Gemini: The Future of AI Models
Gemini is a family of highly capable multimodal models that has been making waves in the AI community since its announcement. In this article, we will explore the capabilities of Gemini and how it compares to other AI models. We will also discuss its potential applications and the future of AI models.
What is Gemini?
Gemini is a family of AI models developed by Google that is capable of understanding and processing multiple modalities, including text, images, audio, and video. It consists of three models: Nano, Pro, and Ultra. Nano is designed for mobile devices, while Pro is the rough equivalent of GPT-3.5, and Ultra is set to be released early next year as the competitor to GPT-4.
How Does Gemini Compare to Other AI Models?
Gemini is not an AGI (Artificial General Intelligence) model, but it is better than GPT-4 in many modalities. However, in text, it is probably a draw. Gemini Ultra, the biggest model, was evaluated on the Chain of Thought with 32 samples, while GPT-4 was given only five examples to learn from before answering each question. Therefore, it is not an apples-to-apples comparison.
Gemini is also better than GPT-4 in image understanding, document understanding, infographic understanding, video captioning, video question answering, speech translation, and coding. It is trained to support a 32,000 token context window, which compares to 128,000 for GPT-4 Turbo.
The Potential Applications of Gemini
Gemini's ability to understand nuanced information and answer questions relating to complicated topics makes it an ideal tool for personalized learning. It can provide customized explanations of subjects and personalized practice problems based on mistakes.
Gemini can also be used for interactive coding. Alpha code 2, based on Gemini Pro, was evaluated on the Codeforces platform and outperformed more than 99.5% of competition participants. Alpha code 2 is not just one model; it is an entire system that generates code samples for each problem.
The Future of AI Models
Google DeepMind is already looking into how Gemini might be combined with robotics to physically interact with the world and become truly multimodal. Gemini will get more senses, become more aware, and gain insanity points as we approach AGI.
In conclusion, Gemini is a highly capable multimodal model that has the potential to revolutionize personalized learning and interactive coding. Its future applications are vast, and it is set to become even more advanced as we approach AGI.
