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A subset of AI in which systems learn from data to improve their performance on a task without being explicitly programmed. Instead of following hard-coded rules, machine learning models identify patterns in training data and use those patterns to make predictions or decisions on new data.

A visual automation platform (formerly Integromat) that allows users to build complex multi-step workflows connecting hundreds of apps and services. Make is more powerful and flexible than Zapier for advanced automation scenarios, with a visual drag-and-drop workflow builder and support for complex data transformations.

An autonomous AI agent platform that can independently browse the web, write and execute code, manage files, and complete complex multi-step tasks with minimal human supervision. Manus represents a new generation of general-purpose AI agents that go beyond chatbots to actively accomplish goals on behalf of users.

The ability of an AI agent to retain and recall information across multiple interactions or sessions. Without memory, each conversation starts fresh. With memory, an AI agent can remember user preferences, past decisions, and context from previous sessions — enabling more personalized and coherent long-term assistance.

Microsoft's AI assistant integrated across the Microsoft 365 suite (Word, Excel, PowerPoint, Outlook, Teams) and Windows. Microsoft Copilot uses GPT-4 and Microsoft's proprietary models to help users draft documents, analyze spreadsheets, generate presentations, summarize emails, and search across their organization's data.

One of the most popular AI image generation tools, known for producing highly artistic, detailed, and visually stunning images from text prompts. Midjourney operates primarily through Discord and a web interface. It is widely used by designers, marketers, and content creators for concept art, marketing visuals, and brand imagery.

A French AI company and model family known for producing highly efficient, high-performance open-source models. Mistral Large 3 (December 2025) is a 41B active parameter mixture-of-experts model competitive with much larger models. Mistral models are popular for their balance of capability, speed, and open availability.

A neural network architecture where different 'expert' sub-networks specialize in different types of inputs, and a routing mechanism selects which experts to activate for each input. MoE models like GPT-4, Mistral, and DeepSeek can be very large in total parameters but efficient in practice because only a fraction of parameters are active for any given input.

A phenomenon where AI models trained on AI-generated data progressively degrade in quality over generations, eventually losing the diversity and accuracy of the original human-generated training data. As more AI-generated content floods the internet, model collapse is a growing concern for future AI training. It underscores the importance of high-quality, human-generated training data.

An open standard developed by Anthropic that defines how AI models connect to external tools, data sources, and services. MCP provides a universal interface — like a USB-C port for AI — so that any AI assistant can connect to any tool (databases, APIs, file systems, web browsers) without custom integration code for each combination. MCP is rapidly becoming the industry standard for AI agent tool use.

A technique for creating a smaller, faster AI model (the student) that mimics the behavior of a larger, more capable model (the teacher). The student model is trained to reproduce the teacher's outputs rather than the original training data. Distillation enables deploying powerful AI capabilities on devices with limited compute, like smartphones.

A system in which multiple AI agents work together, each with specialized roles, to complete complex tasks that would be difficult for a single agent. In a multi-agent system, one agent might research, another might write, and a third might review and edit — all coordinated by an orchestrator agent.

AI systems that can process and generate multiple types of data — such as text, images, audio, and video — in a single model. Multimodal AI enables applications like analyzing an image and answering questions about it, transcribing audio, or generating video from a text description. GPT-4o, Gemini, and Claude are all multimodal AI models.

The practice of providing AI models with multiple types of input — such as text combined with images, audio, or documents — to get richer, more contextually aware responses. Multimodal prompting is possible with models like GPT-4o, Claude, and Gemini. For example, uploading a photo of a property and asking 'What improvements would increase this property's value?'