It is an advanced AI model designed to organize and make information more useful by leveraging multimodality, long context understanding, and agentic capabilities.
It is an advanced AI model designed to organize and make information more useful by leveraging multimodality, long context understanding, and agentic capabilities. Gemini 2.0, introduced by Google and Alphabet CEO Sundar Pichai, builds on the foundation of Gemini 1.0, which focused on organizing and understanding information across text, video, images, audio, and code. The new model, Gemini 2.0, enhances these capabilities with native image and audio output, native tool use, and advanced reasoning, enabling the creation of AI agents that can think multiple steps ahead and take actions on behalf of users under supervision.
Gemini 2.0 Flash, the first model in the Gemini 2.0 family, is an experimental version designed for low latency and enhanced performance. It supports multimodal inputs and outputs, including natively generated images, multilingual text-to-speech audio, and the ability to call tools like Google Search and execute code. This model is now available to developers via the Gemini API in Google AI Studio and Vertex AI, with general availability planned for January 2025.
The model is integrated into Google products, starting with Gemini and Search, and introduces features like Deep Research, which acts as a research assistant to explore complex topics and compile reports. AI Overviews in Search, powered by Gemini 2.0, will tackle more complex queries, including advanced math equations and multimodal questions, with broader rollout planned for early 2025.
Gemini 2.0 is underpinned by Google’s custom hardware, including Trillium, the sixth-generation TPUs, which powered 100% of its training and inference. The model also supports a new Multimodal Live API, enabling real-time audio and video-streaming input for dynamic applications.
Google is exploring agentic capabilities through research prototypes like Project Astra, a universal AI assistant; Project Mariner, which interacts with browser content; and Jules, an AI-powered code agent for developers. These prototypes aim to enhance human-agent interaction across various domains, including gaming and robotics, while prioritizing safety and responsibility.
Gemini 2.0 represents a significant step toward building AI agents that can assist users in both virtual and physical environments, with ongoing research and iterative development to ensure safe and responsible deployment.
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It is a Python-based project called Teenage-AGI that enhances an AI agent's capabilities by giving it memory and the ability to "think" before generating responses.
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