Browsing: Accelerating

Enterprise data with tens of millions of rows, row-level and column-level security, and dozens of datasets spanning multiple business domains need AI-generated answers that are trustworthy,…

Last year, X announced a partnership with Visa aimed at creating some sort of personal finance ecosystem within the X app. Last month, it was easy…

Practical benchmarks showing faster inter-token latency when deploying Qwen3 models with vLLM, Kubernetes, and AWS AI Chips. Speculative decoding on AWS Trainium can accelerate token generation…

Quality assurance (QA) automation is critical for modern software delivery. It catches regressions before production, validates user journeys at scale, and enables confident feature releases. But…

Last year, AWS announced an integration between Amazon SageMaker Unified Studio and Amazon S3 general purpose buckets. This integration makes it straightforward for teams to use…

AcknowledgementsThis work is a collaboration across multiple teams at Google. Key contributors to this project include Ruofei Du, Benjamin Hersh, David Li, Xun Qian, Nels Numan,…

Businesses across industries face a common challenge: how to efficiently extract valuable information from vast amounts of unstructured data. Traditional approaches often involve resource-intensive processes and…

This blog post was co-authored with Johannes Maunz, Tobias Bösch Borgards, Aleksander Cisłak, and Bartłomiej Gralewicz from Hexagon. Hexagon is the global leader in measurement technologies…

Marketing teams face major challenges creating campaigns in today’s digital environment. They must navigate through complex data analytics and rapidly changing consumer preferences to produce engaging,…

Foundation models (FMs) and large language models (LLMs) have been rapidly scaling, often doubling in parameter count within months, leading to significant improvements in language understanding…