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Google's AI research and product division
Google AI encompasses DeepMind, Google Research, and the teams building Gemini, Google Search AI features, and AI-powered Workspace tools.
Google AI is the umbrella for Google's artificial intelligence efforts, including Google DeepMind (formed by the merger of Google Brain and DeepMind in 2023), Google Research, and the product teams building Gemini models, AI-powered Search features, and Workspace integrations. Google has been at the forefront of AI research with breakthroughs including the Transformer architecture, AlphaFold, and the Gemini model family. It is one of the largest AI investors and employers globally.
Gemini AI model family
Google Search AI Overviews
Google Workspace AI features
AlphaFold (protein structure prediction)
TPU AI accelerator chips
Vertex AI cloud platform
Google AI Studio
DeepMind research
OpenAI
OpenAI
OpenAI is the AI safety company and research lab that created ChatGPT, GPT-4, DALL-E, Whisper, and the Sora video generator.
Anthropic
Anthropic
Anthropic is an AI safety company founded by former OpenAI researchers, best known for creating the Claude AI assistant family.
xAI
xAI
xAI is Elon Musk's AI company that created Grok, an AI assistant integrated into X (formerly Twitter) with real-time web access.
Google AI founded
by Google / Alphabet
Gemini AI model family
Google Search AI Overviews
Google Workspace AI features
AlphaFold (protein structure prediction)
Google AI today
Active platform with 15+ years of development
RAG (Retrieval-Augmented Generation)
A technique that combines a language model with real-time document retrieval to produce grounded, up-to-date answers.
MCP (Model Context Protocol)
An open standard by Anthropic that lets AI assistants connect to external tools, data sources, and services through a unified protocol.
Agentic AI
AI systems that can autonomously plan, take multi-step actions, use tools, and achieve goals without step-by-step human instruction.
Vector Database
A database purpose-built to store and query high-dimensional vector embeddings, enabling semantic similarity search at scale.
Fine-Tuning
Training a pre-trained language model on a smaller, task-specific dataset to improve its performance on a particular domain or task.
Embeddings
Dense numerical vector representations of text, images, or other data that capture semantic meaning in a form machines can compare.
Prompt Engineering
The discipline of designing and refining input prompts to elicit more accurate, reliable, and useful responses from AI language models.
LLM (Large Language Model)
A deep learning model trained on vast quantities of text that can generate, summarise, translate, and reason about language at human level or above.
AI Intelligence Review
DeepAITool Editorial TeamLast Updated
Jun 2, 2026
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