AI Layers

Generative AI

or GenAI, which is familiar to many people, is artificial intelligence capable of generating text, images, or other media. Examples are ChatGPT, DALL-E, Google Bard and MidJourney. Using generative models, they select patterns and structures learned from input training data and produce similar data output.

While AI is more than GenAI, many implementations still consist of three layers similar to Gen AI.

AI as experienced

by people is a technology that enables machines to learn from experience, adjust to new inputs, and perform human-like tasks. In addition to applications such as image recognition, speech recognition, natural language processing, and recommendation systems, AI can also: filter email spam, categorize and classify documents, analyze telemetry streams, defend against incoming missiles and assist doctors in complex medical procedures, such as surgery or diagnosis.

Machine Learning

involves training algorithms for computers to learn from data, without being explicitly programmed. It may involve unsupervised learning, supervised learning, or reinforcement learning.

Deep Learning

attempts to simulate the behavior of the human brain with interacting multi-layer neural networks immerged in very large sets of data



Content

• 2Life.us Home
• AI Construction Steps
• Database Types
• AI Layers
• Generative and Classification AI's
• Classification AI Algorithms
• Clustering and AI
• Heuristics
• Biases in AI
• Knowledge Inference
• Incremental vs. Radical
• Induction, Reduction, and Abduction