is a Contrast to
What is Artificial Intelligence?
Artificial Intelligence suggest that machines can mimic humans in:
Artificial Intelligence is also called Machine Intelligence and Computer Intelligence.
Arthur Samuel 1959:
"Machine Learning is a subfield of computer science that gives computers the ability to learn without being programmed"
Arthur Samuel, IBM Journal of Research and Development, Vol. 3, 1959.
Artificial intelligence is intelligence demonstrated by machines. Unlike natural intelligence displayed by humans and animals, which involves consciousness and emotionality.
Artificial intelligence refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions.
Artificial intelligence leverages computers and machines to mimic the problem-solving and decision-making capabilities of the human mind.
Artificial intelligence is the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings, .... such as the ability to reason, discover meaning, generalize, or learn from past experience.
Artificial Intelligence (AI)
Artificial Intelligence is a scientific discipline embracing several Data Science fields ranging from narrow AI to strong AI, including machine learning, deep learning, big data and data mining.
Narrow Artificial Intelligence is limited to narrow (specific) areas like most of the AI we have around us today:
- Search Engines
- Email spam Filters
- Text to Speech
- Speech Recognition
- Language Translation
- Netflix's Recommendations
- Apple's Siri
- Microsoft's Cortana
- Amazon's Alexa
- IBM's Watson
- Visual Perception
- Face Recognition
Narrow AI is also called Weak AI.
Built to simulate human intelligence.
Built to copy human intelligence.
Strong Artificial Intelligence is the type of AI that mimics human intelligence.
Strong AI indicates the ability to think, plan, learn, and communicate.
Strong AI is the theoretical next level of AI: True Intelligence.
Strong AI moves towards machines with self-awareness, consciousness, and objective thoughts.
One need not decide if a machine can "think".
One need only decide if a machine can act as intelligently as a human.
Machine Learning (ML)
Today, Artificial Intelligence is usually referring to Machine Learning technologies.
While traditional computer programming uses rules (algorithms) created by humans, machine learning uses technologies where the rules (algorithms) are created from the input data (on which the system is trained).
Classical programming uses programs to create results:
Data + Computer Program = Result
Machine Learning uses results to create programs (algorithms):
Data + Result = Computer Program
Neural Networks (NN)
One of the most significant discoveries in history is the power of Neural Networks (NN).
In Neural Networks, many layers of data called Neurons are added together or stacked on top of each other to compute new levels of data.
Commonly used short names:
- DNN Deep Neural Network
- CNN Convolutional Neural Network
- RNN Recurrent Neural Network
Deep Learning (DL)
Deep Learning is a subcategory of Machine Learning.
Deep Learning are algorithms that use Neural Networks to extract higher-level data.
Each successive layer uses the preceding layer as input.
For instance, optical reading uses low layers to identify edges, and higher layers to identify letters.
Deep Learning has two phases:
Input data are used to calculate the parameters of the model.
The "trained" model outputs correct data from any input.
Big data is data that is impossible for humans to process without the assistance of advanced machines.
Big data does not have any definition in terms of size, but datasets are becoming larger and larger as we continously collect more and more data and store data at a lower and lower cost.
With big data comes complicated data structures.
A huge part of big data processing is refining data.