In more good news for Amazon, Snowflake signs $6B deal with AWS for AI CPU chips
Snowflake has signed a new, enormous five-year deal with Amazon to secure chips for AI usage. Nvidia is once again being put on notice.
InfoWorld AI·
AWS late on Thursday added a new prompt optimization tool to Amazon Bedrock, its fully managed service for building, deploying, and scaling generative AI applications. The tool, Amazon Bedrock Advanced Prompt Optimization, can be accessed through the Bedrock console, and is designed to automatically refine prompts for better accuracy, consistency, and efficiency across multiple large language models, the hyperscaler wrote in a blog post. The tool works by first evaluating prompts against user-defined datasets and metrics, then rewriting them to optimize them for up to five inference models. It then benchmarks the optimized versions against the originals across the models to help developers identify the best-performing configurations for specific workloads, AWS said. Currently, it is generally available across multiple AWS regions, including US East, US West, Mumbai, Seoul, Singapore, Sydney, Tokyo, Canada (Central), Frankfurt, Ireland, London, Zurich, and São Paulo. The company said th
Read full articleSnowflake has signed a new, enormous five-year deal with Amazon to secure chips for AI usage. Nvidia is once again being put on notice.
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AWS has increased Amazon CloudWatch Logs Insights query result limits from 10,000 to 100,000 rows and added pagination support for its GetQueryResults API to help developers and site reliability engineers (SREs) troubleshoot and debug large-scale distributed applications more efficiently. The update to the monitoring and observability service, according to an AWS blog post, will reduce the need to repeatedly split queries into smaller time windows during incident investigations, debugging, and operational audits across enterprise environments. Analysts see sound operational reasoning behind the move. “The old 10,000-row CloudWatch limit was a real problem for large distributed systems. During outages, SRE teams often had to rerun the same query across multiple small time windows and manually combine results. Automated monitoring and compliance pipelines also needed extra custom logic, making systems more complex and fragile,” said Pareekh Jain, principal analyst at Pareekh Consulting.