Artificial Intelligence (AI) has been a buzzword for quite some time! It is tossed around a lot in the business world, and one can’t ignore it. Experts believe that AI has the potential to disrupt numerous industries, and consequently, investors are pumping huge money into it. So what exactly is Artificial Intelligence? Let’s have a brief dive into it.
Who coined the term Artificial Intelligence?
Before getting into the definition of AI, let us learn who coined the term Artificial Intelligence (AI).
In 1956, John McCarthy, a professor emeritus of computer science at Stanford, coined Artificial Intelligence at the Dartmouth Conference.
In the conference, McCarthy proposed, “The study is to proceed based on the conjecture that every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it.”
What is Artificial Intelligence(AI)?
To date, several definitions of Artificial Intelligence have surfaced on the Internet. However, John McCarthy published a paper in 2004 explaining the nitty-gritty of AI.
According to McCarthy’s definition, “It is the science and engineering of making intelligent machines, especially intelligent computer programs. It is related to the similar task of using computers to understand human intelligence, but AI does not have to confine itself to biologically observable methods.”
To put it simply, Artificial Intelligence is when a machine learns to mimic the cognitive functions of the human brain – learning, decision making, and problem-solving.
What are the types of Artificial Intelligence?
Now that you have an idea of what Artificial Intelligence is, let’s dive into its different types. At present, AI is categorised based on two crucial factors – functionality and capabilities.
Based on the functionality, the AI is classified into four types:
Reactive – It is a basic model of AI with limited capabilities. As the name suggests, it reacts to existing conditions. The reactive AI functions the way it has been programmed with a predictable outcome based on a given input. It does not have memory-based functionality, meaning this AI cannot use the previously acquired experience to tweak its present action.
Limited Memory – Limited Memory AI is a bit sophisticated. In addition to having the capabilities of Reactive AI, it can learn from past data and improve over time based on the experience. At present, AI applications like virtual assistants, self-driving vehicles, and chatbots are powered by limited memory AI.
Theory of Mind – Unlike Reactive and Limited Memory AI’s, which is functional and available in the real world, Theory of Mind research and developmental phase.
According to experts, the most crucial aspect of this AI is that machines would have the capability to understand and remember emotions, belief systems, thinking patterns and adjust accordingly, just like humans.
Researchers in Artificial Emotional Intelligence are working towards making machines understand humans better and learn from several factors. However, there is so much work to do!
Self Aware – Self Aware is the final type of AI, and it exists only in the cinematic universe as of now. To put it simply, this AI will enable machines to have self-awareness and self-consciousness on par with human brains.
There are other types as well, considering the capabilities aspect of AI. They are:
Narrow Intelligence – Narrow Intelligence, also known as Weak AI, focuses on one or two tasks and cannot perform beyond what they are programmed to do. It is used in Machine Learning, and Natural Language Processing.
General Intelligence – General Intelligence, also known as Strong AI, can imitate human beings to an extent, meaning it can learn, perceive, understand, and function.
Super Intelligence – According to researchers, the development of Super Intelligence would be the zenith in AI research. Here, the AI system will do exceptionally well, better than any human being can, thanks to vast memory, extraordinary data processing, and remarkable decision-making capabilities.
What are the various use cases of AI?
Artificial Intelligence (AI) is utilised in almost every field, considering the way it gets things done. From curing complex diseases to resolving the global warming crisis, AI is being presented as the solution to all of our problems. In this regard, let’s have a look at some of the important AI use cases.
Personal assistants – Let us start with something that we can relate to easily. Virtual/personal assistants like Alexa (Amazon Echo), Siri (Apple), and Ok Google (Google) are some of the best examples of AI use cases in our daily lives. The AI personal assistance is software that can perform a task based on the user’s verbal commands. The market for AI assistants is growing, and it is safe to say that they will become better and intelligent over the years to come.
Healthcare – The potential of AI in healthcare is vast! AI helps in improving patient experience, care outcomes, and access to healthcare services. It can also increase the efficiency and productivity of care delivery, allowing healthcare professionals to provide better care for more people. Further, AI can be handy in creating personalised medication and care, drug discovery, early diagnosis of disease, gene therapy, and much more.
Fintech – Decision-making is one of the crucial aspects when it comes to dealing with finance. With a broad and deep dataset, AI can assist fintech companies in finding recommended results, which in turn can help officials to make better decisions. Further, AI is also used in Fraud detection and abnormal financial behaviour, chatbots, credit lending, and scoring, billing, expense reporting, user behaviour analysis, among others.
Self-driving cars – Self-driving cars and Artificial Intelligence go hand in hand. Many experts believe that most transportation vehicles, including cars, trucks, ships, and airplanes will achieve some degree or complete autonomy in the next few years. In general self-driving cars uses sensors (radar, cameras, and LiDAR) and AI algorithms. The vehicle collects the data, plans its route, and executes it. The planning and execution part requires machine learning techniques, which is a part of AI.
Robotics – Robotic concepts that were considered science fiction once are becoming reality, thanks to Artificial Intelligence. The application of AI in robotics is to enhance the capabilities of industrial robots. Further, it has also made robotic solutions a bit more flexible by bringing in some learning capabilities. At present, AI-powered robots are used in various fields like Agriculture, retail & fashion, manufacturing, defence, and much more.
What is the future of AI?
Are we confident about the future of AI? Certainly, yes! In fact, Dr. Kai-Fu Lee, a Taiwanese computer scientist, businessman, and writer, said, “[AI] is going to change the world more than anything in the history of mankind. More than electricity.”
Having said that, the final goal of Artificial Intelligence is to have a machine that can function with general intelligence similar to a human being.
So what is its foreseeable future? According to the paper published by MIT on the Work of the Future titled, “Artificial Intelligence And The Future of Work,” it shows a pretty optimistic picture.
Artificial Intelligence will enable new industries to emerge, creating more new jobs than are lost to the technology, adds the report. However, there is a significant need for governments and other parts of society to help smooth this transition.
What is Europe’s approach for AI development and implementation?
European Commission has already laid out an approach to Artificial Intelligence (AI) to build a resilient Europe for the Digital Decade.
“The EU’s approach to artificial intelligence centres on excellence and trust, aiming to boost research and industrial capacity and ensure fundamental rights.”
The European Commission has developed an AI strategy to turn Europe into the global hub for trustworthy Artificial Intelligence (AI).
The AI strategy proposed measures to streamline research, as well as policy options for AI regulation, which fed into work on the AI package.
European Commission says, “The combination of the first-ever legal framework on AI and a new Coordinated Plan with the Member States will guarantee the safety and fundamental rights of people and businesses while strengthening AI uptake, investment, and innovation across the EU.”
Margrethe Vestager, Executive Vice-President for a Europe fit for the Digital Age, says: “On Artificial Intelligence, trust is a must, not a nice to have. With these landmark rules, the EU is spearheading the development of new global norms to make sure AI can be trusted. By setting the standards, we can pave the way to ethical technology worldwide and ensure that the EU remains competitive along the way. Future-proof and innovation-friendly, our rules will intervene were strictly needed: when the safety and fundamental rights of EU citizens are at stake.”
What is AI winter?
AI winter is a term associated with a phase where there is little or no investment in artificial intelligence. This could be caused by lack of advances or results in the field, or investors feeling that the technology is overhyped.
The first AI winter was witnessed in the 1970s, when the funding for AI research dropped sharply and many scientists decided to leave the field, altogether. A large part of this AI winter could be owed to the hype surrounding AI back then and the lack of results to back up that hype. The second AI winter lasted from late 1970s to early 1980s.