MindMap Gallery Artificial Intelligence Map Notes
Artificial intelligence, also known as omniscience and machine intelligence, refers to the intelligence displayed by machines made by humans. The picture below summarizes the development history, classification and application of artificial intelligence. Collect the picture below to learn!
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This is a mind map about bacteria, and its main contents include: overview, morphology, types, structure, reproduction, distribution, application, and expansion. The summary is comprehensive and meticulous, suitable as review materials.
This is a mind map about plant asexual reproduction, and its main contents include: concept, spore reproduction, vegetative reproduction, tissue culture, and buds. The summary is comprehensive and meticulous, suitable as review materials.
This is a mind map about the reproductive development of animals, and its main contents include: insects, frogs, birds, sexual reproduction, and asexual reproduction. The summary is comprehensive and meticulous, suitable as review materials.
AI
Basic overview
definition
Intuitive understanding
ordinary people
Approximation to human behavior
definition
pragmatism
Artificial intelligence is a new technical science that studies and develops theoretical methods, technologies and application systems for simulating, extending and expanding human intelligence. Artificial intelligence is a branch of computer science;
textbook
Textbook definition: The main purpose of artificial intelligence science is to research and develop intelligent entities. At this point, it belongs to engineering. Needless to say, some basic disciplines of engineering include mathematics, logic, induction, systems, control and engineering. , computer science, and also includes research on other disciplines such as philosophy, psychology, biology, neuroscience, bionics, economics, linguistics, etc. It can be said that this is a cutting-edge discipline that integrates the essence of several disciplines. So artificial intelligence is A comprehensive subject.
Turing test
When the tester is separated from the person being tested (a person and a machine), he or she can ask random questions to the person being tested through some device (such as a keyboard). After multiple tests, if more than 30% of the testers are unsure If the person being tested is a human or a machine, then the machine will pass the test and be considered to have human intelligence.
Classification
weak artificial intelligence
Artificial intelligence that is good at a single aspect;
For example, there is an artificial intelligence that can defeat the world champion of chess, but it can only play chess. If you ask it how to better store data on the hard disk, it will not know how to answer you. "
strong artificial intelligence
human-level artificial intelligence
difficulty
Creating strong artificial intelligence is much harder than creating weak artificial intelligence, and we can’t do it yet
explain
Strong artificial intelligence refers to artificial intelligence that can compete with humans in all aspects. It can do all the mental work that humans can do.
definition
A broad range of mental abilities capable of thinking, planning, problem solving, abstract thinking, understanding complex ideas, rapid learning, and learning from experience;
Strong artificial intelligence should be as comfortable as humans at performing these operations;
super artificial intelligence
Superartificial intelligence: Nick Bostrom, an Oxford philosopher and well-known artificial intelligence thinker, defines superintelligence as "much smarter than the most ignorant human brain in almost all fields, including scientific innovation, general knowledge, and social skills." Superartificial intelligence Intelligence can make you a little better than humans in all aspects, or it can be trillions of times stronger than humans in every aspect. Super artificial intelligence is exactly why
Evolution
1. The birth of artificial intelligence (1943-1956)
From 1943 to 1946, von Neumann proposed the principle of computers
In 1950, Turing published a landmark paper and proposed the famous "Turing Test"
1956, Dartmouth Conference: The birth of AI
2. Early development boom (1950-1970)
symbolism
early reasoning system
Early neural networks (connectionism)
expert system
An intelligent computer program system contains a large amount of expert-level knowledge and experience in a certain field, and can use the problem-solving methods of human experts' knowledge to deal with problems in this field.
3. The second development boom (1980-2000)
Statistical school
After the "AI Winter", in the field of speech recognition, the statistical school replaced the expert system
machine learning
Specializes in studying how computers can simulate or implement human learning behavior to acquire new knowledge or skills, and reorganize existing knowledge structures to continuously improve their performance.
Neural Networks (Connectionism Reborn)
Neural networks are used for tasks such as pattern recognition
4. The third development boom (after 2006)
Big data is widely used
Refers to a collection of data that cannot be captured, managed and processed with conventional software tools within a certain time range. It is a massive, high-growth and diverse data set that requires new processing models to have stronger decision-making power, insight discovery and process optimization capabilities. ized information assets.
deep learning
Discover distributed feature representations of data by combining low-level features to form more abstract high-level ones that represent attribute categories or features.
The development of new technologies such as reinforcement learning, transfer learning, and generative adversarial networks
Common applications of deep learning in machine vision, speech recognition, machine translation and other fields
(non-deep) machine learning
AlphaGo for mass communication of annotation
application
Internet application
search engine
Content recommendation engine
Precision marketing
Speech and natural language interaction
Image and video content understanding and retrieval
User portrait
Anti-fraud
Smart transportation
self-driving cars
sensor
Perception
planning
control
Vehicle inheritance
Internet of Vehicles
High-precision map
emulator
Smart road network and traffic signs
Sharing prototype
Automated logistics vehicles and logistics robots
Intelligent logistics planning
Smart Finance
banking
Risk control and anti-fraud
Precision marketing
Investment decision
Intelligent customer service
Insurance
Risk control and anti-fraud
Precision marketing
Intelligent claims process
Precision marketing
Securities, funds, investment banks, etc.
Quantitative trading
Robo-advisory
Smart medical
Intelligent interpretation of medical images
Auxiliary diagnosis
Medical record understanding and retrieval
surgical robot
Rehabilitation smart equipment
Smart Pharmacy
Smart manufacturing
Smart agriculture
machine translation
Influence
industrial change
The discovery of artificial intelligence will inevitably lead to large-scale industrial changes. Many business models have begun to be reshuffled, which is an opportunity and a challenge for entrepreneurs.
Unemployment and social security issues
With the large-scale use of artificial intelligence, especially the emergence of robots, a large number of repeatable jobs will be replaced by robots, causing many people to lose their careers, thus bringing about a series of social problems. Therefore, we solve the problem of harmonious human life.
The problem of wealth gap
With artificial intelligence travel, the gap between the rich and the rich will further widen. With artificial intelligence, the rich will become richer, while the poor will become poorer because they have lost their jobs.
The problem of uneven regional development
Artificial intelligence is a high-tech industry, and the initial investment is very large. Once it is marketed on a large scale, it can help improve production efficiency in the region. This means that areas lacking artificial intelligence technology are still in a primitive state, just like the late Qing Dynasty. During this period, Britain entered the industrial revolution while China was still in an agricultural society, which would increase the economic imbalance between the two regions.
industrial structure adjustment
In the era of artificial intelligence, the division of labor between humans and machines will promote the adjustment of industrial structure.
The service industry in the era of artificial intelligence
With the upgrade of the service industry, laid-off workers can engage in considerate and caring services while increasing corporate tax revenue.
Education, vocational training, re-education
Dr. Kaifu Li believes that targeted personnel education and retraining should be carried out in areas where artificial intelligence is not good at;
personal impact
Unemployment and social security issues
psychological impact
human self worth
human self-actualization
Human Psychology in the Era of Human-Machine Collaboration
Personal education and personal growth
Choose a career
future
Asimov's three laws of machines
The First Law: Robots shall not harm human beings, or do nothing when witnessing human beings being put in danger;
Second Law: A robot must obey the orders given to it by humans, except when the order conflicts with the First Law;
The third law: Robots must protect their own survival as much as possible without violating the first and second laws.
The Destiny of Humanity-Fermi Paradox
1. There are billions of stars similar to the solar system in the Milky Way, many of which are more than a billion years older than the solar system.
2. Some of these stars are likely to have Earth-like planets, and they are likely to harbor intelligent life.
3. Some of these intelligent life forms may develop interstellar flight technology.
4. Even with the technology we can imagine now, they can fly throughout the galaxy within a million years.
5. Why don’t we see the shadow of an intelligent life in space? This is the famous Fermi Paradox
common forms
robot
Human-machine combination
Non-humanoid intelligent robot
Human-machine interconnection
Relationships: Classes and Machines
With the advent of the era of artificial intelligence, how to deal with the relationship between humans and robots to ensure the interests of humans and achieve a balance in all aspects is a question that has to be faced.
The Essence of Wisdom and Compassion
What is the nature of wisdom? Continuous acquisition? This is a philosophical question that needs to be answered as society progresses.
the fate of the universe
The ultimate fate of the universe is a major issue in physical cosmology. Many scientific theories make predictions about the fate of the universe, including debates about infinite versus finite time. Since the big bang theory has been widely accepted by scientists, the ultimate fate of the universe has become a question that can be discussed.
Method to realize
Based on knowledge model
algorithm model
Based on large amounts of data
machine learning
Classification
supervised learning
unsupervised learning
reinforcement learning
Theoretical system
Mathematical basis
calculus
linear algebra
Probability and statistics
Set theory and graph theory
information theory
game theory
Technical machine basics
computer principles
programming language
operating system
Distributed Systems
Algorithm basics
machine learning algorithm
Machine learning basics
Estimation method
feature engineering
linear model
logistic regression
decision tree
Support Vector Machines
Bayesian classifier
Neural Networks
deep learning
MLP
CNN
RNN
LSTM
GAN
Clustering Algorithm
K-means algorithm
Machine learning classification
supervised learning
Classification tasks
return mission
unsupervised learning
Clustering task
transfer learning
reinforcement learning
problem areas
Language recognition
Character recognition
handwriting recognition
machine vision
Natural Language Processing Machine Translation
knowledge reasoning
natural language understanding
automatic control
Game Theory and Human-Computer Games
chess
Go
Texas Hold'em
Starcraft
Machine learning architecture
Acceleration chip
CPU
GPU
FPGA
ASIC
TPU
Virtualization
container
Decker
distributed structure
Spark
Libraries and Computing Frameworks
TensorFlow
scikt-leam
Torch
MXNET
Theano
Caffe
Microsoft CNTK
Visualization solutions
cloud service
AmazonML
MSCOCC
Google Cloud ML
Microsoft Azure ML
Datasets and Competitions
Ali Tianchi
MSCOCC
Kaggle
ImageNet
Artificial Intelligence Technology in Other Fields
Knowledge graph
statistical language model
expert system
genetic algorithm
Game algorithm