Artificial Intelligence

Artificial intelligence (AI), the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings. The term is frequently applied to the project of developing systems endowed with the intellectual processes characteristic of humans, such as the ability to reason, discover meaning, generalize, or learn from past experience.

All but the simplest human behaviour is ascribed to intelligence, while even the most complicated insect behaviour is never taken as an indication of intelligence. What is the difference? Consider the behaviour of the digger wasp, Sphex ichneumoneus. When the female wasp returns to her burrow with food, she first deposits it on the threshold, checks for intruders inside her burrow, and only then, if the coast is clear, carries her food inside. The real nature of the wasp’s instinctual behaviour is revealed if the food is moved a few inches away from the entrance to her burrow while she is inside: on emerging, she will repeat the whole procedure as often as the food is displaced. Intelligence conspicuously absent in the case of Sphex must include the ability to adapt to new circumstances.

The ideal characteristic of artificial intelligence is its ability to rationalize and take actions that have the best chance of achieving a specific goal. A subset of artificial intelligence is machine learning, which refers to the concept that computer programs can automatically learn from and adapt to new data without being assisted by humans. Deep learning techniques enable this automatic learning through the absorption of huge amounts of unstructured data such as text, images, or video.


  • Artificial intelligence refers to the simulation of human intelligence in machines.
  • The goals of artificial intelligence include learning, reasoning, and perception.
  • AI is being used across different industries including finance and healthcare.

Weak AI tends to be simple and single-task oriented, while strong AI carries on tasks that are more complex and human-like. Things might have changed in the time


When most people hear the term artificial intelligence, the first thing they usually think of is robots. That’s because big-budget films and novels weave stories about human-like machines that wreak havoc on Earth. But nothing could be further from the truth. Artificial intelligence is based on the principle that human intelligence can be defined in a way that a machine can easily mimic it and execute tasks, from the most simple to those that are even more complex. The goals of artificial intelligence include mimicking human cognitive activity. Researchers and developers in the field are making surprisingly rapid strides in mimicking activities such as learning, reasoning, and perception, to the extent that these can be concretely defined. Some believe that innovators may soon be able to develop systems that exceed the capacity of humans to learn or reason out any subject. But others remain skeptical because all cognitive activity is laced with value judgments that are subject to human experience.

Applications of Artificial Intelligence

The applications for artificial intelligence are endless. The technology can be applied to many different sectors and industries. AI is being tested and used in the healthcare industry for dosing drugs and different treatments in patients, and for surgical procedures in the operating room. Other examples of machines with artificial intelligence include computers that play chess and self-driving cars. Each of these machines must weigh the consequences of any action they take, as each action will impact the end result. In chess, the end result is winning the game. For self-driving cars, the computer system must account for all external data and compute it to act in a way that prevents a collision.

Categorization of Artificial Intelligence

Artificial intelligence can be divided into two different categories: weak and strong. Weak artificial intelligence embodies a system designed to carry out one particular job. Weak AI systems include video games such as the chess example from above and personal assistants such as Amazon’s Alexa and Apple’s Siri. You ask the assistant a question, it answers it for you. Strong artificial intelligence systems are systems that carry on the tasks considered to be human-like. These tend to be more complex and complicated systems. They are programmed to handle situations in which they may be required to problem solve without having a person intervene. These kinds of systems can be found in applications like self-driving cars or in hospital operating rooms.

Four types of artificial intelligence?

Arend Hintze, an assistant professor of integrative biology and computer science and engineering at Michigan State University, explained in a 2016 article that AI can be categorized into four types, beginning with the task-specific intelligent systems in wide use today and progressing to sentient systems, which do not yet exist. The categories are as follows:
Type 1: Reactive machines. These AI systems have no memory and are task specific. An example is Deep Blue, the IBM chess program that beat Garry Kasparov in the 1990s. Deep Blue can identify pieces on the chessboard and make predictions, but because it has no memory, it cannot use past experiences to inform future ones.

Type 2: Limited memory. These AI systems have memory, so they can use past experiences to inform future decisions. Some of the decision-making functions in self-driving cars are designed this way.

Type 3: Theory of mind. Theory of mind is a psychology term. When applied to AI, it means that the system would have the social intelligence to understand emotions. This type of AI will be able to infer human intentions and predict behavior, a necessary skill for AI systems to become integral members of human teams.

Type 4: Self-awareness. In this category, AI systems have a sense of self, which gives them consciousness. Machines with self-awareness understand their own current state. This type of AI does not yet exist.

Artificial Intelligence and Machine Learning in Cybersecurity

World is an ever changing place. Contemporary world has revealed new notions such as Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning (DL). AL, ML and DL have the capacity of various uses including increasing the potential to increase the efficiency and output in multiple fields. Machine Learning is commonly known in the world of cybersecurity when it comes to general application of Artificial Intelligence. Artificial Intelligence, Machine Learning and Deep Learning share many traits which seem similar and are often confused with one another.

The main purpose and goal of Artificial Intelligence is to develop computer programs having the ability to achieve intelligent functions just as they are carried out by human brains. It cannot be said when the first ever programming idea related to Artificial Intelligence was formulated but it can be traced back to the late 1940s and early 1950s. One significant development in the world of Artificial Intelligence was the creation of LISP or list processing language by John McCarthy in the year of 1957. Then in 2016, Sophia, a programmed humanoid, was introduced to the world. Artificial Intelligence also has some day-to-day occurrences in our daily lives including speech recognition, mapping, finding best possible routes when travelling, smart phones and devices that can perform independently etc.

Machine learning is defined “as the ability (for computers) to learn without being explicitly programmed.” Machine Learning has the capability to learn from large amount of data available using algorithm that are man built to complete tasks and it can also be seen as a data mining since it processes large amount of data. There are two kinds of learnings that fall under Machine Learning; Supervised Learning and Unsupervised Learning. In Supervised Learning, computer is given parameters to equate the data whereas in Unsupervised Learning, computer does that comparison and finds relationship from the data available independently. One of the pioneer of Machine Learning, Arthur Samuel, stated in his 1959 IBM paper that “programming computers to learn from experience should eventually eliminate the need for much of this detailed programming effort.” Machine Learning programs independently improves basing upon old and new data with a little help of humans. Machine Learning helps in designing cybersecurity algorithms that flag the unauthorized and unnecessary access. It also helps in flagging the security risks if there is any breaching or hacking taking place.

Machine Learning shows great commitment in cybersecurity and Artificial Intelligence. Machine Learning has the ability to extend great help when it comes to IT or cybersecurity. Machine Learning can acquire results from the past existing data to recommend the appropriate responses and predictions. It can build profiles of the hackers and how they attempt to breach from previous data breaches. As per Amir Kanaan, as it expands its knowledge, it can start to make proactive recommendations on how to reduce risk. Also, the advantages of Machine Learning in security can help us in areas such as Anti-malware, Dynamic Risk Analysis, and anomaly detection.

According to Rob Sobers, some benefits of Machine Learning include:

Classification: Programs classify data based on predetermined parameters.

Clustering: For data that does not fit preset parameters, Machine Learning group’s data based on their similarities or anomalies.

Recommendations: Programs learn from past choices, inputs and associations to recommend approaches and decisions.

Generative frameworks: Based on past data inputs, programs generate possibilities that can be applied to data that had not encountered those specific inputs before.

Predictions: Programs forecast based on data sets and past outcomes.

Machine Learning can be very beneficial in case of cybersecurity because it can generate an alert when there is a data breach, theft or other attacks that can cause strain financially. Machine Learning also helps in minimizing the workload for security teams, decreases the risks of human error and cater the specific requirements. Although Machine Learning has benefits, it is not entirely invincible. Machine Learning and Artificial Intelligence are becoming an essential part in the world of cybersecurity to run the matters more smoothly and timely. It is still not clear if Machine Learning will complete take over the tasks that require human brain. Complete reliance on Machine Learning and Artificial Intelligence can cause a false sense of safety and security, which is why it is important for both humans and technology to work hand-in-hand to stand against ever powerful cybersecurity threats.

Electromagnetic Pulse: Weapon of Today

In contemporary world we are surrounded by the most sophisticated technology having the capability of controlling and monitoring finance, electricity, travelling and communications. United States carried out its last above the surface nuclear test in the South Pacific in 1962 and world was exposed to deadly side effects of gamma rays that are electromagnetic pulse. In today’s world possessing nuclear weapons other than deterring offensive enemy or self-defense is considered unnecessary. Now world is shifting to practical application of weapons for target engagement using hi-tech. Another product of hi-tech is Electromagnetic Pulse or EMP.

Electromagnetic Pulse is described as a weapon possibly intimidating to national security. EMP can be created by two traditional methods: microwave emission and overhead nuclear burst. High power microwave electromagnetic energy can be produced as a direct pulse via special electrical equipment that transforms battery power into intense microwaves that are very damaging to electronics falling in much smaller area. Electromagnetic pulse is an instant electromagnetic field that is produced in the atmosphere by the radiation and power of a nuclear explosion. The damage to electrical equipment via EMP also covers wide area but it depends upon device’s design and altitude of the burst. The obligatory contrivance for the production of EMP is ionization of air molecules by gamma rays generated from nuclear detonation.

Electromagnetic Pulse of high altitude and High Power Microwave technology have advanced to the extent where Electromagnetic bombs are becoming viable. EMP is not radioactive, as said, it is a pulse that is formed as a side effect of electromagnetic or nuclear bomb detonation. It is also claimed that EMP has no direct side effects on living organisms. It is mainly used to everlastingly or briefly inactivate electrical and electronic equipment because electromagnetic energy travels at the speed of light. Most of the electrical systems are controlled by semiconductors and they fail while becoming in contact with EMP. Failure of semiconductors can potentially terminate railway, industrial, phone, water and power system.

EMP has the ability to destroy or burn out specified path range electronic equipment. EMP weapon has the ability to offer an edge in army combat and it can lead to very lethal affects in the battlefield. Developed EMP has range covering meters and kilometers. Reach of an EMP bomb depends upon its size and output power source. US Air Force Laboratory has developed an EMP called Counter-electronics High-powered Microwave Advanced Missile Project or CHAMP. CHAMP is capable of bursting high frequency energy destroying the adversary’s data and electronic system. EMP can be a device as small that it can fit in a regular sized briefcase. These bombs are thought to be developed to deter or to defeat an enemy with any nuclear confrontation. The smallest EMP devices are powered by AA battery and have the ability to deprogram a circuitry in a computer system frim 15 meters away. Electromagnetic pulse weapons are a lot larger in scale than microwave emission pulse. The technology used for microwave pulse is of such lower scale that non-state actors or organizations can acquire or make it to damage the computer devises.

Other States like Russia and China are also in a race of developing EMP weapons capable of destroying electronic equipment and systems. According to a Russian News Agency, TASS, the Russian EMP weapon, known as EMP Cannons, produces a high beam of electromagnetic pulse that can travel up to 10 km against aerial targets. TASS further explained that airborne targets can be destroyed from the range of 10 km because their electrical system burns down due to the heat and electromagnetic energy exposure. Russia aims to install EMP cannons in unmanned version of Russian sixth generation fighter jet because EMP cannons cannot be installed in an aircraft with a piolet due to the risk high EMP energy signals. USA has been accusing Russia for exposing several American soldiers and diplomates, inside and outside Russia, to electromagnetic waves silently. Many cases of sharp pain in head and throwing up have been reported which was later named “Havana Syndrome.”

There are no compelling proofs that Russia is behind exposing American diplomates to such affects. USA is still adamant by comparing situations to 1953-79 when Soviets barraged US embassy in Moscow microwave radiation leaving American diplomate’s white blood cells abnormal and many adverse health issues. USA claims that fire swept through the block right opposite to US embassy in Moscow and there were no radiations detected. By July of the same year, microwave radiations were detected again and another fire broke out in the same block. There are two explanations given by the USA that Russia has been using EMP as a weapon against them for years: one notion is that Russia has been using microwave to listen to American devise installed in the embassy or that they were used to freeze or burn out American electrical devise. Despite all the theories and accusations, it is not proved that Havana Syndrome is caused by electromagnetic energy radiations.

China has also been recently accused of using microwaves against Indian soldiers in the mountains range of Himalaya. The reports suggest that healthy Indian soldiers suddenly started feeling weak and violent vomiting. According to professor Jin Canrong at Renmin University in Beijing, China used microwave energy and exposed Indian soldiers to high frequency electromagnetic pulse which increased the heat in their body, leaving them feel vexed and irritated. By using that technique China turned the Himalayan hilltop into a giant microwave threatening the lives of Indians soldiers to be cooked alive from the inside. It made Indian solders to leave the premises of the hilltop unprotected for Chinese soldiers to occupy without even releasing a single bullet. India has dismissed the news by calling it “fake.” It has also been reported that China has “first strike” capability to melt and burn down and entire US power grid with the use of EMP radiation.

It is believed that the effects of being exposed to EMP energy are not long lasting and wear off in a span of weeks. Though EMP weapons require hi-tech and advanced power system, they are still less expensive than producing aircraft carriers, fifth generation fighter jets and nuclear bombs. EMP is not just a dream or a movie plot, it is a reality. EMP weapon can take down an entire State or a specific area by frying every electrical system and not shedding a drop of blood.