Google has entered the AI arena with its Gemini family of models, presenting a potential challenge to OpenAI’s widely acclaimed GPT series. Comprising Ultra, Pro, and Nano models, Gemini offers diversity and versatility, catering to tasks ranging from highly complex to on-device efficiency. Unlike GPT-4, Gemini is a multimodal model, proficient across various data types like text, videos, images, and code. Boasting three sizes, Gemini includes Ultra for complex tasks, Pro optimized for low latency and cost, and Nano designed for on-device usage. Ultra, yet to be released, has achieved state-of-the-art benchmarking.
Google emphasizes Gemini’s multimodal capabilities and exceptional speed, attributing its strength to the TPUv5 chips. The model surpasses GPT-4 in processing speed, achieving a 90% score on the MMLU benchmark, outperforming human experts. Trained on extensive datasets of text and code, Gemini ensures real-time learning, continually incorporating new information for up-to-date knowledge. This feature distinguishes it from GPT-4, showcasing its next-generation capabilities and applicability in scientific research.
Gemini excels in analysing vast datasets, recognizing patterns, and generating hypotheses, potentially transforming scientific discovery. Gemini Pro outperforms GPT-3.5 across benchmarks, positioning it as a powerful free AI chatbot integrated into Google’s Bard and Apps. Gemini Ultra stands out as the most potent model, surpassing GPT-4 in various academic benchmarks, reasoning, and Python code generation. The Gemini family’s diverse capabilities and real-time learning may contribute to its potential dominance over existing models, reshaping the landscape of AI.
