If you are at all into the tech world or even scrolled through the internet recently you have come across the term AI. Hype continues to rise around artificial intelligence and it’s no wonder why. This concept has been around for decades. YES-decades! It began with myths, stories and rumors of artificial beings endowed with intelligence or consciousness by master craftsmen. The seeds of modern AI were planted by philosophers who attempted to describe the process of human thinking as the mechanical manipulation of symbols. This work culminated in the invention of the programmable digital computer in the 1940s, a machine based on the abstract essence of mathematical reasoning. This device and the ideas behind it inspired a handful of scientists to begin seriously discussing the possibility of building an electronic brain.
Of course the start of AI was nowhere near what it represents today, but it is very interesting to think about how long ago it started and how only in this last decade it’s gaining a lot more traction among the average person.
So, what exactly is AI? – Artificial Intelligence is a technology that allows machines and computer applications to mimic human intelligence, learning from experience via iterative processing and algorithmic training.
AI requires a foundation of specialized hardware and software for writing and training machine learning algorithms. No one programming language is synonymous with AI. However, Python, R and Java, are popular.
There are many different components to an AI system. Each of these is commonly utilized by AI technology:
Machine Learning – A specific application of AI that lets computer systems, programs, or applications learn automatically and develop better results based on experience, all without being programmed to do so. Machine Learning allows AI to find patterns in data, uncover insights, and improve the results of whatever task the system has been set out to achieve. When people refer to AI, they usually refer to this component of the AI system and not the more complex ones. Just because this one is more commonly used.
Deep Learning – A specific type of machine learning that allows AI to learn and improve by processing data. Deep Learning uses artificial neural networks which mimic biological neural networks in the human brain to process information, find connections between the data, and come up with inferences, or results based on positive and negative reinforcement.
Neural Networks – A process that analyzes data sets over and over again to find associations and interpret meaning from undefined data. Neural Networks operate like networks of neurons in the human brain, allowing AI systems to take in large data sets, uncover patterns amongst the data, and answer questions about it.
Cognitive Computing – Another important component of AI systems designed to imitate the interactions between humans and machines, allowing computer models to mimic the way that a human brain works when performing a complex task, like analyzing text, speech, or images.
Natural Language Processing – A critical piece of the AI process since it allows computers to recognize, analyze, interpret, and truly understand human language, either written or spoken. Natural Language Processing is critical for any AI-driven system that interacts with humans in some way, either via text or spoken inputs.
Computer Vision – One of the prolific uses of AI technologies is the ability to review and interpret the content of an image via pattern recognition and deep learning. Computer Vision lets AI systems identify components of visual data, like the captchas you’ll find all over the web which learn by asking humans to help them identify cars, crosswalks, bicycles, mountains, etc.
So, AI systems work by ingesting large amounts of labeled training data, analyzing the data for correlations and patterns, and using these patterns to make predictions about future states. AI usually focuses on 3 key cognitive skills and those are learning, reasoning and self-correction.
We can also differentiate the AI system by weak and strong AI. Weak AI is more commonly used than strong AI. Weak AI is also known as narrow AI. That is a system that is designed and trained to complete a specific task. Industrial robots and virtual personal assistants use weak AI.
Strong AI, also known as artificial general intelligence (AGI), describes programming that can replicate the cognitive abilities of the human brain. When presented with an unfamiliar task, a strong AI system can use fuzzy logic to apply knowledge from one domain to another and find a solution autonomously.
The AI system is a very in detailed topic that can be discussed in depth. This is just a small introduction into the AI world and some basics. Make sure you are subscribed to the blog if these topics interest you, don’t miss out!