Artificial Intelligence is one of the most promising technologies even in 2023. The vastness of its use cases and capabilities has surprised the world. With each passing day, a new capability of AI is being discovered. As of 2023, AI technology is already adopted and is being used for specific or numerous purposes by 48% of businesses globally.
We all have heard about the promising use cases, potential, and other relevant aspects of AI but have you ever wondered how does this new-age technology work? If yes, then you will have your answer by the end of this blog.
What is Artificial Intelligence?
Artificial Intelligence is man-made machinery intelligence that replicates or tries to replicate human intelligence and has the potential to go beyond as well.
Types of Artificial Intelligence
Based on the capabilities of AI technology we can classify it into three different groups:
Weak AI
Weak AI is the AI system that is created to perform a specific task or solve a particular problem. These types of AI systems cannot perform tasks beyond the narrow domain for which they have been programmed. An example of weak AI is image recognition systems.
Strong AI
Strong AI is the AI system that possesses human-like intelligence and can perform any intellectual task that can possibly be done by a human. Strong AI systems are not limited to any particular domain or niche.
Super Intelligence
Super Intelligence is the AI system that has capabilities beyond human intelligence. This type of AI system can perform tasks or solve problems that are beyond human comprehension.
How Does AI Work?
AI works utilizing its crucial components. Without its critical components, AI can never work smoothly. Here are the critical components of Artificial Intelligence:
Machine Learning
Machine Learning or ML can be considered the main component or application of AI as it provides the computer system able to learn automatically and enhance its performance via experience. This way the necessity of explicit programming gets reduced.
Machine Learning heavily focuses on developing algorithms that have the ability to assess data to make future predictions. To understand better you can look at Duolingo the language learning app. This application utilizes Machine Learning-based speech recognition technology that helps the application assess users’ spoken language skills.
Apart from Duolingo, social media platforms like Facebook, Instagram, Twitter, and more also use Machine Learning to offer a more personalized experience.
Deep Learning
Deep Learning is a sub-part of Machine Learning that utilizes artificial neural networks. These artificial neural networks learn by data processing and replicate the biological neural networks of a human brain. There are several layers of these artificial neural networks that seamlessly work together to finalize the one output from 10s, 100s, or 1000s of inputs.
For example, you can consider the voice assistants like Siri, Alexa, or even Google. They use the voice recognition system to understand the queries of the users and provide them with appropriate answers.
Neural Network
Neural networks are the key that activates deep learning. As mentioned in Deep Learning neural networks are computer systems acting like neural connections within a human brain.
In a human brain, thousands of neurons create neural networks; similarly, bundles of perceptron create artificial neural networks in computer systems. The best learning method for a neural network is by processing the training examples.
For example when someone asks the AI “Is this image of a Tiger?”, the neural networks will search through the thousands of tiger images that were input during training to generate one particular output.
Cognitive Computing
Cognitive computing is the key component of AI that helps in improving the interaction between human and Artificial Intelligence systems. The main purpose of cognitive computing is to replicate and enhance the interaction between us humans, and machines.
Cognitive computing always tries to mimic the human thought process within a computer model. This key component of AI can help in improving the decision-making of an organization by generating insightful reports.
How AI is Being Used in Some of the Key Industries?
Since the discovery of AI and its potential the usage of this mesmerizing technology has sky-rocketed. Here are a few key industries and how they are using AI:
Healthcare
Healthcare is one of the most important sectors for humans. Artificial Intelligence has taken over this sector in all aspects. Be it for medical diagnosis or the development of drugs AI is present everywhere in the healthcare industry. The AI algorithms can help medical professionals in medical images and reports, identify hidden complicated health issues quickly, and fasten the decision-making process.
Finance
The finance industry is the main target of fraudulent activists. With AI in place, the security of finance sectors improves immensely. Professionals in this industry use AI for fraud detection, risk assessment, and trading. With intelligence beyond humans, AI can help the finance industry identify patterns that even professionals can miss and improve decision-making.
Manufacturing
Artificial Intelligence plays a key role in the manufacturing industry. As the AI algorithms can gather data from the sensors and assess them in no time the manufacturing industry can improve its efficiency and also reduce costs.
Retail
AI plays a crucial role in improving customer experience and increasing sales in the retail industry. AI algorithms can offer personalized product recommendations by assessing customer information and track record. On the other hand, AI can also help retailers to optimize their inventory by offering valuable insight into customer demands.
Final Words
Artificial Intelligence or AI is a blessing for humankind if used correctly. Always remember there are both positive and negative sides to technology so using it properly is necessary. When all its key components are effective the AI systems will offer quality performance. However, the AI system can generate unsatisfactory performances and this can be caused by poor training or integration of the system. Focusing on the right way of training and integration can guarantee high performance from the revolutionary technology.