Google Bard, a flagship product in Google’s AI suite and a competent rival to ChatGPT, is set to receive a significant update today. This update, as announced by Google, aims to substantially augment Bard’s capabilities. The secret behind this remarkable enhancement is none other than Gemini, Google’s latest and most sophisticated AI model.
Gemini, a product of large-scale collaboration at Google, has been designed from scratch to be multimodal. This means it can seamlessly understand, operate across, and combine different types of information, including text, code, audio, image, and video. The application of the Gemini AI model to Bard is expected to bolster the chatbot’s ability in reasoning, planning, understanding and much more.
What’s more interesting is that Gemini comes in three sizes – Ultra, Pro, and Nano. This strategic design allows it to operate on a wide range of platforms, from mobile devices to high-powered data centers.
The enhancement of Bard with Gemini will occur in two phases. First, Bard will be upgraded with a specifically tuned version of Gemini Pro. But Google won’t stop there. The tech giant has plans for another update next year, dubbed Bard Advanced. This version will give users access to the crème de la crème of AI models, starting with Gemini Ultra.
The Bard version with Gemini Pro will initially launch in English across over 170 countries and territories worldwide. Additional languages and countries, including the EU and U.K., will follow suit shortly.
What Is Google Gemini AI Model?
Google Gemini is an AI model that has been brought to life by a massive collaborative effort of teams across Google, including Google Research. It has been developed ground up as a multimodal AI model, which allows it to understand and operate across different types of information seamlessly.
The idea behind building the Gemini AI model was to create an AI system that can generalize and combine information from various modes, such as text, code, audio, image, and video. This enables the AI model to have a deeper understanding of the world around us and also perform complex tasks that require reasoning and planning.
What truly distinguishes Google Gemini from other AI models is its extraordinary flexibility. It exhibits the capability to efficiently function on a wide spectrum of platforms, ranging from robust data centers to compact mobile devices. This adaptability opens up new horizons for developers and enterprise customers, empowering them to build and scale with AI in unprecedented ways.
The first version of Gemini, named Gemini 1.0, has been optimized for three different sizes, each tailored for specific tasks.
- Gemini Ultra – The largest and most capable model, Gemini Ultra, is primed for handling highly complex tasks, harnessing state-of-the-art capabilities that push the boundaries of what AI can achieve.
- Gemini Pro – Acting as the perfect balance, Gemini Pro is designed to scale across a wide range of tasks. It brings forth a level of versatility that complements both intensive and moderate applications.
- Gemini Nano – The smallest of the trio, Gemini Nano, is optimized for on-device tasks. Despite its compact size, it packs a punch, driving efficiency without compromising on performance.
Performance of Google Gemini AI Model
Rigorous testing and evaluation have been carried out on Google’s Gemini models across a myriad of tasks. From understanding natural images, audio, and video to mathematical reasoning, Gemini Ultra has demonstrated an unparalleled performance, surpassing the current state-of-the-art results on 30 of the 32 widely-used academic benchmarks used in large language model (LLM) research and development.
With a remarkable score of 90.0%, Gemini Ultra has the distinction of being the first model to outperform human experts on MMLU (massive multitask language understanding). This comprehensive testing uses a combination of 57 subjects such as math, physics, history, law, medicine, and ethics to challenge both world knowledge and problem-solving abilities.
Google’s innovative benchmarking approach to MMLU allows Gemini to fully utilize its reasoning capabilities. Instead of relying solely on first impressions, the model is encouraged to think more carefully before answering difficult questions. This method has led to significant improvements in Gemini’s performance, setting a new bar for AI language understanding models.
Google is committed to continuously enhancing the performance and capabilities of its AI models, including Gemini. The tech giant has already announced plans for a future update, Bard Advanced, which promises to unlock even more possibilities for developers and businesses.
Stay tuned for more exciting updates as Google continues to push the boundaries of AI with its groundbreaking Gemini model.