Artificial Intelligence

In the event that an AI is capable of acting like a human, how can we be confident that it will continue to do so? An AI entity’s human-likeness can be derived from the following considerations:

Artificial intelligence (AI) Turing Test: What Is It?

An artificial intelligence system must be capable of conversing with a person. Ideally, the human agent should not be able to discern that they are conversing with an AI. The AI must have the following characteristics in order to achieve its goals:

Approach based on cognitive modeling

Human cognition is the focus of this approach, as the name implies. There are three ways to get to the heart of the human mind:

Observing our thoughts and creating a model based on them is called introspection.

The study of the mind and behavior of individuals via the use of psychological experiments.

Using MRIs to examine how the brain behaves in different situations and then creating a computer program that mimics that function is known as brain imaging.

The Application of Mental Laws

Many logical statements control the workings of the human mind under the Laws of Thought. Laws of nature can be formalized and applied to artificial intelligence (AI). If you think about it, solving a problem in principle (strictly following the laws of thought) and doing it in practice might be quite different, requiring contextual nuances to be applied. This technique has certain problems. Also, if there are too many parameters, an algorithm might not be able to repeat our actions because we don’t know the conclusion for certain.

An Approach Based on Rational Agents

A rational agent operates in order to attain the best feasible outcome in the current situation.

There must be logical reasoning behind every action taken by any given entity, according to the Laws of Thought. Occasionally though, there is no logically correct course of action because of the potential for conflicting results and the resulting compromises. Using this strategy, agents try to make the best decisions they can given the current situation. Because of this, it’s a lot more dynamic and flexible agent.

Let’s take a look at how these systems are constructed now that we’ve seen how AI can be programmed to behave like a human.

Are you curious in how AI works?

Reverse engineering human qualities and talents into a machine and leveraging its processing power to outperform human capabilities is the process of building an AI system.

It is necessary to delve deeply into the many sub-domains of Artificial Intelligence in order to gain a thorough understanding of how these domains might be applied to diverse industries. An artificial intelligence course can also help you obtain a deeper grasp of the technology.

In ML, a machine is taught the art of making intelligent inferences and conclusions based on prior knowledge. For example, it looks for trends and analyzes previous data to determine what these data points signify without the need for human experience. Businesses benefit from the time savings and improved decision-making that comes from automating the process of arriving at conclusions based on the analysis of data. You can enroll in a free machine learning course for beginners to learn the fundamentals.

Deep Learning is an ML technique that uses deep learning. In order to classify, infer, and forecast the outcome of inputs, it instructs a computer to do so.

These networks are based on the same principles as human brain cells. Algorithms that mimic the way a human brain works by capturing the connections between several underlying factors and processing the resulting data.

NLP is the study of how computers can read, understand, and interpret human speech. Once a machine has figured out what the user is trying to say, it will give the appropriate response.

Breaking down an image and focusing on distinct portions of the object is the goal of computer vision algorithms. As a result, the computer is more equipped to categorize and learn from a collection of photos, resulting in superior output decisions.

By mimicking a human brain, cognitive computing algorithms analyze text, audio, images and objects in the same way as a human would and strive to produce the intended results. In addition, you can sign up for a free course on artificial intelligence applications.

Types of Computer-Aided Intelligence

Not all types of AI all the above fields simultaneously. Different Artificial Intelligence entities are built for different purposes, and that’s how they vary. AI can be classified based on Type 1 and Type 2 (Based on functionalities). Here’s a brief introduction to the first type.

3 Types of Artificial Intelligence

  • Artificial Narrow Intelligence (ANI)
  • Artificial General Intelligence (AGI)
  • Artificial Super Intelligence (ASI)

What is Artificial Narrow Intelligence (ANI)?

This is the most common form of AI that you’d find in the market now. These Artificial Intelligence systems are designed to solve one single problem and would be able to execute a single task really well. By definition, they have narrow capabilities, like recommending a product for an e-commerce user or predicting the weather. This is the only kind of Artificial Intelligence that exists today. They’re able to come close to human functioning in very specific contexts, and even surpass them in many instances, but only excelling in very controlled environments with a limited set of parameters.

What is Artificial General Intelligence (AGI)?

AGI is still a theoretical concept. It’s defined as AI which has a human-level of cognitive function, across a wide variety of domains such as language processing, image processing, computational functioning and reasoning and so on.

We’re still a long way away from building an AGI system. An AGI system would need to comprise of thousands of Artificial Narrow Intelligence systems working in tandem, communicating with each other to mimic human reasoning. Even with the most advanced computing systems and infrastructures, such as Fujitsu’s K or IBM’s Watson, it has taken them 40 minutes to simulate a single second of neuronal activity. This speaks to both the immense complexity and interconnectedness of the human brain, and to the magnitude of the challenge of building an AGI with our current resources.

What is Artificial Super Intelligence (ASI)?

We’re almost entering into science-fiction territory here, but ASI is seen as the logical progression from AGI. An Artificial Super Intelligence (ASI) system would be able to surpass all human capabilities. This would include decision making, taking rational decisions, and even includes things like making better art and building emotional relationships.

Once we achieve Artificial General Intelligence, AI systems would rapidly be able to improve their capabilities and advance into realms that we might not even have dreamed of. While the gap between AGI and ASI would be relatively narrow (some say as little as a nanosecond, because that’s how fast Artificial Intelligence would learn) the long journey ahead of us towards AGI itself makes this seem like a concept that lays far into the future.

Strong and Weak Artificial Intelligence

Extensive research in Artificial Intelligence also divides it into two more categories, namely Strong Artificial Intelligence and Weak Artificial Intelligence. The terms were coined by John Searle in order to differentiate the performance levels in different kinds of AI machines. Here are some of the core differences between them.

What is the Purpose of Artificial Intelligence?

The purpose of Artificial Intelligence is to aid human capabilities and help us make advanced decisions with far-reaching consequences. That’s the answer from a technical standpoint. From a philosophical perspective, Artificial Intelligence has the potential to help humans live more meaningful lives devoid of hard labour, and help manage the complex web of interconnected individuals, companies, states and nations to function in a manner that’s beneficial to all of humanity.

Currently, the purpose of Artificial Intelligence is shared by all the different tools and techniques that we’ve invented over the past thousand years – to simplify human effort, and to help us make better decisions. Artificial Intelligence has also been touted as our Final Invention, a creation that would invent ground-breaking tools and services that would exponentially change how we lead our lives, by hopefully removing strife, inequality and human suffering.

That’s all in the far future though – we’re still a long way from those kinds of outcomes. Currently, Artificial Intelligence is being used mostly by companies to improve their process efficiencies, automate resource-heavy tasks, and to make business predictions based on hard data rather than gut feelings. As all technology has come before this, the research and development costs need to be subsidised by corporations and government agencies before it becomes accessible to everyday laymen. To learn more about the purpose of artificial intelligence and where it is used, you can take up an AI course and understand the artificial intelligence course details and upskill today.

Where is Artificial Intelligence (AI) Used?

AI is used in different domains to give insights into user behaviour and give recommendations based on the data. For example, Google’s predictive search algorithm used past user data to predict what a user would type next in the search bar. Netflix uses past user data to recommend what movie a user might want to see next, making the user hooked onto the platform and increase watch time. Facebook uses past data of the users to automatically give suggestions to tag your friends, based on their facial features in their images. AI is used everywhere by large organisations to make an end user’s life simpler. The uses of Artificial Intelligence would broadly fall under the data processing category, which would include the following:

  • Searching within data, and optimising the search to give the most relevant results
  • Logic-chains for if-then reasoning, that can be applied to execute a string of commands based on parameters
  • Pattern-detection to identify significant patterns in large data set for unique insights
  • Applied probabilistic models for predicting future outcomes

What are the Advantages of Artificial Intelligence?

There’s no doubt in the fact that technology has made our life better. From music recommendations, map directions, mobile banking to fraud prevention, AI and other technologies have taken over. There’s a fine line between advancement and destruction. There’s always two sides to a coin, and that is the case with AI as well. Let us take a look at some advantages of Artificial Intelligence-

Advantages of Artificial Intelligence (AI)

  • Reduction in human error
  • Available 24×7
  • Helps in repetitive work
  • Digital assistance
  • Faster decisions
  • Rational Decision Maker
  • Medical applications
  • Improves Security
  • Efficient Communication
  • Prerequisites for Artificial Intelligence

As a beginner, here are some of the basic prerequisites that will help get started with the subject.

  • A strong hold on Mathematics – namely Calculus, Statistics and probability.
  • A good amount of experience in programming languages like Java, or Python.
  • A strong hold in understanding and writing algorithms.
  • A strong background in data analytics skills.
  • A good amount of knowledge in discrete mathematics.
  • The will to learn machine learning languages.


it’s not technology, it’s what you do with it

Latest News