It wouldn’t be wrong to say that artificial intelligence (AI) is not a drop; it’s the entire ocean in a drop. And with that thought in mind, I will classify artificial intelligence based on its most unusual types that are not too mainstream to be leveraged.
Artificial intelligence is simply a combination of human-sciences and robotics, and this unique arrangement is transforming the world in several unprecedented ways.
Many experts believe that AI’s powerful capabilities will soon take over human interaction in multiple domains in the coming years. However, I am still standing with the mindset that human interaction is irreplaceable, but AI can better partner with humans to accelerate the pace and proximity of required tasks.
So, what exactly is artificial intelligence all about? Why do we need to rely upon it? What are its types? How does it help us in leveraging business opportunities? This and much is yet to explore in this blog, which I am going to write. Let’s first start with generic insights on Artificial intelligence.
The basic concepts
Human-like technology is basically a branch of science amalgamated with engineering. Artificial intelligence involves system training that enables a computer to perform as per given instructions.
Mainly, AI uses and analyzes enormous data to perform tasks that otherwise require human intelligence.
Artificial intelligence deployment’s core premise is to help systems execute critical business operations that include decision-making, solving complex problems, anticipating future opportunities and threats, and object detection can also be resolved via AI integration.
Understanding the function of AI
AI is all about replicating human abilities. Therefore, it is significant to understand how it functions or propels computers to behave and analyze just like we humans do.
Together algorithms and relevant sensors impel AI to collect data, observe environmental behaviors, and make decisions based on data analysis.
The AI-based system also has a tool called an actuator responsible for curbing robotic motion analytically.
Phases of Artificial Intelligence
Often the phases and types of artificial intelligence leave readers baffle. Both are deemed as the same thing. However, there is a significant difference between phases and types of artificial intelligence.
The phases or stages of Artificial intelligence helps you understand how it grows or is applied gradually. Let’s explore the phases of artificial intelligence one-by-one.
1. Artificial Narrow Intelligence (ANI)
Artificial Narrow Intelligence is commonly known as weak artificial intelligence. It involves specific tasks to be done only. No broader job is taking part in this stage. Only a specified set of functions is being performed under this phase of AI.
In other words, you can say that the narrow artificial intelligence only works around the pre-defined tasks without embroiling any decision making or thinking ability. Siri and Alexa are the best examples of such AI-based systems.
2. Artificial General Intelligence (AGI)
Artificial general intelligence is a strong phase of artificial intelligence. It can produce behavioral output. AGI involves machines with thinking and decision-making ability, just like humans. Forget not to mention that currently, there are no live examples of strong artificial intelligence. Nevertheless, we can expect it for the future.
3. Artificial Super Intelligence (ASI)
This is the biggest phase of Artificial intelligence. It involves systems with abilities and intelligence that beat humans. The world hasn’t seen this stage in real-time; however, many movies have been made over the subject where machines run and surpass the human environment.
To me, this stage will always remain hypothetical because machines can’t beat humans. Machines are meant to perform tasks under command, whereas humans are designed to give commands using their unbeatable intelligence. Yet, many people belong to the opposite school of thought. Such individuals believe that soon strong AI will prove to be a threat to human existence, and surprisingly, Stephen Hawking also supported the same thought.
So, I assume that now you’ve understood AI and its stages. It’s time to move on with its types. Typically, people know machine learning and deep learning as the most widespread types of artificial intelligence. But there’s much more that you need to explore.
Types of Artificial Intelligence
Artificial intelligence may have various branches that are somewhat connected with AI technology. However, in accordance with the functionality of AI-based systems, it is categorized into four types mainly.
- Reactive Machines AI
- Limited Memory AI
- Theory Of Mind AI
- Self-aware AI
Reactive Machines AI
Reactive machines AI are one of the most ancient types of artificial intelligence. If we talk about their capability, we can’t say they are quite efficient, but work limitedly.
These machines don’t work following a memory-based functionality. However, they emulate the way the human mind reacts to something.
The Reactive machines respond quite similarly to a human mind only when they get triggered to certain stimuli.
Moreover, Reactive machines are not designed to use past data or experiences to update their future actions. Therefore, it’s better to say that these machines have no learning ability.
Reactive AI machines are only useful for automatic responses to a particular set of inputs. Therefore, since they have no memory to use, further modification in the tasks can’t be done.
Limited Memory AI
Limited memory machines are more useful compared to Reactive machines AI. These are the machines that have all the ability to perform like Reactive AI machines. Plus, they also hold the ability to use and analyze historical data for decision-making.
Limited memory AI is frequently used in today’s applications model in which data sets are analyzed to solve future related problems.
Such systems use deep learning AI techniques to train systems for storing and analyzing data. Later, the AI system uses its memory to understand data and provides relevant output or decision.
The best example of limited memory AI is image recognition AI. The system is trained to scan various objects with the help of image labels and stored pictures. Based on stored data, image recognition AI recognizes and scans relevant products.
Let’s say that when an image is being sent to such an AI system, these systems utilize their previous experience as a reference to identify content. By using the past learning experience, this AI system names new images with utter accuracy. The Chatbots and virtual assistants are also following the limited memory AI rules.
Theory of Mind AI
Theory of mind is an AI type that is not as mainstream as limited memory AI and Reactive Machines AI. However, experts are still discovering and working on the Theory of Mind AI.
Theory of Mind is quite a powerful AI and will boost the operational efficiency to the next level, but it’s still in the development phase.
Theory of Mind AI will be powerful enough to penetrate how entities think, behave, and act. Plus, this AI type will also understand human needs, emotions, and how thought processes run.
It is important to mention that AI is also working in emotional intelligence, but integrating the theory of mind AI is a timely process that requires progression in multiple AI branches.
Achieving the Theory of Mind AI level is a slow-moving process since it requires the machine to completely understand humans, their needs, and minds. However, the human mind runs with multiple factors, including emotions, people, and beliefs. Therefore, Theory of Mind AI will take time to design machines able to interact like humans.
Self-Aware AI is a hypothetical type of artificial intelligence. Nevertheless, no one can’t predict how soon the technology will be seen around increasing technology progression.
Self-aware AI is a concept that defines the accuracy of awareness similar to human brains. It means that the Self-aware AI will have the ability to be as self-aware as we humans are.
AI researchers are working on self-aware AI, but achieving this level of precision is an arduous process.
Indeed, it’s farfetched from reality today; however, the self-aware AI will better understand and arouse human emotions. Besides, it will also own its desires, beliefs, and needs.
This is the type of artificial intelligence that tech gurus are worried about because it seems that self-powered robotics might be a potential danger for the human race.
Other branches of AI
AI is not stopping anywhere yet; more advanced AI forms will appear in the upcoming years. Besides the outlined forms and stages, artificial intelligence also has many other associations. Some of the most commonly used AI branches are:
Machine Learning: Unlike most subsets of artificial intelligence, machine learning is not hypothetical. The machine learning technique has almost penetrated all the ways we work. All the major industries have implemented it. Machine learning uses statistical data to train a computer according to the available databases. The best examples of machine learning are image processing and medical diagnosis.
Deep Learning: Deep learning is another sub-branch of Artificial intelligence. It supports the concept of machine learning by enabling computers to pick human instincts thoroughly. As an example, you can see how virtual assistants work and interact with humans.
Natural Language Processing: Natural language processing is a branch of artificial intelligence that aids systems in understanding and manipulating human language. It uses several advanced algorithms and big data sets to improve human-machine interaction. The best examples of Natural language processing are speech recognition systems, autocomplete, and spam detection.
Image Processing: Artificial intelligence image processing is very beneficial for businesses and security purposes. It involves system training to analyze and interpret images more than humans do.
Facial recognition and object detection are some of the most common examples of this type of artificial intelligence.
There you have it! Although Artificial intelligence is a fast pace technology that is continuously taking over countless domains. Yet, predicting the world’s future with other upcoming AI branches is out of assumption right now.
Patricia H. George is a digital marketer and a privacy advocate at firetvsticks.co. She creates content with the core premise of educating internet users on cybersecurity as a top priority. With 7+ years of experience, she features the best cybersecurity tools to curtail rising online threats.