2633 results
DEC. 6, 2024 / Gemini
The range of family of Gemini models has expanded in the past year in response to developer needs, introducing faster and more cost-effective models, and enhancing tools in Google AI Studio.
DEC. 5, 2024 / Gemma
PaliGemma 2, the next evolution in tunable vision-language models, comes with new features such as scalable performance, long captioning, and expanded capabilities. Get started with pre-trained models, documentation, and tutorials.
NOV. 25, 2024 / Cloud
The Google Developer Program premium membership offers benefits such as Google Cloud credits, certification vouchers, and access to Cloud Skills Boost.
NOV. 25, 2024 / Gemini
Explore real-world applications of Gemini's multimodal AI capabilities, from detailed image descriptions, information extraction, object detection, video summarization, and more.
NOV. 22, 2024 / AI
All are invited to Women in AI Summit 2024 to explore the latest in generative AI with sessions for all expertise levels, focusing on Google AI tools, models, solutions, and insight from women leaders in the AI field.
NOV. 21, 2024 / Mobile
The winners of the Gemini API Developer Competition showcased the potential of the Gemini API in creating impactful solutions, from AI-powered personal assistants to tools for accessibility and creativity.
NOV. 20, 2024 / Gemini
OpusClip utilizes Gemini 1.5 Flash's multimodal capabilities to enhance video understanding and streamline content creation, leading to cost savings and increased engagement.
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.
