The famous John Mccarthy, a prominent American computer scientist who received the Turing Prize in 1971 for his contributions to the field of computing, coined the term “Artificial Intelligence” (AI) for the first time in 1956, during the conference of Dartmouth. This word refers to the use of computers and other technologies for the purpose of simulate intelligent behavior and critical thinking comparable to that of a biological human being.
Human and animal intelligence involves consciousness and emotionality, while AI today is a conglomerate of primarily objective numbers and guidelines. However, an intelligent agent is not one who follows a code perfectly, but one who is able to perceive his environment and to undertake actions “autonomously” which maximize the chances of success of the task at hand.
At the social level, AI has connotations that humans expect from an “intelligent” being, such as reasoning, perceiving, learning, and being able to solve problems according to environmental impositions. The border between computing and AI is very fragile, because as the processes to “command” a machine to do something are mastered, the autonomy in the “thinking” of the program is limited. This phenomenon is known as the “AI effect”, the specifics of which we are reserving for another opportunity.
To the general public, AI looks like an ethereal, fantastic, and difficult-to-understand entity: nothing could be further from the truth, as intelligent computer models surround us more and more without us realizing it. To put this reality into perspective, we tell you today types of artificial intelligence and their characteristics. Don’t miss it.
What are the types of artificial intelligence in machines?
An AI is not an anthropomorphically shaped robot serving tea in a domestic setting, although the term has historically been associated with these fantastic situations.. Without going any further, Siri, the iOS voice assistant, is considered artificial intelligence to use because it relies on natural language processing to meet the needs of consumers. It’s not a robot, but there’s no denying that it’s an AI model that we all use without realizing it.
If we understand AI as a broad spectrum at the IT level, we won’t be surprised to learn that the number of companies using it has increased by 270% over the past 4 years. From product recommendations as we surf the internet to how smartphones work, artificial intelligence surrounds us everywhere: computer intelligence goes hand in hand with social demands, at the research level, and even in the field. of global health.
However, an early split is necessary: not all artificial intelligences are the same. We present the types of AI, based on 2 very different parameters: capacity and functionality. Let’s go.
1. By capacity
While those outside the topic believe we are on the rise of artificial intelligence, human society has only discovered the tip of the iceberg in this regard. Understand what we mean by the following lines.
1.1. Narrow AI
This variant corresponds to the vast majority of artificial intelligences present on Earth today. This type of AI is trained to perform a specific and very limited type of activity, so it can fail unpredictably if you try to act beyond its limits. Although it is a rational entity, its radius of action is very narrow, hence the qualifier.
Siri is a perfect example of narrow artificial intelligence, because it works perfectly, but within a very limited range of predefined functions. Other specific cases are programs that play chess, cars that drive themselves, and mechanisms that recommend advertising to us based on our research.
1.2. General artificial intelligence (general AI)
This kind of artificial intelligence can, in theory, perform any type of task with the same efficiency as a biological human being. We are talking from a theoretical point of view, because currently general AI continues in a hypothetical setting, because it could not develop.
While narrow AI was not designed with the idea of doing activities that are cognitive in nature and marked by “personality” as a human being, general AI aspires to reach this area at some point. . It is not a question of implementing a framework of action and instructions to the machine itself, but of simulating within it the processes of the human brain which allow the computational entity, in theory, to carry out any activity with the same autonomy as a human. . To date, more than 40 organizations are studying the field of general AI.
1.3. Super AI
Once again, we are faced with a term that today is a pipe dream. A super AI must be able to do any activity better than humans, and on top of that, demonstrate the ability to think, reason, solve complex questions, apply own judgments, plan from experience, learn and communicate on one’s own.
This term poses a real challenge to the world of research, because we still wonder whether it is possible to get there only at a given moment in human history. Some authors argue that since the brain is a mechanical system, it should be possible to simulate it using synthetic materials. However, large differences and changes in human thinking suggest that reasoning systems based on the very nature of our species with even more complex abilities are both a physical and a biological impossibility.
2. For its functionality
From there, we’ll go a little faster, ditching guesswork and focusing on the usefulness of artificial intelligence.
2.1. Responsive machines
Purely reactive machines they are the simplest type of AI that can be designed. They do not store memories or experiences from the past in order to implement them in the future, because they simply focus their scope on a specific time and “try to do it as well as possible” with the information available in the field. the “now”.
2.2. Limited memory
These calculation entities are able to store past experiences or data for a limited short period of time. An excellent example of this type of AI are artificial cars, as they recall recent data in order to best perform their task, such as the speed limit, the route to follow, the safe distance between 2 vehicles and other basic parameters. .
2.3. Theory of the mind of AI
This type of AI should be able to understand human emotions, social constructs, beliefs and other parameters in order to be able to interact with us like 2 people would. We speak in the conditional, because the machines that apply the theory of mind have not yet been designed.
2.4. Self-knowledge machines
Self-awareness is one of the primary and ambitious goals of computer research today. A self-aware machine must not only be able to store past data, but also to create its own judgment based on it and act according to whatever autonomous body it deems appropriate., thereby adding such complex terms to the equation as feelings and values.
As you can see, the only AI available today is narrow type, either in the form of a responsive machine or in the form of limited memory. In any case, with these assessments, at no time did we want to undermine the historic milestone of having artificial intelligence today. An AI is programmed to perform a task, yes, but let’s not forget that it does it in the most efficient way possible and by responding to environmental variations with expertise.
Define the programming limit and AI is a less complex debate, because the more you know, the easier it is to program a machine to do exactly what you want. Of course, the future of artificial intelligence lies in general AI and in computational entities capable of developing self-awareness. Only time will tell if the limit is biology.
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