Definition
Artificial intelligence is the recreation of human intelligence by machines. It is used in many ways, including language processing, expert systems, speech recognition, machine vision, and cybersecurity.
AI consumes huge quantities of training data, analyses it for patterns and correlations, and uses the findings to simulate similar outputs.
How Artificial Intelligence Works
- Learning: AI programming develops algorithms to turn the data into actionable information and instruct devices to complete specific tasks.
- Reasoning: AI models use a predefined algorithm to produce the desired results.
- Self-correction: AI models continually improve the algorithms to ensure they always produce accurate results.
Types of Artificial Intelligence
- Self-awareness: They are yet to be developed, but they are expected to be able to form representations of themselves and have consciousness.
- Theory of mind: They are still in the early development stages. This type of AI can interact with human thoughts and emotions.
- Limited memory: They analyse past data and events to make predictions.
- Reactive machines: They react without using any form of past memory or experience.
History of Artificial Intelligence
- 1950s and 1960s: The evolution of AI can be traced back to 1950 when Alan Turing proposed a method to test a machine’s ability to exhibit intelligent behaviour. The term ‘Artificial Intelligence’ was later coined in 1956 when the first AI software (The Logic Theorist) was developed. In 1967, researchers began attempts to develop neural networks, but the project faced setbacks. However, AI applications began using neural networks widely in the 1980s.
- 1990s: A seminal textbook ‘Artificial intelligence: A Modern Approach’ was published in 1995. It contained key AI definitions and differences between machines that simply act and those that can reason and think. AI reached a major milestone in 1997 when IBM’s Deep Blue won a chess game against a champion.
- 2000s: John McCarthy redefined Artificial Intelligence in his paper ‘What is Artificial Intelligence’. This is one of the most cited AI research papers. In 2011, IBM Watson won against champions Brad Rutter and Ken Jennings at Jeopardy.
- Modern AI: AI capabilities continued to grow in the 2010s and 2020s. Supercomputers surpassed human accuracy in image recognition and continued winning matches against champions. In 2023, large language models like ChatGPT were released and have shown significant advancement in AI’s ability to process and generate information.
Artificial Intelligence Training Models
- Supervised learning: The training algorithms of the supervised learning model use labelled training data to train the algorithm to recognize objects and patterns.
- Unsupervised learning: Unsupervised learning models use unlabelled data to train the algorithms. The algorithm categorizes the data depending on patterns or descriptions and learns from it.
- Reinforcement learning: These models learn through ‘trial and error’ by performing the task repetitively until the results are within a desirable range.
Artificial Intelligence Benefits
- Automation: AI systems can automate workflows and processes or work independently and autonomously.
- Reduce human error: AI algorithms can learn to follow the same process steps over time and perform tasks accurately without human error.
- Eliminate repetitive tasks: AI models have algorithms that can handle routine tasks, leaving humans to deal with more creative and strategic tasks.
- Fast and accurate: AI can collect, analyse, and present data faster than humans with a higher level of accuracy.
- Infinite availability: Unlike humans, AI does not need to take breaks when performing tasks. The system can stay active forever.
- Accelerated research: AI’s ability to analyse vast amounts of data and identify patterns can speed up research and development.
Weak AI vs Strong AI
Weak AI systems have limited functionality. They can tackle specific tasks perfectly, but unlike humans, they cannot think broadly or adapt to new situations. Examples are Alexa, Siri, and image recognition systems.
A strong AI has human-level intelligence, if not more. Such models can learn, reason, and solve problems creatively like humans. Strong AI is still in the early development stages and has not been fully achieved yet.