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Together with Anthropic, AWS is building an EC2 UltraCluster of Trn2 UltraServers, named Project Rainier, which will scale out distributed model training across hundreds of thousands of Trainium2 ...
Incremental training to help with agility The incremental training ability added to Clean Rooms will help enterprises build upon existing model artifacts, AWS said.
AWS unveiled Trainium3, its next-generation AI training chip. Trainium3 will be the first AWS chip made with a 3-nanometer process node, setting a new standard for performance, power efficiency, and ...
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Gadget on MSNAWS Summit: Bedrock powers next wave of GenAI apps
At the Johannesburg event, the tech giant showcased the evolution of services from simple model access to customisable, ...
Barclays said the acceleration “assumes the bulk of Anthropic training continues on AWS,” noting that the AI start-up ...
AWS Trainium chips will be the preferred processors for training Mosaic AI models on the Databricks platform, the company announced today. The deal represents a blow to Nvidia’s continued AI dominance ...
AWS unveils Blackwell-powered instances for AI training and inference To power customer training and inference workloads, AWS unveiled two new system configurations: the P6-B200 and P6e-GB200 ...
AWS and Rice University have introduced Gemini, a new distributed training system to redefine failure recovery in large-scale deep learning models. According to the research paper, Gemini adopts a ...
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Verdict on MSNAnthropic secures $13B Series F funding at $183bn valuation
The funding will enhance Anthropic's enterprise initiatives, advance safety research, and facilitate international expansion ...
Federal agencies are scaling AI for real-world impact from border security to data governance. Learn how AWS and Thundercat are powering the transformation.
“ Using AWS, LG AI Research can develop and use EXAONEPath at an unprecedented scale, reducing data processing and model training times and improving accuracy.
AWS added Intelligent Prompt Routing and Prompt Caching to Bedrock in hopes of getting model usage prices down.
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