Gemini
Gemini is Google's family of multimodal AI models capable of processing text, images, audio, and video. It represents Google's most advanced AI system and competes with models like GPT-4 and Claude.
Understanding Gemini
Gemini is Google DeepMind's family of multimodal foundation models designed to understand and generate text, images, audio, video, and code within a unified architecture. Launched as a successor to earlier models like PaLM, Gemini was built from the ground up to handle multiple modalities natively rather than bolting them on as separate modules. The model family spans different sizes, from lightweight versions suitable for edge AI deployment on mobile devices to ultra-large variants optimized for complex reasoning tasks. Gemini competes directly with OpenAI's GPT series and is integrated into Google products like Search, Workspace, and the Gemini chatbot. Its training leveraged Google's vast infrastructure for distributed training across thousands of TPUs. Gemini exemplifies the trend toward versatile generative AI systems and has demonstrated strong performance across benchmarks in natural language processing, computer vision, and code generation.
Category
Generative AI
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Chain of Thought
Chain of thought is a prompting technique that encourages large language models to break down complex reasoning into intermediate steps. This approach significantly improves performance on math, logic, and multi-step reasoning tasks.
ChatGPT
ChatGPT is an AI chatbot developed by OpenAI that uses large language models to generate human-like conversational responses. It became one of the fastest-growing consumer applications in history after its launch in November 2022.
Claude
Claude is an AI assistant developed by Anthropic, designed to be helpful, harmless, and honest. It is built using Constitutional AI techniques and competes with models like GPT-4 and Gemini.
Diffusion Model
A diffusion model is a generative AI model that creates data by learning to reverse a gradual noise-adding process. Diffusion models power state-of-the-art image generation systems like Stable Diffusion and DALL-E.
Discriminator
A discriminator is the component of a GAN that learns to distinguish between real and generated data. It provides feedback to the generator, creating an adversarial training dynamic that improves output quality.
Few-Shot Prompting
Few-shot prompting provides a language model with a small number of input-output examples in the prompt to demonstrate the desired task format. This technique helps models understand task requirements without any fine-tuning.
Foundation Model
A foundation model is a large AI model trained on broad data that can be adapted to a wide range of downstream tasks. GPT-4, Claude, Gemini, and DALL-E are examples of foundation models that serve as bases for specialized applications.
GAN
A GAN (Generative Adversarial Network) is a generative model consisting of two competing neural networks — a generator and a discriminator. GANs produce realistic synthetic data by training these networks in an adversarial game.