Google Gemini: Unveiling the Next-Gen Generative AI Platform

Google’s Gemini: A Comprehensive Guide to the Next-Gen AI Suite

Google is making waves in the world of artificial intelligence with the introduction of Gemini, a flagship suite of generative AI models, applications, and services. While Gemini shows promise in certain areas, it falls short in others, as revealed by TechCrunch’s informal review. In this guide, we’ll explore what Gemini is, how you can use it, and how it compares to its competitors.

Understanding Gemini

Developed by Google’s AI research labs, DeepMind and Google Research, Gemini is a family of next-generation AI models that come in three varieties:

• Gemini Ultra: The flagship model
• Gemini Pro: A “lite” version
• Gemini Nano: A smaller, mobile-friendly model that runs on devices like the Pixel 8 Pro

What sets Gemini apart is its “natively multimodal” training, which allows it to work with various types of data, including audio, images, videos, codebases, and multilingual text. This is a significant departure from models like Google’s LaMDA, which was trained solely on text data.

Gemini Apps vs. Gemini Models

Image Credits: Google

Google’s branding has caused some confusion, as it wasn’t initially clear that Gemini models and Gemini apps (formerly Bard) are separate entities. The Gemini apps serve as an interface for accessing certain Gemini models, acting as a client for Google’s GenAI. It’s important to note that Gemini apps and models are also independent from Imagen 2, Google’s text-to-image model available in some of the company’s development tools and environments.

The Potential of Gemini

Given their multimodal nature, Gemini models have the potential to perform a wide range of tasks, such as speech transcription, image and video captioning, and artwork generation. While many of these capabilities have yet to reach the product stage, Google promises to deliver them in the near future. However, the company’s track record with the original Bard launch and a heavily doctored promotional video has led to some skepticism.

Gemini Ultra

According to Google, Gemini Ultra can assist with tasks like physics homework, step-by-step problem-solving, and identifying relevant scientific papers. It can also extract information from these papers and update charts by generating the necessary formulas. While Gemini Ultra technically supports image generation, this feature hasn’t been productized yet, possibly due to its more complex mechanism compared to apps like ChatGPT.

Gemini Ultra is available as an API through Vertex AI and AI Studio, and it powers the Gemini apps. However, access to Gemini Ultra through Gemini Advanced requires a subscription to the Google One AI Premium Plan, priced at $20 per month. This plan also integrates Gemini with your Google Workspace account, allowing for email summarization and note-taking during video calls.

Gemini Pro

Gemini Pro is said to be an improvement over LaMDA in terms of reasoning, planning, and understanding capabilities. An independent study by Carnegie Mellon and BerriAI researchers found that Gemini Pro outperforms OpenAI’s GPT-3.5 in handling longer and more complex reasoning chains. However, like all large language models, Gemini Pro struggles with multi-digit math problems, and users have discovered instances of inconsistent outputs and factual errors.

Google’s Gemini AI: A Powerful Language Model with Multimodal Capabilities

Gemini 1.5 Pro: Improved Data Processing and Multimodal Support

Google has recently introduced Gemini 1.5 Pro, a significant upgrade to its predecessor, Gemini 1.0 Pro. This new model, currently in limited private preview, boasts impressive enhancements in data processing capabilities. Gemini 1.5 Pro can handle up to 700,000 words or 30,000 lines of code, a staggering 35 times more than its predecessor. Additionally, being a multimodal model, Gemini 1.5 Pro can analyze up to 11 hours of audio or an hour of video in various languages, although the processing time can be lengthy.

Gemini Pro is accessible via API in Vertex AI, accepting text input and generating text output. A separate endpoint, Gemini Pro Vision, can process both text and imagery, including photos and videos, and output text, similar to OpenAI’s GPT-4 with Vision model.

Within Vertex AI, developers can customize Gemini Pro for specific contexts and use cases through fine-tuning or “grounding” processes. The model can also be connected to external, third-party APIs to perform particular actions.

AI Studio: Streamlined Workflows for Structured Chat Prompts

AI Studio offers workflows for creating structured chat prompts using Gemini Pro. Developers have access to both Gemini Pro and Gemini Pro Vision endpoints, with the ability to adjust model temperature to control output creativity and provide examples for tone and style instructions. Safety settings can also be tuned within the platform.

Gemini Nano: Efficient On-Device AI

Gemini Nano, a smaller version of the Gemini Pro and Ultra models, is efficient enough to run directly on some phones without relying on server-side processing. It currently powers two features on the Pixel 8 Pro: Summarize in Recorder and Smart Reply in Gboard.

The Recorder app, which allows users to record and transcribe audio, includes Gemini-powered summaries of recorded conversations, interviews, presentations, and more. These summaries are generated on-device, ensuring data privacy.

Gemini Nano is also available in Gboard, Google’s keyboard app, as a developer preview. It powers the Smart Reply feature, suggesting the next thing you might want to say when conversing in a messaging app. Initially, the feature only works with WhatsApp but will expand to more apps in 2024.

Gemini vs. OpenAI’s GPT-4: Benchmarks and Early Impressions

Google has repeatedly highlighted Gemini’s superiority on benchmarks, claiming that Gemini Ultra surpasses current state-of-the-art results on 30 out of 32 widely used academic benchmarks in large language model research and development. The company also states that Gemini Pro outperforms GPT-3.5 in tasks such as content summarization, brainstorming, and writing.

However, the benchmark scores appear to be only marginally better than OpenAI’s corresponding models. Moreover, early impressions from users and academics have not been entirely positive, with reports of Gemini Pro making basic factual errors, struggling with translations, and providing subpar coding suggestions.

Pricing and Availability

Gemini Pro is currently free to use in the Gemini apps, AI Studio, and Vertex AI. Once Gemini Pro exits preview in Vertex, the model will cost $0.0025 per character, while output will cost $0.00005 per character. Customers will pay per 1,000 characters (approximately 140 to 250 words) and, for models like Gemini Pro Vision, per image ($0.0025).

To put this into perspective, summarizing a 500-word article containing 2,000 characters with Gemini Pro would cost $5, while generating an article of similar length would cost $0.1.

Gemini Pro and Ultra can be experienced in the Gemini apps, answering queries in various languages. They are also accessible in preview through Vertex AI via an API, which is free to use “within limits” for the time being and supports certain regions, including Europe, as well as features like chat functionality and filtering.

Gemini Pro and Ultra are also available in AI Studio, allowing developers to iterate prompts and Gemini-based chatbots and obtain API keys for use in their apps or export the code to a more fully featured IDE.

Duet AI for Developers, Google’s suite of AI-powered assistance tools for code completion and generation, now utilizes Gemini models. Google has also integrated Gemini models into its dev tools for Chrome and the Firebase mobile dev platform.

Gemini Nano is currently available on the Pixel 8 Pro and will be coming to other devices in the future. Developers interested in incorporating the model into their Android apps can fill out a form to express their interest.

Google’s Gemini: The Next-Generation AI Assistant

Google has unveiled Gemini, a groundbreaking AI assistant that promises to revolutionize the way we interact with technology. This cutting-edge tool, built on the foundation of large language models and machine learning, is set to transform various aspects of our digital lives.

What Makes Gemini Special?

Gemini stands out from its predecessors by offering an unparalleled level of understanding and adaptability. It can engage in natural, context-aware conversations, providing users with highly personalized and relevant information. Whether you need help with complex tasks or simply want to engage in casual conversation, Gemini is up to the challenge.

Gemini’s Potential Applications

The possibilities for Gemini are virtually endless. From enhancing search engines and virtual assistants to powering advanced chatbots and intelligent home devices, this AI assistant has the potential to streamline and enrich our interactions with technology across the board. Imagine having a virtual companion that can anticipate your needs, provide expert advice, and even entertain you with witty banter – that’s the promise of Gemini.

Gemini on the iPhone?

Rumors are swirling that Gemini might soon make its way to the iPhone. Apple and Google are reportedly in talks to integrate Gemini-powered features into an upcoming iOS update later this year. However, nothing is set in stone, as Apple is also said to be in discussions with OpenAI and has been developing its own GenAI capabilities.

This post was originally published Feb. 16, 2024 and has since been updated to include new information about Gemini and Google’s plans for it.