40 results
JULY 11, 2024 / Gemma
Google has developed a number of technologies that you can use to start experimenting with and exploring the potential of generative AI to process data that needs to stay private.
JULY 22, 2025 / Gemini
Gemini 2.5 Flash-Lite, previously in preview, is now stable and generally available. This cost-efficient model is ~1.5x faster than 2.0 Flash-Lite and 2.0 Flash, offers high quality, and includes 2.5 family features like a 1 million-token context window and multimodality.
MAY 11, 2023
At Google I/O, we showed how PaLM 2, our next generation model, is being used to improve products ac...
JULY 10, 2025 / Gemini
GenAI Processors is a new open-source Python library from Google DeepMind designed to simplify the development of AI applications, especially those handling multimodal input and requiring real-time responsiveness, by providing a consistent "Processor" interface for all steps from input handling to model calls and output processing, for seamless chaining and concurrent execution.
MAY 16, 2023
A customizable AI-powered character template that demonstrates the power of LLMs to create interacti...
JUNE 27, 2024 / Gemini
Developers will now be able to give Gemini 1.5 Flash a set of pre-trained data of their own and tune it to improve model performance significantly.
JULY 17, 2024 / Go
Genkit for Go is an open source framework for building AI-powered applications in Go. It leverages Go's simplicity, scalability, and security, and is currently in alpha.
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.
AUG. 2, 2023
Google Lab Sessions is a series of experimental AI collaborations with innovators. In our latest Lab...
JULY 29, 2025 / AI
Max's journey introduces LQRax, a JAX-native LQR solver, which exemplifies the growing JAX robotics ecosystem that includes tools like Brax, MJX, and JaxSim, highlighting the benefits of JAX for computational efficiency in optimal control and simulation, and for seamlessly integrating model-based and learning-based approaches.
