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Cloud costs can significantly impact your business operations. Gaining real-time visibility into infrastructure expenses, usage patterns, and cost drivers is essential. This insight enables agile decision-making, optimized scalability, and maximizes the value derived from cloud investments, providing cost-effective and efficient cloud utilization for your organization’s future growth. What makes cost visibility even more important for …

Read more “Governing ML lifecycle at scale: Best practices to set up cost and usage visibility of ML workloads in multi-account environments”

Crafting the perfect prompt for generative AI models can be an art in itself. The difference between a useful and a generic AI response can sometimes be a well-crafted prompt. But, getting there often requires time-consuming tweaking, iteration, and a learning curve. That’s why we’re thrilled to announce new updates to the AI-powered prompt writing …

Read more “Use AI to build AI: Save time on prompt design with AI-powered prompt writing”

How Defense Efforts Align with Human Rights Palantir’s Founding Connection to Human Rights Palantir has its origins and identity in the defense of the values and traditions of liberal democratic societies. Our company was founded in response to the 9/11 attacks with the mission of supporting bedrock defense and intelligence institutions without compromising the protection of the …

Read more “Safeguarding Freedom”

You can now register machine learning (ML) models in Amazon SageMaker Model Registry with Amazon SageMaker Model Cards, making it straightforward to manage governance information for specific model versions directly in SageMaker Model Registry in just a few clicks. Model cards are an essential component for registered ML models, providing a standardized way to document …

Read more “Improve governance of models with Amazon SageMaker unified Model Cards and Model Registry”

As AI models increase in sophistication, there’s increasingly large model data needed to serve them. Loading the models and weights along with necessary frameworks to serve them for inference can add seconds or even minutes of scaling delay, impacting both costs and the end-user’s experience.  For example, inference servers such as Triton, Text Generation Inference …

Read more “Data loading best practices for AI/ML inference on GKE”