Google is making waves with Gemini, a comprehensive suite of generative AI models, apps, and services. While Gemini shows promise in some areas, it falls short in others, as our informal review has revealed.

So, what exactly is Gemini, how can it be utilized, and how does it compare to its competitors?

To help you stay abreast of the latest Gemini developments, we've compiled this informative guide, which we'll continuously update as new Gemini models and features are introduced.

What is Gemini? Gemini represents Google's much-anticipated next-gen GenAI model family, crafted by the collaborative efforts of Google's AI research labs, DeepMind, and Google Research. It encompasses three main variants:

Gemini Ultra, the flagship Gemini model. Gemini Pro, a lighter version of Gemini. Gemini Nano, a compact, mobile-friendly model tailored for devices like the Pixel 8 Pro. All Gemini models are designed to be inherently multimodal, capable of processing various types of data beyond just text. They underwent both pre-training and fine-tuning across a diverse range of audio, visual, and textual inputs in multiple languages.

This sets Gemini apart from models like Google's LaMDA, which were exclusively trained on textual data and lack the versatility of Gemini models.

What distinguishes the Gemini apps from Gemini models? Google's Bard

Initially, Google failed to clarify that Gemini is distinct from the Gemini apps available on the web and mobile platforms (formerly known as Bard). The Gemini apps serve as interfaces through which specific Gemini models can be accessed, essentially acting as clients for Google's GenAI.

It's worth noting that the Gemini apps and models operate independently from Imagen 2, Google's text-to-image model featured in some of the company's developer tools and environments. The distinction between these components has caused confusion among users.

What capabilities does Gemini offer? Due to the multimodal nature of Gemini models, they theoretically have the potential to perform a wide array of multimodal tasks, including speech transcription, image and video captioning, and artwork generation. While many of these capabilities are still in development, Google has pledged to roll them out in the near future.

However, given Google's track record of overpromising and underdelivering, skepticism remains regarding the actualization of these promises.

Google's original Bard launch was a disappointment, and recent controversies surrounding misrepresented Gemini capabilities have further fueled skepticism.

Nevertheless, assuming Google delivers on its commitments, here's what each tier of Gemini is expected to offer:

Gemini Ultra According to Google, Gemini Ultra leverages its multimodality to assist with tasks such as physics homework, step-by-step problem-solving, and error identification in completed assignments.

Gemini Ultra can also facilitate tasks like identifying relevant scientific papers, extracting pertinent information, and updating charts with refreshed data.

While Gemini Ultra technically supports image generation, this feature has yet to be incorporated into the model's productized version.

Access to Gemini Ultra via what Google terms Gemini Advanced requires a subscription to the Google One AI Premium Plan, priced at $20 per month. This plan also integrates Gemini with users' Google Workspace accounts, allowing for enhanced productivity across various Google services.

Gemini Pro Google asserts that Gemini Pro surpasses LaMDA in its reasoning, planning, and comprehension abilities.

An independent study by researchers from Carnegie Mellon and BerriAI corroborated Gemini Pro's superior performance over OpenAI's GPT-3.5 in handling complex reasoning chains. However, like all large language models, Gemini Pro faces challenges with certain mathematical computations and occasionally produces erroneous output.

To address these issues, Google introduced Gemini 1.5 Pro, an enhanced version boasting improved data processing capabilities. Gemini 1.5 Pro can handle significantly larger volumes of data, enabling more comprehensive analyses across multiple modalities.

Gemini Nano Gemini Nano represents a scaled-down iteration of Gemini Pro and Ultra, optimized for direct deployment on select smartphones, such as the Pixel 8 Pro. It powers features like Summarize in Recorder and Smart Reply in Gboard, offering users enhanced functionality without relying on server-side processing.

Developers interested in integrating Gemini Nano into their Android applications can sign up for early access to this innovative model.

Is Gemini superior to OpenAI's GPT-4? Google claims that Gemini outperforms existing benchmarks, citing its success across 30 of 32 widely used academic benchmarks for large language model research and development. Additionally, Gemini Pro purportedly excels in tasks like content summarization, ideation, and text generation compared to GPT-3.5.

However, some users and academics have raised concerns about Gemini Pro's accuracy, particularly regarding factual correctness, translation accuracy, and code suggestions.

What are the costs associated with Gemini? While Gemini Pro is currently free to use in the Gemini apps, AI Studio, and Vertex AI, Google plans to introduce pricing once Gemini Pro exits its preview phase in Vertex AI.

Upon official release, Gemini Pro will be priced at $0.0025 per character for input and $0.00005 per character for output, with additional charges for image processing. Pricing details for Gemini Ultra have yet to be disclosed.

Where can Gemini be accessed? Gemini Pro and Ultra are accessible via the Gemini apps, AI Studio, and Vertex AI. Developers can leverage these models to create innovative applications and services tailored to specific contexts and use cases.

Gemini Nano is currently available on the Pixel 8 Pro and will expand to other devices in the future. Developers keen on integrating Gemini Nano into their Android applications can request early access to explore its capabilities.

As Gemini continues to evolve, it promises to revolutionize AI-powered experiences across various domains, from education to entertainment. By staying informed and leveraging Gemini's capabilities, developers can unlock new possibilities in the realm of generative AI.