AI FUNDAMENTALS

Generative AI

AI Fundamentals

Definition

Generative AI includes models capable of creating new content: text, images, code, music, video. ChatGPT generates text, DALL-E generates images, Copilot generates code. For SMEs, generative AI accelerates the production of marketing content, technical documentation, business proposals, and personalized customer communications.

Related terms

AI Fundamentals

Language Model

A language model is an AI system trained on enormous amounts of text to understand and generate natural language. Large language models (LLMs) such as GPT and Claude can write texts, answer questions, translate, and reason about complex problems. For businesses, they represent versatile assistants for any text-based task.

Computer Vision

DALL-E

DALL-E is the image generation model developed by OpenAI that creates images from text descriptions. DALL-E 3, integrated into ChatGPT, produces high-quality images with precise control over composition, style, and details. Companies use it to quickly create visuals for social media, presentations, and marketing materials.

Computer Vision

Stable Diffusion

Stable Diffusion is an open source image generation model that can be run locally on your own servers. Unlike DALL-E, it does not require sending data to cloud services, offering greater privacy and customization. It can be fine-tuned on specific company products to generate catalog images perfectly consistent with the brand.

EXPLORE

More terms in AI Fundamentals

Artificial Intelligence

Artificial intelligence is the computer science discipline that develops systems capable of performing tasks that normally require human intelligence: understanding language, recognizing images, making decisions. For Italian SMEs, AI represents a concrete opportunity to automate repetitive processes and achieve measurable competitive advantages.

Machine Learning

Machine learning is a subfield of AI in which systems automatically learn from data without being explicitly programmed for every scenario. ML algorithms analyze patterns in historical data to make predictions on new data. In business practice, it is used to forecast demand, classify documents, and optimize production processes.

Deep Learning

Deep learning is an advanced machine learning technique that uses neural networks with many layers (hence 'deep') to learn complex data representations. It underpins modern speech recognition, machine translation, and text generation systems. It requires large amounts of data but produces extraordinarily accurate results.

Neural Network

An artificial neural network is a computational model inspired by the workings of the human brain, composed of nodes (neurons) organized in interconnected layers. Each connection has a weight that is adjusted during training. Neural networks underpin nearly all modern AI systems, from image recognition to text generation.

Language Model

GPT

GPT (Generative Pre-trained Transformer) is the architecture behind ChatGPT, developed by OpenAI. It is a language model pre-trained on vast text corpora that can be used to generate content, answer questions, and perform complex text tasks. GPT-4 and subsequent versions have demonstrated increasingly advanced reasoning capabilities.

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