AiVibeGenerative AI
Generative AI refers to models that create new content, such as text, images, audio, video, code or 3D data, by learning the patterns in their training data and sampling new outputs that resemble it.
Generative models learn the probability distribution of their training data. Large language models generate text and code token by token; diffusion models generate images, audio and video by progressively removing noise; earlier approaches include generative adversarial networks and variational autoencoders. Many systems are multimodal, accepting and producing several types of content, and are controlled through natural-language prompts.
Business uses include drafting documents and reports, conversational assistants, code generation, summarising maintenance records, producing product images and marketing content, and creating synthetic data to train other models, such as rare defect images for inspection systems.
Risks include factual errors, copyright and licensing questions about training data and outputs, leakage of confidential data, biased or harmful content and misuse such as deepfakes. Organisations address these through governance, human review, guardrails and evaluation. The EU AI Act includes transparency obligations for certain AI-generated content, and NIST has published a generative AI profile for its AI Risk Management Framework.
Key points
- Creates new text, images, audio, video, code or 3D content
- Built mainly on large language models and diffusion models
- Used for drafting, assistants, code and synthetic training data
- Risks include factual errors, IP questions and data leakage
Where AiVibe comes in
AiVibe delivers AI and machine learning services, chatbots and virtual assistants with RAG, MCP tools and voice, AI quality management including bias detection and model validation, and the AIMURUGA AI agent, and builds Intel-based edge AI devices using the Intel Distribution of OpenVINO toolkit.
Related terms
- Large Language Model (LLM)AI & Machine Learning
- Diffusion ModelAI & Machine Learning
- Foundation ModelAI & Machine Learning
- Synthetic DataAI & Machine Learning
- AI GuardrailsAI & Machine Learning
- Responsible AIAI & Machine Learning