Article Summary
Google DeepMind has made significant progress in artificial intelligence (AI) with the release of the first model in the Gemini 2.0 family of models: an experimental version of Gemini 2.0 Flash. This workhorse model boasts low latency, enhanced performance, and native multimodal capabilities for inputs such as images, video, and audio. Additionally, it supports multimodal output like generated images mixed with text and steerable text-to-speech. Gemini 2.0 Flash outperforms its predecessor on key benchmarks and is now available as an experimental model to developers via the Gemini API.
What This Means for You
- As a developer, you can leverage the advanced features and performance of Gemini 2.0 Flash for your projects.
- You may benefit from the new multimodal input and text output capabilities, enabling more interactive and engaging applications.
- By using Gemini 2.0 Flash, you can take advantage of its enhanced speed and performance compared to the previous model, improving user experience and reducing latency.
- With the release of this new model, you can expect more advanced AI capabilities and tools from Google DeepMind, fueling innovation and progress in AI development.
Original Post
Introducing Gemini 2.0 Flash: Our Workhorse Model with Low Latency and Enhanced Performance at Scale
Over the past year, we have continued to make incredible progress in artificial intelligence. Today, we are releasing the first model in the Gemini 2.0 family of models: an experimental version of Gemini 2.0 Flash. It’s our workhorse model with low latency and enhanced performance at the cutting edge of our technology, at scale.
Native Multimodal Capabilities: A Peek into the Future of AI
We are also sharing the frontiers of our agentic research by showcasing prototypes enabled by Gemini 2.0’s native multimodal capabilities.
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Key Terms
- Gemini 2.0 Flash
- Native multimodal capabilities
- Artificial intelligence (AI)
- Workhorse model
- Low latency
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