35 results
MARCH 11, 2025 / Cloud
An enhancement to Google Cloud Dataflow templates for MongoDB Atlas enables direct integration of JSON data into BigQuery, eliminating complex data transformations, reducing operational costs, and enhancing query performance for users.
MARCH 10, 2025 / Cloud
Google Cloud Next 2025, happening April 9-11 in Las Vegas, will feature expanded developer content, interactive experiences, and opportunities to connect with peers and Google experts.
JAN. 7, 2025 / Matter
The public beta launch of Home APIs for Android allows developers to create better smart home experiences. This launch emphasizes investments in Matter to improve device connectivity and interoperability, and increase smart home accessibility.
JAN. 7, 2025 / Matter
The Google Home APIs are now in public developer beta for Android, allowing developers to build innovative smart home experiences for over 600M devices using Google's hubs, Matter infrastructure, and automation engine.
DEC. 18, 2024 / Gemini
Learn how to build Go applications using Project IDX, an AI-assisted workspace for full-stack app development.
DEC. 17, 2024 / Cloud
Apigee API hub is a centralized repository for your entire API ecosystem, providing a single source of truth.
DEC. 12, 2024 / Cloud
Google Cloud Next 2025, happening April 9-11 in Las Vegas, will feature expanded developer content, interactive experiences, and opportunities to connect with peers and Google experts.
NOV. 19, 2024 / Firebase
Explore Firebase's new AI-powered app development tools and resources, including demos, documentation, and best practices at Firebase Demo Day 2024.
NOV. 14, 2024 / Gemini
The integration of Gemini's 1.5 models with Sublayer's Ruby-based AI agent framework enables developer teams to automate their documentation process, streamline workflows, and build AI-driven applications.
NOV. 13, 2024 / Gemma
vLLM's continuous batching and Dataflow's model manager optimizes LLM serving and simplifies the deployment process, delivering a powerful combination for developers to build high-performance LLM inference pipelines more efficiently.
