Google has unveiled Gemini, its most advanced and capable artificial intelligence (AI) model, with advanced multimodal capabilities.
This groundbreaking model represents a leap forward in AI technology, offering state-of-the-art performance compared to existing large language models (LLMs).
Sundar Pichai, CEO of Google and Alphabet, emphasized that AI is shaping a profound technological shift, potentially surpassing the impact of the mobile and web revolutions.
He highlighted the significance of AI in driving innovation and economic progress, enhancing human knowledge, creativity, and productivity.
What Is Google Gemini?
Developed by Google DeepMind, led by CEO and co-founder Demis Hassabis, Gemini stands as a testament to Google’s ongoing commitment to being an AI-first company.
I’m very excited to share our work on Gemini today! Gemini is a family of multimodal models that demonstrate really strong capabilities across the image, audio, video, and text domains. Our most-capable model, Gemini Ultra, advances the state of the art in 30 of 32 benchmarks,… pic.twitter.com/sQfxBy9tpT
— Jeff Dean (@) (@JeffDean) December 6, 2023
The model showcases an impressive array of capabilities, particularly in its multimodal understanding – a feature allowing it to process and seamlessly combine different types of information, including text, code, audio, image, and video.
Google Gemini Performance
Gemini 1.0, the first version of the model, comes in three variants: Gemini Ultra, Gemini Pro, and Gemini Nano.
Each is optimized for specific tasks, with Gemini Ultra designed for highly complex tasks, Gemini Pro for a wide range of tasks, and Gemini Nano for efficient on-device tasks.
The model’s performance is exceptional, surpassing human experts in Massive Multitask Language Understanding (MMLU) with a score of 90.0%.
Additionally, Gemini Ultra outperforms existing models in 30 of the 32 widely used academic benchmarks in large language model research.
Gemini’s Multimodal Capabilities
Gemini’s innovative approach to multimodality sets it apart from previous models.
Traditional multimodal models are often limited by their design, which involves training separate components for different modalities and then stitching them together.
In contrast, Gemini was built from the ground up to be natively multimodal, enabling it to understand and reason across various inputs far more effectively.
This capability positions Gemini as a powerful tool in fields ranging from science to finance, where it can uncover insights from vast amounts of data and provide advanced reasoning in complex subjects like math and physics.
Examples from the Google DeepMind report on Google Gemin showcase Gemini’s multimodal capabilities, such as image generation.
It also can handle text, image, and audio, as shown below.
Gemini Excels At Coding
In addition to its multimodal capabilities, Gemini excels in coding tasks. Its ability to understand, explain, and generate high-quality code in multiple programming languages positions it as a leading model for coding.
It also forms the basis for more advanced coding systems, like AlphaCode 2, significantly improving competitive programming problems.
The model’s efficiency and scalability are bolstered by Google’s in-house designed Tensor Processing Units (TPUs) v4 and v5e, making it the most reliable and scalable model to train and serve.
Google Bard Now Powered By Gemini Pro
Google also has announced a significant upgrade to Bard, integrating Gemini Pro to enhance the AI’s capabilities.
This upgrade marks the biggest enhancement Bard has received to date. Gemini Pro has been fine-tuned within Bard to significantly improve its performance in understanding and summarizing information, reasoning, coding, and planning.
Users can now experience Bard powered by Gemini Pro for text-based interactions, with plans to extend support to other modalities shortly.
Initially available in English across more than 170 countries and territories, this upgrade will soon extend to additional languages and regions, including Europe.
Responsible AI Development
Google has prioritized responsible AI development, ensuring comprehensive safety evaluations of Gemini for bias and toxicity.
The company collaborates with diverse external experts and partners to rigorously test the model and address potential risks.
How To Get Gemini
Gemini 1.0 is gradually being integrated across various Google products and platforms and will soon be accessible to developers and enterprise customers via Google AI Studio and Google Cloud Vertex AI.
As part of Google’s commitment to advancing AI responsibly, Gemini Ultra will undergo extensive trust and safety checks before its broader release.
The introduction of Gemini by Google marks a significant milestone in AI development.
Its advanced capabilities, ranging from sophisticated multimodal reasoning to efficient coding, signal the beginning of a new era in AI, opening up remarkable possibilities for innovation across multiple domains.
Featured image: VDB Photos/Shutterstock