What is Artificial Intelligence?
The Technical Answer
How Does It Work?
Artificial intelligence is a field of science concerned with building computers and machines that can reason, learn, and act in such a way that would normally require human intelligence or that involves data whose scale exceeds what humans can analyze.
Artificial intelligence is a specific branch of computer science concerned with replicating the thought process and decision-making ability of humans through computer algorithms. There are many different branches of AI that can create and do different things. Some types complete simple tasks, while others are much more complex. Some AI programs adjust their own algorithms, and some specialized algorithms are so advanced they can beat human experts in their given fields
AI is a broad field that encompasses many different disciplines, including computer science, data analytics and statistics, hardware and software engineering, linguistics, neuroscience, and even philosophy and psychology.
On an operational level for business use, AI is a set of technologies. Technolgies that are based primarily on machine learning and deep learning, used for data analytics, predictions and forecasting, object categorization, natural language processing, recommendations, intelligent data retrieval, and more.
From a technical perspective, modern AI systems primarily utilize machine learning (ML) techniques, particularly deep learning, which involves multi-layered artificial neural networks inspired by the biological neural networks in human brains. These networks consist of interconnected nodes (neurons) that process information through weighted connections, which are systematically adjusted during the training process.
The Learning Process
While the specifics vary across different AI techniques, the core principle revolves around data. AI systems learn and improve through exposure to vast amounts of data, identifying patterns and relationships that humans may miss.
This learning process often involves algorithms, which are sets of rules or instructions that guide the AI’s analysis and decision-making. In machine learning, a popular subset of AI, algorithms are trained on labeled or unlabeled data to make predictions or categorize information.
Deep learning, a further specialization, utilizes artificial neural networks with multiple layers to process information, mimicking the structure and function of the human brain. Through continuous learning and adaptation, AI systems become increasingly adept at performing specific tasks, from recognizing images to translating languages and beyond.
Types of Artificial Intelligence
Deep learning, a further specialization, utilizes artificial neural networks with multiple layers to process information, mimicking the structure and function of the human brain. Through continuous learning and adaptation, AI systems become increasingly adept at performing specific tasks, from recognizing images to translating languages and beyond.
Artificial intelligence can be organized in several ways, depending on stages of development or actions being performed.
For instance, four stages of AI development are commonly recognized.
- Reactive machines: Limited AI that only reacts to different kinds of stimuli based on preprogrammed rules. Does not use memory and thus cannot learn with new data. IBM’s Deep Blue that beat chess champion Garry Kasparov in 1997 was an example of a reactive machine.
- Limited memory: Most modern AI is considered to be limited memory. It can use memory to improve over time by being trained with new data, typically through an artificial neural network or other training model. Deep learning, a subset of machine learning, is considered limited memory artificial intelligence.
- Theory of mind: Theory of mind AI does not currently exist, but research is ongoing into its possibilities. It describes AI that can emulate the human mind and has decision-making capabilities equal to that of a human, including recognizing and remembering emotions and reacting in social situations as a human would.
- Self aware: A step above theory of mind AI, self-aware AI describes a mythical machine that is aware of its own existence and has the intellectual and emotional capabilities of a human. Like theory of mind AI, self-aware AI does not currently exist.
A more useful way of broadly categorizing types of artificial intelligence is by what the machine can do. All of what we currently call artificial intelligence is considered artificial “narrow” intelligence, in that it can perform only narrow sets of actions based on its programming and training. For instance, an AI algorithm that is used for object classification won’t be able to perform natural language processing. Google Search is a form of narrow AI, as is predictive analytics, or virtual assistants.
Deep learning, a further specialization, utilizes artificial neural networks with multiple layers to process information, mimicking the structure and function of the human brain. Through continuous learning and adaptation, AI systems become increasingly adept at performing specific tasks, from recognizing images to translating languages and beyond.
Artificial general intelligence (AGI) would be the ability for a machine to “sense, think, and act” just like a human. AGI does not currently exist. The next level would be artificial superintelligence (ASI), in which the machine would be able to function in all ways superior to a human.
