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Organizations face the challenge to manage data, multiple artificial intelligence and machine learning (AI/ML) tools, and workflows across different environments, impacting productivity and governance. A unified development environment consolidates data processing, model development, and AI application deployment into a single system. This integration streamlines workflows, enhances collaboration, and accelerates AI solution development from concept to …

Read more “Use Amazon SageMaker Unified Studio to build complex AI workflows using Amazon Bedrock Flows”

Palantir’s Advice for the White House OSTP’s AI R&D Plan Editor’s Note: This blog post highlights Palantir’s response to a Request for Information regarding the redrafting of the National AI R&D Plan. For more information on Palantir’s contributions to AI policy, visit our website here. Improving the Nation’s AI R&D Plan As the AI race evolves, so too …

Read more “From R&D to Real-World Impact”

Amazon SageMaker Inference has been a popular tool for deploying advanced machine learning (ML) and generative AI models at scale. As AI applications become increasingly complex, customers want to deploy multiple models in a coordinated group that collectively process inference requests for an application. In addition, with the evolution of generative AI applications, many use …

Read more “Build and deploy AI inference workflows with new enhancements to the Amazon SageMaker Python SDK”

For over two decades, Google has been a pioneer in AI, conducting groundwork that has shaped the industry. Concurrently, in the Web3 space, Google focuses on empowering the developer community by providing public goods resources like BigQuery blockchain datasets and testnet faucets, as well as the cloud infrastructure builders will need to bring their decentralized …

Read more “How to build Web3 AI agents with Google Cloud”