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Exponentiation 👉 Exponentiation is the process of multiplying a number by itself a given number of times. 👉 The products of exponentiation become large quickly (264=18,446,744,073,709,551,616) which can consume available memory quickly.   👉 Fortunately, the process can be broken up into small problems that better fit into the memory of a microprocessor. 👉 The modulus operator takes care of overruns.

Modular Arithmetic 👉 The modulus operator determines the remainder left after division.  👉 Imagine cutting 5-foot lengths of rope from a 103-foot length until you’ve run out of rope. 👉 The modulus operator determines how long the last piece of rope is—in the case of the example above, 103-feet mod 5-feet = 3-feet.  👉 Each piece of cut rope is identical to the last, and if you were handed the left-over rope, it would be difficult to impossible to determine the number of pieces of rope that preceded it.

The Diffie-Hellman Exchange in Embedded Cryptography Whitfield Diffie and Martin Hellman came up with a way for the sender and receiver of private messages to generate their shared secret by transmitting numbers in plain sight using modular arithmetic and exponentiation.

WHAT IS THE HYPERLOOP? 👉 The Hyperloop concept as it is widely known was proposed by billionaire industrialist Elon Musk, CEO of the aerospace firm SpaceX and the guy behind Tesla. 👉 A one way trip between San Francisco and Los Angeles on the Hyperloop could take about 35 minutes. 👉 Musk’s Hyperloop consists of two massive tubes extending from San Francisco to Los Angeles.  👉 Pods carrying passengers would travel through the tubes at speeds topping out over 700 mph.  👉 For propulsion, magnetic accelerators will be planted along the length of the tube, propelling the pods forward. 👉 The tubes would house a low pressure environment, surrounding the pod with a cushion of air that permits the pod to move safely at such high speeds, like a puck gliding over an air hockey table.

Hyperloop Transportation  👉 Dreams never die, however, and the fantasy of futuristic transportation is very much alive right now as exemplified by a concept called the Hyperloop. 👉 While it’s not as mind-shattering as a teleporter or as fun as a personal jetpack, the Hyperloop could revolutionize mass transit, shortening travel times on land and reducing environmental damage in the process.

👉 These silicon nanorobots move as their bilayer legs are actuated by a few hundredmillivolts, which are generated from a laser shining on their integral solar cells.  👉 These walking nanobots are both wireless powered and controlled using embedded silicon photovoltaics.  👉 The robots “walk” using a new type of voltage-controllable electrochemical actuator fabricated from nanometer-thick membranes on a platinum base.  👉 Their bodies are rectangular skeletons of glass about 10 µm by 70 µm and topped with a layer of silicon.  👉 The legs, about 100 atoms thick, are built as two layers, comprising platinum applied via atomic layer deposition topped with titanium. 👉 The researchers also etched electronic-control components and either two or four silicon solar cells into the body.

Silicon Nanobot Swarms will be coming soon 👉 Swarms of nanorobots, usually referred to as nanobots are the stuff of science-fiction movies. 👉 They’re getting closer to reality as tiny, insect-like electromechanical “creatures”, being created and evaluated. 👉 Wirelessly powered and controlled using silicon photovoltaics, a research team employed a voltage-controllable electrochemical actuator to create their “walking” nanorobots. 👉 Taking advantage of IC-production techniques, they can create over one million functional units in a single production pass on a single 4-in wafer..

Points to keep in mind before Learning Machine Learning 👉 Probability and Statistics - Gets used a lot, especially in classification. A good understanding of conditional probability and Bayes theorem is an absolute necessity. 👉 Linear Algebra - Required more from an implementation standpoint. Most procedures are best implemented as matrix and vector operations instead of loops. You can use a lot of nested for-loops to achieve the same results as matrix operations but that is not computationally optimum. 👉 Optimization - Almost all ML algorithms essentially boil down to a convex optimization problem - be it linear/logistic regression or neural networks or SVMs or tree-based methods. It really helps to have some basic understanding of optimization theory.  Note: Optimization necessarily requires a strong grasp of differential calculus. 👉 Programming skills - You don't need to be an expert developer but basic coding skills are a must. Pick up a commonly used language like Python to get started. Python is easy to learn and has a lot of open source packages for machine learning. It also integrates well with Big data tools like Hadoop and Spark (PySpark). These tools may not be needed for beginners but they will be useful later when you deal with massive datasets.  Andrew Ng uses MATLAB in his Coursera course. It is extremely powerful but very expensive at the same time. The open source free equivalent OCTAVE is simply not as good and somewhat painful to use. It may be useful to know that a majority of the machine learning community uses Python. So you would be recommended learning that. The subsequent development of prototypes into products usually happens in more traditional languages like C++ or Java. 👉 A good, well-maintained computer - Don't underestimate the importance of this. It may not matter in the beginning but lack of raw computation power and RAM can be frustrating while working with bigger datasets and computationally intensive techniques like neural networks. Maintain your computer well. Always ensure that there is no accumulated dust inside the system and its cooling unit. Dust can significantly affect the system's performance and result in longer training times of algorithms as well as overheating of the computer.

According to Harvard Business Review, "The effects of AI will be magnified in the coming decade, as manufacturing, retailing, transportation, finance, healthcare, law, advertising, insurance, entertainment, education, and virtually every other industry transform their core processes and business models to take advantage of machine learning.”

Why is Artificial Intelligence important? 👉 Artificial intelligence systems are critical for companies looking to extract value from data by automating and optimizing processes or producing actionable insights. 👉 Artificial intelligence systems powered by machine learning enable companies to leverage their large amounts of available data to uncover insights and patterns that would be impossible for any one person to tease out, enabling them to deliver more targeted, personalized communications, predict critical care events, identify likely fraudulent transactions, and more.

The typical definition used for AI looks something like above figure.. "An AI is a computer system that is able to perform tasks that ordinarily require human intelligence.These artificial intelligence systems are powered by machine learning. Many of them are powered by machine learning, some of them are powered by specifically deep learning, some of them are powered by very boring things like just rules."

What exactly is Artificial Intelligence?? Artificial intelligence is a conglomeration of concepts and technologies that mean different things to different people – self-driving cars, robots that impersonate humans, machine learning, and more – and its applications are everywhere you look. 

The argument in favour of AC current 👉 According to Charles Dalziel experiments on men and women, muscles contraction is continuous in case of an electric shock with DC current. 👉 Whereas in the case of AC current, a person experiencing electric shock undergoes a series of muscle contraction. Series of muscle contraction causes very severe damage to the muscles. 👉 Due to the capacitive behaviour of the skin coming in contact with the current carrying conductor, more current can pass through the body if the voltage is rapidly changing. 👉 Studies have shown that twofold of increase in the voltage increases sevenfold increase in the current. 👉 DC current “let-go” threshold is higher than the AC “let-go” threshold. 👉 More DC current is required to produce a similar effect as of AC current. 👉 With all these, it can be summarised that AC Current is more dangerous than DC Current. 

👉 Which current is more dangerous, AC or DC? There are arguments in favour of both AC current and DC current.  👉 The argument in favour of DC current Victims who have experienced the electric shock with DC current says that they are unable to pull their hand back because DC current flows continuously. This effect is similar to an electric doorbell supplied with DC current. Hence, it is believed that the DC current shock is more dangerous. Whereas, in the case of AC current, the person experiencing the electric shock can pull their hand back as the current goes to zero. Hence, it is believed that the AC current shock is least dangerous than DC current.

👉 Why does the Human body feel an electric shock? The current penetrates inside the body through the skin. The outermost layer of skin epidermis is composed of protein material called keratin. Keratin offers the highest resistance to the passage of electricity. After the epidermis layer, we have sweat glands and then blood vessels. These sweat glands and blood vessels constitute of various ions, which are a good conductor of electricity. Hence, blood vessels and sweat glands offer low resistance to the passage of electricity. 👉 How current reaches and travels through the body?? The outermost layer of skin epidermis acts as a dielectric, the internal sweat glands and tissues acts like one plate of capacitor and metal piece carrying electric current acts like another plate of the capacitor. Due to this capacitive-effect, current passes through the body. Rapidly changing voltage allows more current to pass through the body.

👉 Time duration An electric shock with a small amount of current say; 0.3 milliamperes can also cause painful effect if it is held for the longer duration. 👉 Body Resistance The resistance offered by the wet body to electric shock is less as compared to the dry body.

The path of current The current passing from the right hand to the right leg can be painful. But when it passes from right hand to left hand through the heart may cause ventricular fibrillation. This condition is usually fatal.

Which Current Is More Dangerous, AC Or DC? The amount of current For example, an electric shock with an alternating current of 15 to 20 milliamperes can be extremely painful. However, an electric shock with 100 milliamperes may cause death.