Artificial Intelligence or (AI) is the theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.
Computer science defines AI research as the study of “intelligent agents”: any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals.
Artificial Intelligence is sometimes referred to as machine intelligence, intelligence demonstrated by machines. This is in contrast to the natural intelligence displayed by humans and other animals. The term “artificial intelligence” is applied when a machine mimics “cognitive” functions that humans associate with other human minds, such as “learning” and “problem-solving”.
Artificial Intelligence is a system’s ability to correctly interpret external data, to learn from such data, and to use those learnings to achieve specific goals and tasks through flexible adaptation.
Artificial intelligence was founded as an academic discipline in 1956, and in the years since has experienced several waves of optimism, followed by disappointment, and the loss of funding (known as an “AI winter”), followed by new approaches, success, and renewed funding.
In the twenty-first century, AI techniques have experienced a resurgence following concurrent advances in computer power, large amounts of data, and theoretical understanding; and AI techniques have become an essential part of the technology industry, helping to solve many challenging problems in computer science, software engineering, and operations research.
The scope of AI is disputed: as machines become increasingly capable, tasks considered as requiring “intelligence” are often removed from the definition, a phenomenon known as the AI effect. “AI is whatever hasn’t been done yet.” For instance, optical character recognition (OCR) is frequently excluded from “artificial intelligence”, having become a routine technology.
For most of its history, Artificial Intelligence research has been divided into subfields that often fail to communicate with each other.
These sub-fields are based on technical considerations, such as particular goals (e.g. “robotics” or “machine learning”), the use of particular tools (“logic” or artificial neural networks), or deep philosophical differences. Subfields have also been based on social factors (particular institutions or the work of particular researchers).
The traditional problems or goals of AI research include reasoning, knowledge representation, planning, learning, natural language processing, perception, and the ability to move and manipulate objects.
Modern machine capabilities generally classified as AI include successfully understanding human speech or Natural language processing (NLP) competing at the highest level in strategic game systems (such as chess and Go), autonomously operating cars, and intelligent routing in content delivery networks (CDN’s), and in military simulations.
Artificial Narrow Intelligence (ANI) or Weak AI
Artificial Narrow Intelligence (ANI) also known as “Weak” AI is the AI that exists in our world today. Narrow AI is AI that is programmed to perform a single task; whether it’s checking the weather, being able to play chess, or analyzing raw data to write journalistic reports.
ANI systems can attend to a task in real-time, but they pull information from a specific data-set. As a result, these systems don’t perform outside of the single task that they are designed to perform.
Narrow AI is not conscious, sentient, or driven by emotion the way that humans are. Narrow AI operates within a pre-determined, pre-defined range, even if it appears to be much more sophisticated than that.
Every sort of machine intelligence that surrounds us today is Narrow AI. Google Assistant, Google Translate, Siri and other natural language processing tools are examples of Narrow AI. Some might assume that these tools aren’t “weak” because of their ability to interact with us and process human language, but the reason that we call it “Weak” AI is because these machines are nowhere close to having human-like intelligence. They lack self-awareness, consciousness, and genuine intelligence to match human intelligence; they can’t think for themselves.
When we converse with Google Assistant, it isn’t a conscious machine responding to our queries. Instead, Google Assistant is able to process human language, enter it into a search engine (Google), and return to us with results.
This explains why when we pose abstract questions about things like the meaning of life or how to approach a personal problem to Google Assistant, we get vague responses that often don’t make sense, or we get links to existing articles from the Internet that address these questions.
On the other hand, when we ask Google Assistant what the weather outside is, we get an accurate response. That’s because answering basic questions about the weather is within the range of intelligence that Google Assitant is designed to operate in.
As humans, we have the capacity to assess our surroundings, to be sentient creatures, and to have emotionally-driven responses to situations. The AI that exists around us doesn’t have the fluidity or flexibility to think like we do. Even something as complex as a self-driving car is considered Weak AI, except that a self-driving car is made up of multiple ANI systems.
Benefits of Artificial Narrow Intelligence
Narrow AI by itself is a great feat in human innovation and intelligence. ANI systems are able to process data and complete tasks at a significantly quicker pace than any human being can, which has enabled us to improve our overall productivity, efficiency, and quality of life.
ANI systems like IBM’s Watson, is able to harness the power of AI to assist doctors to make data-driven decisions, making healthcare better, quicker, and safer.
Additionally, Narrow AI has relieved us of a lot of the boring, routine, mundane tasks that we don’t want to do. From increasing efficiency in our personal lives, like Google Assistant ordering a pizza, to rifting through mounds of data and analyzing it to produce results.
Narrow AI is making our lives significantly better
With the advent of advanced technologies like self-driving cars, ANI systems will also relieve us of frustrating realities like being stuck in traffic, which will inevitabley provide us with more leisure time. ANI systems are important building blocks of more intelligent AI which will be the future in Artificial Intelligence.
Artificial General Intelligence (AGI) or Strong AI
Artificial General intelligence or “Strong” AI refers to machines that exhibit human intelligence. In other words, AGI can successfully perform any intellectual task that a human can.
This is AI that we see in movies like “Her” or other sci-fi movies in which humans interact with machines and operating systems that are conscious, sentient, and driven by emotion and self-awareness.
Currently, machines are able to process data faster than we can. But as humans, we have the ability to think abstractly, strategize, and tap into our thoughts and memories to make informed decisions or come up with creative ideas. This type of intelligence makes us superior to machines, but it’s hard to define because it’s primarily driven by our ability to be sentient creatures. Therefore, it’s something that is very difficult to replicate in machines.
AGI is expected to be able to reason, solve problems, make judgments under uncertainty, plan, learn, integrate prior knowledge in decision-making, and be innovative, imaginative, and creative. For machines to achieve true human-like intelligence, they will need to be capable of experiencing consciousness.
Artificial Super Intelligence (ASI)
Artificial Super Intelligence (ASI) will surpass human intelligence in all aspects: creativity, general wisdom, and problem-solving.
Machines will be capable of exhibiting intelligence that we haven’t seen in the brightest human beings. This is the type of AI that worries people, and the type of AI that Elon Musk believes could cause humans to become an andangered species.
Dr. Ben Goertzel is the founder and CEO of SingularityNET, a blockchain-based AI marketplace is one of the premier pioneers in the A.I. field. He had this to say:
Connecting Brains with Computers
Before we have Super Intelligent computers, it’s more likely we will have Super Intelligent humans first.
Elon Musk’s Neuralink hopes to put sensors in human brains by late 2020
The Elon Musk-backed company Neuralink claims its “sewing machine-like” robot will be able to implant threads deep into a human brain. Neuralink says its intention for the technology at first is to do things like help amputees, restore the ability of sight, speech, and sound.
Elon believes that connecting our brains to computers will eventually be the only way to keep up with the progression of artificial intelligence, so the plan is for something much more powerful.
According to futurist Ray Kurzweil, if the technological singularity happens, then there won’t be a machine takeover. Instead, we’ll be able to co-exist with AI in a world where machines reinforce human abilities.
Kurzweil predicts that by 2045, we will be able to multiply our intelligence a billionfold by linking wirelessly from our neocortex to a synthetic neocortex in the cloud. This will essentially cause a melding of humans and machines. Not only will we be able to connect with machines via the cloud, but we’ll also be able to connect to another person’s neocortex. This could enhance the overall human experience and allow us to discover various unexplored aspects of humanity.
Though we’re years away from ASI, researchers predict that the leap from AGI to ASI will be a short one. No one really knows when the first sentient computer life form is going to arrive. But as Narrow AI gets increasingly sophisticated and capable, we can begin to envision a future that is driven by both machines and humans; one in which we are much more intelligent, conscious, and self-aware.
There are four types of Artificial Intelligence: Reactive Machines, Limited Memory, Theory of Mind, and Self-Awareness
Reactive machines are basic, they do not store ‘memories’ or use past experiences to determine future actions. They simply perceive the world and react to it. IBM’s Deep Blue, which defeated chess grandmaster Garry Kasparov is a reactive machine that sees the pieces on a chessboard and reacts to them. Deep Blue cannot refer to any of its prior experiences, and cannot improve with practice.
Limited Memory machines can retain data for a short period of time. While they can use this data temporarily (for a specified period), they cannot add it to a library of experiences. Many self-driving cars use Limited Memory technology: they store data such as the recent speed of nearby cars, the distance of such cars, the speed limit, and other similar types of information that can help them navigate roads.
Theory of Mind
Psychology tells us that people have thoughts, emotions, memories, and mental models that drive their behavior. Theory of Mind researchers hopes to build computers that imitate our mental models by forming representations about the world and about other agents and entities in it. One goal of these researchers is to build computers that relate to humans and perceive human intelligence. While plenty of computers use models, a computer with a ‘mind’ does not yet exist.
Self-aware machines are the still figments of science fiction, though many AI enthusiasts believe them to be the ultimate goal of AI development. Even if a machine can operate as a person does: by preserving itself, predicting its own needs and demands, and relating to others as an equal, the question of whether a machine can become truly self-aware, or ‘conscious’, is up to philosophers to debate.
The field was founded on the claim that human intelligence “can be so precisely described that a machine can be made to simulate it”. This raises philosophical arguments about the nature of the mind and the ethics of creating artificial beings endowed with human-like intelligence which are issues that have been explored by myth, fiction, and philosophy since antiquity. Some people also consider AI to be a danger to humanity if it progresses unabated. Others believe that AI, unlike previous technological revolutions, will create a risk of mass unemployment.
The truth is that, despite being surrounded by it, few of us use the term “AI” in the right context. Misusing and misunderstanding the term can cause us to make fallacious statements and assumptions about what the future holds. As we know, the world is changing at an alarming pace, so thinking critically about these changes is crucial if we want to thrive in the future. To adapt in a world driven by change, understand the implications of AI on society, and clarify where we stand today, we need to first distinguish between the various types of AI.