Google Gemini: Everything you need to know about the new generative AI platform

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Google’s Gemini: The All-Encompassing Generative AI Suite

Google is making waves in the generative AI landscape with Gemini, its ambitious suite of AI models, apps, and services. This comprehensive guide breaks down what Gemini is, how you can use it, and how it compares to the competition. We’ll keep it updated as Google releases new features, models, and details about its future plans for Gemini.

What is Gemini?

Gemini is Google’s next-generation generative AI model family, developed by its renowned AI research labs DeepMind and Google Research. It’s not just one model, but a family of four unique variations:

  • Gemini Ultra: The most powerful and advanced Gemini model, designed for complex, multi-faceted tasks.
  • Gemini Pro: A lightweight, more streamlined alternative to Ultra, suitable for a broader range of applications.
  • Gemini Flash: An optimized, "distilled" version of Pro, built for speed and efficiency in specific scenarios.
  • Gemini Nano: Two smaller, offline models – Nano-1 and the more capable Nano-2 – designed for mobile devices.

What sets Gemini apart is its multimodality. Unlike Google’s own LaMDA, which was trained solely on text data, Gemini can analyze and generate content across various formats. This includes text, audio, images, and even videos, offering a more versatile and comprehensive approach to AI. Google claims Gemini models were trained on a massive dataset of publicly available, proprietary, and licensed data, including codebases and texts in diverse languages.

The Ethics of Public Data Training

While Gemini promises groundbreaking capabilities, it’s crucial to acknowledge the potential ethical and legal implications of training models on public data, particularly without explicit consent. Google’s AI indemnification policy aimed at protecting Google Cloud customers from lawsuits related to AI usage includes carve-outs, highlighting the complex legal landscape surrounding this issue. Users, especially those planning commercial applications, should proceed cautiously.

Understanding the Gemini Models vs. Applications

Gemini, confusingly, refers to both the AI models themselves and the applications they power.

  • Gemini models, like Ultra and Pro, are the technological foundation.
  • Gemini apps are user interfaces that connect to these models, providing a chatbot-like experience. They’re analogous to ChatGPT by OpenAI and Claude by Anthropic.

Gemini Apps:

  • Web: Accessible through a web browser.
  • Android: Replaces the existing Google Assistant app.
  • iOS: Integrated into the Google and Google Search apps.

These apps accept text, images, voice commands, and even files like PDFs and (soon) videos. They generate text, images, and engage in conversational interactions. Content seamlessly transitions between the web and mobile apps if you’re logged into the same Google Account.

Beyond the Apps: Gemini’s Integration Across Google Services

Gemini isn’t confined to dedicated apps. It’s gradually being woven into the fabric of core Google services, enhancing features and capabilities:

  • Google One AI Premium Plan ($20): This subscription plan unlocks access to Gemini in Google Workspace apps like Docs, Slides, Sheets, and Meet. It also enables Gemini Advanced, bringing Ultra to the Gemini apps and introducing support for analyzing and answering questions about uploaded files.
  • Google Workspace: Gemini assists with writing and editing in Docs, creating presentations in Slides, analyzing data in Sheets, and generating custom images.
  • Gmail: A side panel allows for email drafting, summarizing message threads, and scheduling emails.
  • Google Drive: Gemini provides file summaries and insights into project details.
  • Google Meet: Gemini translates captions into multiple languages.
  • Google Chrome: Offers an AI writing tool for generating new content or rewriting existing text.
  • Google TV: Generates descriptions for movies and TV shows.
  • Google Photos: Powers natural language search queries for image retrieval.
  • NotebookLM Note-Taking Assistant: Improves note-taking and knowledge management.
  • Code Assist (Duet AI for Developers): Leverages Gemini for code completion and generation.
  • Google Cloud Security Products: Utilizes Gemini for threat intelligence analysis and identifying malicious code.

The Power of "Gems": Custom Chatbots with Gemini

Gemini Advanced subscribers will have the ability to create Gems, customized chatbots powered by Gemini models. These chatbots can be generated from natural language descriptions and shared with others or kept private. Future iterations of Gems will offer expanded integration with Google services, allowing them to perform tasks across various platforms.

Gemini Live: In-Depth Voice Chat

Gemini Live is an upcoming feature for Gemini Advanced subscribers, enabling immersive voice chat experiences within the Gemini apps. Key features include:

  • Real-time Interaction: Seamlessly ask clarifying questions while Gemini is speaking.
  • Adaptive Speech Recognition: Gemini adapts to user speech patterns.
  • Contextual Understanding: Leverages visual input from the user’s smartphone camera to understand the surroundings.
  • Virtual Coaching: Provides assistance for rehearsal, brainstorming, and skill-building.

Gemini Models: Capabilities and What They Can Do

Gemini leverages its multimodality to tackle a diverse array of tasks. Here’s a breakdown of the capabilities of the different Gemini models:

Gemini Ultra:

  • Problem-Solving: Assists with physics homework, solving problems step-by-step, and identifying potential mistakes.
  • Scientific Research: Extracts information from scientific papers, updates charts with new data, and generates relevant formulas.
  • Image Generation: This capability is in development and not yet fully integrated into the Gemini apps.

Gemini Pro:

  • Reasoning and Planning: Offers improved reasoning, planning, and understanding capabilities compared to LaMDA.
  • Enhanced Data Processing: Processes up to 1.4 million words, 2 hours of video, or 22 hours of audio.
  • Code Execution: Iteratively refines generated code to reduce bugs.
  • Contextual Customization: Allows developers to fine-tune the model for specific uses and datasets.
  • Integration with External APIs: Connects to third-party APIs for automated workflows.

Gemini Flash:

  • Optimized for High-Frequency Tasks: Designed for narrow, frequently used tasks.
  • Multimodality: Analyzes and generates text, audio, and image data.
  • Ideal for: Summarization, chat applications, image/video captioning, data extraction, etc.
  • Context Caching: Stores large amounts of information for efficient retrieval.

Gemini Nano:

  • Mobile-Ready: Powerful enough to run on smartphones without server reliance.
  • Powers: Summarize in Recorder (for audio transcription), Smart Reply in Gboard (for messaging), Magic Compose in Google Messages (for message crafting), and future accessibility features in Android.

Gemini Compared to GPT-4

Google has boasted about Gemini Ultra‘s superiority on various benchmarks, claiming it outperforms current state-of-the-art models on many metrics. However, the comparison to OpenAI’s GPT-4 is complex:

  • Benchmarks: While Gemini Ultra might achieve slightly better results on some benchmarks, these tests may not always reflect real-world performance.
  • GPT-4o: OpenAI’s latest GPT-4o model demonstrates superior performance in text evaluation, visual understanding, and audio translation.
  • Anthropic’s Claude 3.5 Sonnet: Outperforms both Gemini 1.5 Pro and GPT-4o in several areas, indicating the rapid pace of AI advancements.

The Cost of Gemini Models

Gemini Pro and Flash are available through Google’s Gemini API for building apps and services, with free options offering limited usage and features. The primary pricing model is pay-as-you-go, with prices based on tokens:

Gemini 1.0 Pro:

  • Input: $0.50 per 1 million tokens
  • Output: $1.50 per 1 million tokens

Gemini 1.5 Pro:

  • Input (up to 128,000 tokens): $3.05 per 1 million tokens
  • Input (over 128,000 tokens): $7.00 per 1 million tokens
  • Output (up to 128,000 tokens): $10.50 per 1 million tokens
  • Output (over 128,000 tokens): $21.00 per 1 million tokens

Gemini 1.5 Flash:

  • Input (up to 128,000 tokens): $0.35 per 1 million tokens
  • Input (over 128,000 tokens): $0.70 per 1 million tokens
  • Output (up to 128,000 tokens): $1.05 per 1 million tokens
  • Output (over 128,000 tokens): $2.10 per 1 million tokens

Note: 1 million tokens are roughly equivalent to 700,000 words.

Gemini Ultra pricing is yet to be announced. Nano is still in early access.

The Future of Gemini: On iPhones and Beyond

Rumors suggest Gemini could be integrated into future iOS updates, potentially powering various features on Apple devices. While Apple is also exploring partnerships with OpenAI and developing its own AI capabilities, the potential for Gemini to reach a wider audience is significant.

Gemini represents a major leap forward for Google in the generative AI space, offering a multifaceted, comprehensive approach that encompasses powerful models, versatile apps, and seamless integration across various platforms. As this technology continues to evolve, it will be interesting to see how Gemini shapes the future of AI and its impact on users around the world.

Article Reference

Emily Johnson
Emily Johnson
Emily Johnson is a tech enthusiast with over a decade of experience in the industry. She has a knack for identifying the next big thing in startups and has reviewed countless internet products. Emily's deep insights and thorough analysis make her a trusted voice in the tech news arena.