Types of artificial intelligence (AI) and practical applications

Types of artificial intelligence (AI) and practical applications

Here’s a general overview to give you a better understanding of the different types of artificial intelligence (AI) and their practical aspects.

Types of artificial intelligence

1. Weak or specialised AI

Weak AI, also known as specialised AI, is designed to perform a specific task. For example, Netflix’s recommendation systems analyse your viewing habits to suggest films and series. Similarly, Siri and Alexa, the voice assistants from Apple and Amazon, are programmed to respond to voice commands and perform simple tasks.

2. Strong or widespread AI

Strong AI is still largely theoretical and aims to reproduce human intelligence as a whole. Known in English as Artificial General Intelligence (AGI), this form of AI is said to be capable of general reasoning and autonomous learning, but it raises complex ethical and technical issues. Although there are no clear examples of strong artificial intelligence, the field of AI is innovating rapidly.

AI methodologies

1. Supervised learning

In supervised learning, algorithms learn from labelled data. For example, a speech recognition system is trained with voice recordings and their transcriptions to learn to understand human speech.

2. Unsupervised learning

Here, algorithms discover patterns in unlabelled data. Companies use this method to segment their customers into groups based on similar behaviours. Chatbots use unsupervised machine learning to translate written text into intentions. This is how they are able to respond to users’ queries. Unsupervised Machine Learning is also used in the medical field, in particular to make diagnoses.

3. Reinforcement learning

In reinforcement learning, the algorithm learns by trial and error. A famous example is the AI AlphaGo, which learned to play and win the game of Go against human champions.

Practical applications of AI

Health: AI is helping to diagnose diseases more accurately and speed up medical research. Here are 5 applications of AI in healthcare.

Finance: Trading algorithms are automating stock market operations, while risk analysis is also benefiting from AI.

Industry: Process automation and predictive maintenance have become common practice in industry thanks to AI.

Transport: Autonomous vehicles (like Tesla’s) and intelligent navigation systems are at the forefront of modern transport technology.

Web design: With its machine learning and data processing capabilities, AI is revolutionising the way we design, develop and interact with websites.

Challenges and ethical considerations

AI poses challenges in terms of bias, fairness, impact on employment, confidentiality and data security. The development of strong AI raises questions about the control and regulation of potentially powerful technologies.

Conclusion

Artificial intelligence is transforming our world, presenting both opportunities and challenges. As we move towards an increasingly automated future, it is crucial to promote the responsible and ethical use of AI.