What is AI?
What is AI? – Artificial Intelligence (AI) is revolutionising many aspects of business and everyday life, from customer service to medicine. AI offers endless potential applications.
Weak AI, commonly referred to as narrow or specialised AI, specialises in performing one specific task very efficiently. Examples include chatbots that respond rapidly to frequently asked questions and image recognition tools that detect objects.
Artificial intelligence is the ability of a machine to perform tasks that normally require human intelligence
Artificial Intelligence can be harnessed to perform tasks that would otherwise require human intelligence, such as performing medical diagnoses or analysing data. Furthermore, AI is often deployed for tasks too difficult or dangerous for human to complete safely–driving cars or defending against cyberattacks are two examples.
There are numerous varieties of AI, but they all share some key similarities. All AI systems learn from data, use both supervised and unsupervised learning strategies, and are created specifically to complete specific tasks. AI applications range from computer vision, speech recognition, language translation and more.
Artificial Intelligence has existed for decades. Alan Turing first introduced AI with his seminal work Computing Machinery and Intelligence published in 1950, in which he examined whether machines could be considered intelligent. Since then, many machines have demonstrated some level of artificial intelligence – IBM Deep Blue defeated the world chess champion in 1997, and one computer even won TV show Jeopardy! in 2011. Many experts claim AI may soon reach human levels of intelligence.
Crafting various types of content such as articles, blog posts, web pages, sales copy, and landing pages becomes a breeze.
It is also the ability of a machine to learn
Machine learning is a subset of artificial intelligence that employs algorithms to teach computers to recognise insights and patterns in data. As the foundational technology for AI systems, machine learning allows them to autonomously solve data-based business issues without human interference and adapt quickly to changing conditions such as financial considerations, road conditions, or military security considerations.
One approach to machine learning is artificial neural networks, which is a model loosely inspired by human cognition. A neural network comprises computational nodes known as perceptrons that process information as it flows through, passing that to subsequent layers where decisions are made on its behalf; until finally the model has achieved desired results such as classifying objects or discovering patterns in data.
Advanced AI takes it a step further with deep learning that goes beyond traditional machine learning to mimic how the human brain logically analyses data. Such advanced AI can perform tasks such as recognising visual scenes, comprehending texts written in natural languages, and using robotic arms to stack blocks.
It is the ability of a machine to think
AI can be defined in many ways, but most agree it refers to the ability of machines to think. A machine may think in many different ways: perceiving its environment, memorising information, learning new languages and solving problems.
IBM Deep Blue was the first machine to demonstrate artificial intelligence when it defeated world champion Garry Kasparov in 1997 at chess, then Watson won Jeopardy! in 2011; both milestones are seen as milestones of progress towards AI development.
One definition of AI is when a machine can understand human speech and communicate with other machines; this process is known as natural language processing. One of the biggest challenges faced by designers of artificial intelligence systems is creating algorithms that are fair and non-discriminatory; failing to do so could lead to biased or unfair decisions being made – an ongoing research topic. A machine with true artificial intelligence would have the capacity to make ethical choices based on reasoning about its own actions and making ethical decisions on its own behalf.
It is the ability of a machine to feel
Computers are currently undergoing a profound transformation that will enable them to process sensory data more closely resembling what humans experience. This technology, known as neuromorphic chips, uses artificial neural networks that mimic massively parallel neurological processes found within humans’ minds. By 2016, this research hopes to achieve full functional computer simulation of all parts of the human brain.
AI does not yet possess true emotions, yet some signs of empathy or sadness can still be detected by AI systems like Google Assistant if someone is feeling sad and suggests an upbeat playlist to help alleviate those emotions.
But it can be challenging to ascertain if these expressions are real or the result of programming, and what exactly consciousness means. Jurgen Schmidhuber holds that machines already experience emotions as part of the learning process but does not believe they experience pain or fear like humans do.
