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AnthropicAnnouncement
Expanding access to safer AI with Amazon
Summary
Anthropic announces that Amazon will invest up to $4 billion and become its primary cloud provider for mission-critical workloads. The collaboration combines Anthropic’s frontier safety research and models with AWS infrastructure, including Trainium and Inferentia chips, while expanding Amazon Bedrock support for secure model customization and fine-tuning. Organizations will be able to use Claude 2 through Bedrock, including its 100,000-token context window, with examples spanning legal search, investment analysis, and travel recommendations; Lonely Planet reduced itinerary-generation costs by almost 80 percent after deployment. Amazon will take a minority stake, while Anthropic’s governance remains unchanged under the Long Term Benefit Trust and its Responsible Scaling Policy, including pre-deployment testing of new models.
Context
Anthropic says the collaboration responds to significant AWS customer demand for Claude and provides the extensive compute power and research resources required to train state-of-the-art models while advancing AI safety and research.
Approach / What changed
Amazon will provide AWS as Anthropic’s primary cloud provider for mission-critical workloads, including access to Trainium and Inferentia chips. The companies will collaborate on future chip technology and expand Amazon Bedrock with secure Claude customization and fine-tuning, while Anthropic continues pre-deployment testing under its Responsible Scaling Policy.
Takeaways
Amazon’s investment can reach $4 billion, and AWS will supply Trainium and Inferentia compute for model training and deployment.
Amazon Bedrock will support secure model customization and fine-tuning, allowing enterprises to use expert knowledge while limiting potential harmful outcomes.
Claude 2 has a 100,000-token context window; Lonely Planet reported almost 80 percent lower itinerary-generation costs after deployment.
Source and freshness
- Source
- anthropic.com
- Published
- Added to Yomu
Summaries are generated from the original by a language model. Check the original before relying on it.
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