The beginning of the new era of Artificial intelligence advancement moves forward with the launch of Google Gemini AI, which is more than just a mere AI model. Created with the successful collaboration of Google teams and driven by the motive of causing people to interact with generative AI, the Google Gemini AI model is made from scratch. This includes its robust familiarity and operation across different data types, including videos, images, audio, code, text, etc.
Models of Google Gemini AI
Intending to make Gemini the most adaptable prototype available, it has several versions compatible with various devices. The lighter version, Gemini Nano, is designed to run online and offline on Android devices. The Gemini Pro is a beefier version by Google, with the ability to support and power numerous AI services and provide backend support to Google Bard. However, Google continues beyond there. Its mega-capable Gemini Ultra can support data centers and applications via its powerful LLM.
Human vs Google Gemini AI
Through rigorous testing of all models, it can be concluded that the Gemini Ultra’s performance crosses the several benchmarks used in LLM growth and analysis.
Testing Gemini AI Models:
Achieving a straight 90.0%, the Google Gemini AI model outperformed the benchmark of 86.4%, which was previously set by the GPT-4 model in MMLU, which comprises 57 subjects including but not limited to history, medicine, maths, law, etc. This new benchmark means the Google Gemini AI model has more advanced and capable reasoning to answer more complex questions without bluffing.
Even with the image capabilities, it scores 59.4% on the MMMU benchmark, including deliberate reasoning in different domains; after testing its image feature with the previous state-of-the-art models, it can be said that the Google Gemini AI model creates images and detects them without the help of optical character recognition (OCR) system.
All these bench scores highlight earlier indications of the Google Gemini AI model’s success and its capacity for multimodality and intricate logic proficiency.
Building the Technology with Responsibility
Focusing on Google’s AI Principles, Google aims to assemble Gemini’s multimodal capabilities while looking for potential risks in their development stage. It is concluded that these security evaluations created by Google are implemented to avoid toxicity, discrimination, and cyber offenses.
As claimed by Google, it is their long-term commitment to build a broader ecosystem equipped with best practices and settings to help reduce security risks from AI systems.
Gemini Availability for Users
It is highlighted that Gemini 1.0 is proceeding for different Google products. Users can test the Gemini Pro version by using Bard online, and it is available in more than 170 countries across the globe. They are also planning to expand the existing models to support unexplored languages and places in the future.
Conclusion:
Google is setting a new landmark in the AI world and its effectiveness in users’ daily lives. It is planned that Google will also bring Gemini Nanu to its first smartphone, Pixel Pro 8, which will be run by Gemini Nanu. It will be exciting for users to experience the SmartReply feature on WhatsApp and other messaging apps. At the same time, the Gemini Ultra model is set to launch this year. Overall, such development will be exciting for the world.