Introduction
Artificial intelligence (AI) is a branch of Computer Science that deals with making intelligent/smart machines. It has been around for decades now, but it has only recently become an area of real focus for tech companies on a large scale and various other fields such as healthcare, manufacturing, etc.
The term ‘Artificial Intelligence’ was first coined by John McCarthy in 1956. John McCarthy was an American scientist and a computer science enthusiast.
AI is a tool that can be used for good or evil depending on how it’s being used. While AI and machine learning are very closely connected, they are not the same. Machine learning is considered a subset of AI. It's important to understand the difference between Artificial Intelligence(AI) and Machine Learning(ML), which are terms more commonly used together in the context of computer science.
Artificial Intelligence And Machine Learning
Artificial Intelligence is the capability of a computer system to mimic human activities such as learning and problem-solving whereas Machine Learning is an application of Artificial Intelligence(AI). It’s the process of using mathematical data models to help a computer learn without direct instructions. This enables a computer system to continue learning and improving on its own, based on its experience.
The most common forms of AI are:
Artificial Narrow Intelligence (ANI) - This refers to systems that perform very specific tasks and require little creativity; ANI systems can perform tasks such as analysing data, playing chess, translating languages, or doing simple arithmetic calculations. These applications are useful for specific purposes but don't necessarily have much value outside them because they cannot create new things as humans do through creativity or imagination.
Artificial General Intelligence (AGI) - AGI will be able to learn from experiences over time so it becomes an expert at performing complex tasks while being able to create new things based on its own experiences with past events/situations rather than simply repeating a task. This is important because it means that AI systems will be able to perform tasks in a manner similar to “humans”, who are capable of creating new things without them being pre-programmed.
How AI and machine learning work together
When you are looking into the difference between artificial intelligence and machine learning, it is helpful to see how they interact with each other.
This is how the AI and machine learning work together:
An AI system is built using machine learning and other techniques and the Machine learning models are created by studying patterns in the data. After the creation of data models, Data scientists optimise the machine learning models based on patterns in the data to improve their efficiency. The process is repeated and refined until the model's accuracy is high enough for the tasks that need to be done.
The Future of AI:
In the forthcoming years, AI will be the most practical thing around us. The applications of AI are numerous and they’re bound to grow with time. For instance:
All drivable vehicles would go autonomous and the occurrences of accidents would be a thing of the past. Besides, driving would be even more accessible and even the specially-abled people would be able to travel without the aid of a companion. AI in self-driving cars will have the capability to improve as we move on.
The ability of a system to optimise by analysing data on its own opens up opportunities for future applications in other fields not limited to the transportation sector. Speaking of which, I believe that AI will change the medical field forever. AI will play a vital role in making the medicare field much more dynamic and personalised. The vision of personalised medicine would at last be a reality.
With AI and machine learning (ML), we can expect to see orders of magnitude of improvement in what can be accomplished. There's a certain set of ideas that humans can computationally explore. There’s a broader set of ideas that humans with computers can address. And there’s a much bigger set of ideas that humans with computers, plus AI, can successfully tackle. AI enables an unprecedented ability to analyse enormous data sets and computationally discover complex relationships and patterns. AI, augmenting human intelligence, is primed to transform the scientific research process, unleashing a new golden age of scientific discovery in the coming years.
Talking about the future of AI, we can go on and on, but rather than penning it all down, we’ll let ourselves or our future generations experience it themselves with a little anticipation and excitement.
Conclusion
Artificial Intelligence is coming faster than we can anticipate, and we need to be mindful of its uses. AI can be used for good or evil; it's up to us as a society to decide what kind of world we want our future generations to inhabit. It can either be a boon or bane to mankind depending on what fields we implement it in. It is best used in places where the working environment can be risky and unsatisfactory for humans, but for machines tailored to be used in certain situations, it is ideal to simulate repetitive tasks that require little to no creativity.
Artificial intelligence is one of the most exciting developments in modern technology. It has the potential to revolutionise a lot of industries, from healthcare to robotics. AI can also provide solutions for problems that humans can’t solve on their own—like climate change or global poverty. But it’s not just about robots taking over your job, it is the excitement and anticipation of how AI can transform the world to be a better place to reside in.
By: Muhammad Saif
Editor: Zaiba Fathima