P-EAGLE: Faster LLM inference with Parallel Speculative Decoding in vLLM

TutoSartup excerpt from this article:
EAGLE is the state-of-the-art method for speculative decoding in large language model (LLM) inference, but its autoregressive drafting creates a hidden bottleneck: the more tokens that you speculate, the more sequential forward passes the drafter needs... P-EAGLE removes this ceiling by generating all K draft tokens in a single forward pass, delivering up to 1...69x speedup over vanilla EAGLE-3 on...

Twenty years of Amazon S3 and building what’s next

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Twenty years ago today, on March 14, 2006, Amazon Simple Storage Service (Amazon S3) quietly launched with a modest one-paragraph announcement on the What’s New page:Amazon S3 is storage for the Internet... It gives any developer access to the same highly scalable, reliable, fast, inexpensive data storage infrastructure that Amazon uses to run its own global network of web sites... When S3 ...

US 10‑Year Treasury Yield Near ‘Fair Value’ at Outset of Iran War

TutoSartup excerpt from this article:
The 10-year Treasury yield was close to its “fair value” estimate in February, based on the average of three models...The 10-year yield in March has jumped more than 30 basis points since last month’s close, rising to 4...Using the 10-year yield as a proxy, the market appears to be repricing inflation risk, albeit moderately so far... The 10-year rate’s rise so far this month le...

Improve operational visibility for inference workloads on Amazon Bedrock with new CloudWatch metrics for TTFT and Estimated Quota Consumption

TutoSartup excerpt from this article:
While these metrics provide a strong operational foundation, they leave two important gaps: they don’t capture how quickly a streaming response begins (time-to-first-token), and they don’t reflect the effective quota consumed by a request after accounting for token burndown multipliers... Today, we’re announcing two new Amazon CloudWatch metrics for Amazon Bedrock, TimeToFirstToken and Est...

Introducing account regional namespaces for Amazon S3 general purpose buckets

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Today, we’re announcing a new feature of Amazon Simple Storage Service (Amazon S3) you can use to create general purpose buckets in your own account regional namespace simplifying bucket creation and management as your data storage needs grow in size and scope... You can create general purpose bucket names across multiple AWS Regions with assurance that your desired bucket names will always be a...

Secure AI agents with Policy in Amazon Bedrock AgentCore

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Deploying AI agents safely in regulated industries is challenging... Without proper boundaries, agents that access sensitive data or execute transactions can pose significant security risks... Unlike traditional software, an AI agent chooses actions to achieve a goal by invoking tools, accessing data, and adapting its reasoning using data from its environment and users... This autonomy is precisel...

How to manage the lifecycle of Amazon Machine Images using AMI Lineage for AWS

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As organizations scale their cloud infrastructure, maintaining proper lifecycle management of Amazon Machine Images (AMIs) is a critical component of their security and risk management goals... AMIs provide the essential information required to launch Amazon Elastic Compute Cloud (Amazon EC2) instances, however; they present security and compliance challenges if not tracked and managed thro...