Google is making waves in the AI landscape with the debut of Gemini, its latest generative AI platform developed in collaboration with its AI research labs, DeepMind and Google Research. While the platform shows promise in certain aspects, it also falls short in certain areas, prompting curiosity about its capabilities, applications, and how it compares to its competitors.
Decoding Gemini: A Comprehensive Guide to Google’s Next-Gen AI
Gemini is Google’s highly anticipated generative AI model family, boasting three distinct versions:
- Gemini Ultra: The flagship model serves as the foundation for others.
- Gemini Pro: A “lite” version offering improvements in reasoning, planning, and understanding.
- Gemini Nano: A smaller, efficient model suitable for mobile devices like the Pixel 8 Pro.
Unlike some of its counterparts, Gemini models are “natively multimodal,” designed to work with various data types, including audio, images, videos, codebases, and text in different languages. This versatility positions Gemini uniquely in the AI landscape.
Bard vs. Gemini: Unraveling the Google Branding Conundrum
One source of confusion lies in distinguishing Gemini from Bard. While Bard serves as an interface for accessing certain Gemini models, Gemini itself represents a family of models, not an app or front end. This distinction is crucial, akin to the relationship between ChatGPT and the GPT models that power it.
Additionally, Gemini operates independently from Imagen-2, another model in Google’s AI arsenal, adding complexity to Google’s diverse AI strategy.
Gemini’s Multifaceted Capabilities
Due to its multimodal nature, Gemini models theoretically possess a wide array of capabilities, from transcribing speech and captioning images to generating artwork. While some features are still in development, Google promises a robust suite of functionalities soon.
However, skepticism arises due to Google’s track record, particularly with the Bard launch and a controversial video showcasing Gemini’s capabilities, which turned out to be aspirational rather than reflective of its current state.
Gemini Models in Action
- Gemini Ultra: Initially available to a select set of customers, Ultra aims to assist with tasks such as physics homework, problem-solving, and extracting information from scientific papers. Its comprehensive capabilities extend to generating formulas and updating charts based on new data.
- Gemini Pro: Publicly available, Gemini Pro exhibits varied performance depending on its usage. In Bard, it outperforms Google’s LaMDA in reasoning and understanding, while API integration in Vertex AI allows developers to harness its text and imagery processing capabilities. Despite positive aspects, Gemini Pro faces challenges with complex math problems and has room for improvement in certain areas.
- Gemini Nano: A smaller, efficient version deployed on the Pixel 8 Pro for features like summarizing recorded audio and providing smart replies in Gboard. Its practical applications showcase its potential for on-device processing.
Gemini vs. OpenAI’s GPT-4: A Comparative Outlook
While Gemini’s true standing awaits the release of Gemini Ultra later this year, Google claims superiority over the state-of-the-art, often represented by OpenAI’s GPT-4. Benchmark results, however, show marginal improvements and early user impressions highlight some shortcomings, including factual errors and suboptimal reasoning.
Pricing and Accessibility
Currently, Gemini Pro is free to use in Bard, AI Studio, and Vertex AI during its preview phase. Once it exits preview in Vertex, users can expect pricing at $0.0025 per character for the model and $0.00005 per character for output. The platform’s accessibility spans Bard, Vertex AI, AI Studio, and even Duet AI for Developers, emphasizing its integration into various developer tools.
Where to Experience Gemini
Gemini Pro is accessible in Bard, providing users with a glimpse of its capabilities through text-based queries. Additionally, it is available in preview within Vertex AI via an API, supporting multiple languages and regions.
For developers, AI Studio serves as a comprehensive tool to create chat prompts and chatbots using Gemini Pro. The model’s integration into other tools, such as Duet AI for Developers, Chrome dev tools, and Firebase mobile dev platform, is expected in the coming weeks and early 2024.
Gemini Nano, tailored for on-device processing, is currently featured on the Pixel 8 Pro and will extend to other devices in the future. Developers can sign up for a sneak peek to incorporate Gemini Nano into their Android apps.
As Google’s Gemini continues to unfold, its potential impact on the AI landscape remains a subject of keen interest, with developers and enthusiasts eagerly exploring its capabilities and anticipating further developments in the rapidly evolving world of generative AI.