The announcement of Gemini 1.5 by Sundar Pichai, CEO of Google and Alphabet, marks a significant step forward in the field of artificial intelligence. This model, developed with security as a priority, promotes significant improvements to Google products, thanks in particular to the Gemini API available in AI Studio and Vertex AI.

Here’s a detailed exploration of Gemini 1.5, its features, and a comparison with ChatGPT 4 Turbo.

Key features of Gemini 1.5

Gemini 1.5 offers significantly better performance than its predecessors, thanks to an innovative architecture and optimizations in model development and infrastructure.

Architecture Mixture-of-Experts (MoE) 

This new architecture enables Gemini 1.5 to be more efficient to train and serve, by selectively activating the most relevant neural paths for the given type of input.

This architecture enables increased specialization and operational efficiency, significantly reducing training and inference times. For companies, this translates into reduced costs and the ability to deploy AI solutions more quickly.

The specialization of “experts” within the model paves the way for highly personalized AI applications, capable of adapting and responding precisely to specific needs in a variety of fields such as healthcare, finance, or education.

Read our article on Mixtral, a model that also uses MoE: Mixtral : The French ChatGPT ?

Processing Capacity Up to 1 Million Tokens

With a standard context window of 128,000 tokens, and the possibility of expanding to up to 1 million tokens, Gemini 1.5 can process and analyze a massive amount of information at once.

This extended capability enables large data sets to be processed and analyzed in a single operation, significantly improving the efficiency of work on complex projects requiring large amounts of information.

Developers can build systems capable of understanding and synthesizing entire documents, voluminous code bases, or video and audio archives, opening up opportunities in documentary research, software development and multimedia processing.

Long Context Understanding

The ability to understand longer contexts without losing sight of important details enables deeper analysis and more consistent, relevant content generation, reducing the need for manual corrections and adjustments.

This feature is particularly useful for creating long and complex content, such as research articles, technical reports, or scripts for multimedia productions, where consistency and precision are crucial.

Multimodal capabilities

Gemini 1.5 Pro is capable of understanding and reasoning across different modalities, including text, image, video, and code, offering exceptional versatility.

Gemini 1.5’s ability to process and generate not only textual content, but also visual and auditory content, enables broader automation of creative and analytical tasks, reducing the time and effort needed to produce high-quality results.

Comparison with ChatGPT 4 Turbo

While ChatGPT 4 Turbo impresses with its ability to generate consistent and appropriate responses, Gemini 1.5 pushes the boundaries with its ability to process up to 1 million tokens, offering unprecedented long-range context understanding.

Architecture and Efficiency

Gemini 1.5’s MoE architecture represents a significant advance over traditional architectures used in ChatGPT, enabling increased efficiency and specialization.

Safety and Ethics

Both models place a premium on safety and ethics. However, Gemini 1.5 benefits from Google’s latest research and techniques in security testing and ethical assessments, promising responsible integration into applications and services.

Gemini 1.5 represents a major evolution in the AI landscape, with significant improvements in performance, efficiency, and multimodal capabilities. Compared to ChatGPT 4 Turbo, Gemini 1.5 offers deeper context understanding and increased versatility, paving the way for innovative applications and services.

As ChatGPT continues to impress in the field of text generation, Gemini 1.5 sets new standards for the future of artificial intelligence.

The increased efficiency of Gemini 1.5 in training and servicing AI models not only rreduces operational costs but also accelerates the development cycle of AI products, enabling a quicker time-to-market.

This efficiency opens the door to more frequent experimentation and faster innovation in the development of AI products and services, encouraging the adoption of AI solutions in sectors previously unexplored due to cost or performance constraints.