engblogs

This blogpost discusses how to simplify Dataflow development by using the Cloud Code plugin for IntelliJ IDE. It explains the features of the plugin such as executing Dataflow pipelines from the IDE, error checking and diagnostics, and step-by-step onboarding for various aspects of the pipeline. It also provides a step-by-step guide on getting started with IntelliJ and creating a Dataflow project.

Learn how to configure PGAdapter as a Cloud Run sidecar, enabling you to use PostgreSQL drivers and frameworks to connect with a Cloud Spanner PostgreSQL database at scale.

This blogpost provides guidelines and instructions for performing a zero-downtime migration from an existing Redis cluster to Memorystore for Redis Cluster using RIOT, a Redis Input/Output Tool.

Scalable quality measurement using a NCQA-Certified Engine on the Lakehouse through collaboration with David Roberts, Kevin P. Buchan Jr, and Yubin Park.

Improving stakeholder experience and enabling next generation integrated risk management at LinkedIn through elevated risk and compliance platform.

Insights from inspiring Duos on how their Hispanic heritage has shaped their worldviews

Explore the latest trends in data-centric AI and LLM applications in the Future of Data-Centric AI 2023 videos.

Learn how Prisma saved 98% on distribution costs by switching to Cloudflare R2 for engine distribution.

Videos from the Future of Data-Centric AI 2023 conference are now available for viewing.

Comparison of the performance and scalability of Lambda's NVIDIA H100 SXM5 instance with the reference NVIDIA A100 SXM4 Tensor Core system using DeepChat's 3-step training example

This blogpost discusses the development of industrial use cases for physical simulation on future error-corrected quantum computers in three specific applications: analyzing the chemistry of cytochrome P450 enzymes, studying alternative materials for lithium-ion batteries, and simulating the dynamics of charged particles in inertial confinement fusion experiments.

Understanding the two-step process of LLM text generation and best practices for LLM inference performance engineering.