Exploring the foundations, houses, roads, and application districts of AI
A visitor’s map of AI City. Some destinations are open; others are still under construction
Welcome to AI City
Artificial Intelligence can feel like arriving in an enormous city for the first time.
Everywhere we look, we see unfamiliar names: machine learning, deep learning, neural networks, transformers, Large Language Models, Vision-Language Models, agents, robots, and autonomous systems.
News reports usually show us the tallest buildings: ChatGPT, image generators, self-driving cars, and humanoid robots. These landmarks are impressive, but they are only the visible skyline.
Beneath them are foundations built over many decades. Between them are roads, bridges, and information pathways. Beyond them are entire districts where AI is applied to medicine, science, transportation, education, and the physical world.
This guide is designed for curious visitors. You do not need to be a mathematician or computer scientist. We will begin with familiar stories and metaphors, then walk gradually toward the technical ideas.
Petit à petit. One street at a time.
How to Read the Map
AI City has two dimensions.
The vertical dimension shows the four layers of construction:
- Mathematical and computational foundations
- Machine learning and deep learning methods
- Intelligent models and capabilities
- Real-world applications
The horizontal dimension shows how different capabilities communicate. Vision connects with language. Memory supports understanding. Reasoning supports decisions. Agents turn decisions into actions.
No single house is the whole of intelligence. Intelligence emerges when the houses work together.
For a short explanation of the redesigned architecture, visit:
The New Blueprint of AI City Open to visitors
Layer 1: The Foundations Beneath the City
Our tour begins underground.
Mathematics, linear algebra, calculus, probability, statistics, logic, algorithms, optimization, data, and computing form the bedrock of AI City. They are not always visible from the street, but every house depends upon them.
Tour Stop: The Basement Beneath the Machine
Why are Large Language Models houses rather than foundations? This essay explores the older mathematical and computational structure beneath today’s AI systems.
Status: Open to visitors
The Foundation of AI: Why Large Language Models Are Only the House, Not the Basement
Future Stop: Mathematics Square
A friendly tour of vectors, matrices, probability, statistics, calculus, and optimization.
Status: Planned
Future Stop: The Data Reservoir
Where training examples come from, how they are prepared, and why data quality matters.
Status: Planned
Layer 2: The Learning and Engineering Level
Foundations alone do not make a system intelligent. The second layer contains the machinery that allows computers to learn patterns, improve from examples, and produce predictions.
Future Stop: The Machine Learning Workshop
An introduction to supervised learning, unsupervised learning, prediction, classification, and clustering.
Status: Planned
Future Stop: The Deep Learning Factory
How neural networks learn increasingly complex representations from data.
Status: Planned
Future Stop: CNN Observatory
How convolutional neural networks learned to recognize visual patterns, from edges and textures to objects.
Status: Planned
Future Stop: Transformer Station
A tour of transformers and attention, the architecture behind many modern language and multimodal systems.
Status: Planned
Engineering Workshop
Not every important advance in AI comes from inventing a new model. Many breakthroughs come from engineering techniques that make AI systems smaller, faster, more efficient, and easier to deploy.
Welcome to the Engineering Workshop, where researchers and engineers refine existing AI models before they are put to work throughout AI City.
Knowledge Distillation Workshop
Imagine an experienced teacher passing years of knowledge to a talented student. In AI, a large and powerful teacher model transfers its knowledge to a much smaller student model, producing an AI system that is faster, more efficient, and less expensive while preserving much of the teacher's capability.
Status: Open to visitors
More workshops on quantization, pruning, fine-tuning, parameter-efficient learning, and model compression will open as AI City continues to grow.
Layer 3: The Houses of Intelligent Capability
We have now reached the visible city.
Each house specializes in a particular capability. However, the houses are connected. Their real power comes from exchanging information and working together.
The Language House
This is the home of Large Language Models. They learn patterns in language and can write, summarize, translate, explain, answer questions, and communicate with people.
Status: Partly open
Visit the current introduction to the Language House
The Language House: How Large Language Models Work — Full tour planned
The Vision-Language House
Vision-Language Models connect images with words. They can identify objects, describe scenes, answer questions about images, and support deeper forms of visual understanding.
Status: Open to visitors
From Scene Understanding to State Understanding
Inside the VLM House: Vision, Language, and Multimodal Learning — Technical tour planned
The Memory House
Memory connects the present with the past. It allows an intelligent system to retain experience, recognize change, preserve context, and learn over time.
Status: Planned
The Sound House
A house for speech, music, environmental sounds, and auditory understanding.
Status: Planned
The Reasoning House
A place for connecting evidence, comparing possibilities, solving problems, explaining conclusions, and predicting what may happen next.
Status: Planned
The Agent House
Agents move AI from answering questions toward pursuing goals, making plans, using tools, and taking actions.
Status: Planned
The Agent House: From Thinking to Doing
Layer 4: The Application Districts
The top layer contains real-world districts where several AI houses cooperate. These districts are not separate forms of intelligence. They are places where different capabilities are combined to solve practical problems.
The Remote Sensing District
Satellite images, aerial photographs, radar, drones, maps, language, and historical observations come together to monitor the Earth and understand change over time.
Connected houses: Vision-Language, Memory, Reasoning, and Agents
Status: Planned
The Remote Sensing District: Understanding the Earth From Above
The Medical District
Medical images, patient histories, clinical language, scientific knowledge, and reasoning must work together to support doctors and researchers.
Connected houses: Vision-Language, Language, Memory, and Reasoning
Status: Planned
The Robotics District
Robots must perceive their surroundings, remember where objects are, reason about physical situations, plan movements, and act safely.
Connected houses: Vision, Sound, Memory, Reasoning, Agents, and Embodied Intelligence
Status: Planned
The Autonomous Systems District
Self-driving cars, marine vehicles, aircraft, and drones must combine sensors, maps, prediction, planning, control, and continuous feedback.
Connected houses: Vision, Memory, Reasoning, Agents, and Embodied Intelligence
Status: Planned
The Education District
AI can help explain ideas, adapt lessons, provide feedback, and support lifelong learning, but effective teaching requires more than producing answers.
Connected houses: Language, Memory, Reasoning, and Personalization
Status: Planned
The Space District
Space exploration brings together robotics, remote sensing, autonomous systems, scientific reasoning, communications, and decision-making under extreme conditions.
Connected houses: Vision-Language, Reasoning, Agents, Robotics, and Remote Sensing
Status: Planned
The Roads That Bring the City to Life
The buildings attract attention, but the roads make the city function.
A useful route through AI City is:
Perceive → Remember → Understand → Reason → Decide → Act → Learn
The same principle can be seen in human intelligence. Our brains contain specialized regions, but these regions are richly connected. Vision communicates with memory. Memory supports reasoning. Reasoning guides action. Action produces new experience, which becomes new learning.
Future Tour: AI City and the Human Brain
Why intelligence may emerge from specialization, integration, and continuous communication.
Status: Planned
What Is Intelligence? AI City and the Human Brain
The Future Skyline
AI City is still under construction.
Some houses are already impressive. Others have only foundations. New roads are being planned between language, vision, memory, reasoning, agents, and the physical world.
Artificial General Intelligence (AGI) may not arrive as one gigantic tower. It may emerge gradually as the entire city becomes more connected, coordinated, adaptable, and capable of learning from experience.
This tourist guide will grow with the city. Each completed article will open another house, district, workshop, bridge, or underground passage.
Return from time to time. The skyline will change.
Welcome to AI City.
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