning, deep learning and artificial intelligence applications