How Artificial Intelligence is Shaping our Future

Posted by Pranav Kakhandiki, Edited by Anika Asthana| Aug 14, 2018, 6:00:00 PM


          AI, which stands for for Artificial Intelligence, is a fascinating new field of technology. A sub-field of AI known as machine learning, can automate mundane processes, which gives us more time to focus on more important tasks. Because AI is so new, however, it is hard to predict any benefits or potential drawbacks it might present.


          To properly understand AI’s impact, it is important to understand how it works. It is important to distinguish between the two types of machine learning: supervised and unsupervised. Supervised learning uses input-output pairs to train itself on how to perform a specific task. In other words, supervised learning programs train themselves on data provided by the user. For example, if someone wants to predict the cost of a 1500 square-foot house, we would use other data points relating size and cost. If we know the cost of houses which are 500, 750, and 1000 square feet big, then we can use a technique called linear regression, which draws a best fit line, to estimate the cost of a 1500 square foot house. To calculate how close a program gets to predicting values using linear regression, we use the cost function, defined below:

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The Cost Function


          HØ(x(i))  is the hypothesis function, defined as: Ø1(x)+Ø0, our linear regression model, where Ø1 and Ø0 are the parameters(in this case Ø1 defines the slope of the line, and Ø0 is the y-intercept). y(i) is the actual y value, and m is the total number of (x,y) data-points. Essentially, we are adding the squares of the differences between our hypothesis and the real values, then dividing by the total number of values. The goal of any supervised machine learning program is to minimize the cost function, thus minimizing our overall error in our approximation. The ½ at the beginning is only there to cancel out when the derivative of the cost function is taken, and provides no purpose other than convenience of calculation.

          Unsupervised learning trains a machine without data. But how can any machine learning program predict the size of a house with no other data to estimate with? Unsupervised learning doesn’t predict or approximate with numbers, but rather is used for clustering data. For example, an unsupervised learning program could be able to group articles based on similarity and topic. Artificial Intelligence robots use one or both of these techniques to complete a given task. Semi-supervised learning is the middle ground between the two tactics.

Supervised v.s Unsupervised Learning

          Now that we know the basics of how a simple machine learning algorithm works, we can address its benefits and drawbacks. AI could shape product manufacturing, increasing efficiency and throughput in production. Moreover, AI frees up humans to do what robots can’t do: be creative. Automating simple processes allows employees to think about how they can improve products instead of sorting through spreadsheets.  There are truly endless options with how far AI can go, ranging from automatizing simple tasks like grading tests to performing complex procedures like surgeries. It can even be used to create bots that are similar to humans. Although efficiency and product production can be improved through Artificial Intelligence, there are drawbacks to automating simple tasks, such as the jobs of industry workers. Automating minimum-wage jobs can possibly harm the economy, as it takes crucial sources of income away from a population afflicted with poverty. Though more job positions will open up at AI companies, the total number of jobs might decrease, possibly harming the economy.

          Progress in machine learning has experienced a massive boom in the last few years. Companies are scrambling to create the next bot and automating tasks to make our lives more convenient. Al can also be used in the medical field, assisting doctors diagnose patients. Almost all technologies, however, come with both positive and negative effects. With so much power vested in AI, it’s our responsibility as a human race to decide what we do with it.



Posted by Pranav Kakhandiki, Edited by Anika Asthana| Jul 18, 2018, 9:00:00 PM


        Gene editing, a field in synthetic biology, is a rapidly emerging subject in today’s world. There are a whole world of possibilities, ranging from creating new organisms, to curing diseases previously thought to be un-curable. CRISPR-Cas9 is a riveting new gene editing technology, standing for Clustered Regularly Interspaced Short Palindromic Repeats. The “palindromic repeats” are small pieces of viruses typically found in bacteria. Cas9 is an enzyme which can cut apart DNA allowing scientists to edit the human genome.

        To truly understand when and why CRISPR can be used, it is important to understand how it works. With so many other gene editing tools, such as ZFNs and TALENs, CRISPR is popular for a reason. Unlike other methods, CRISPR does not need to be paired with separate “cleaving” enzymes. In other words, the Cas9 protein uses small RNAs to cleave DNA, as opposed to using separate enzymes. CRISPR is a “knife” that can cut DNA by matching up a guide RNA to the DNA and then cutting it. After the DNA is cut, the cell loosely “glues” the strands of DNA back together.


        So how does Cas9 enzyme know which part of the DNA to cut out? The CRISPR-Cas9 complex scans the DNA for Protospacer Adjacent Motifs (PAMs), which are short DNA sequences. CRISPR, then attached to the PAM, unzips the double helix. The Cas9 protein then cuts the DNA in two, successfully eliminating the specific piece of DNA.


        Now we know how CRISPR cuts out DNA, but what can we do with it? CRISPR can be used to make tiny genomes in the base pairs that make up the genome, which may end up being the difference between life and death. Many major diseases are caused by one just one mutant base pair in the genome, such as sickle cell anemia, cystic fibrosis, and muscular dystrophy. CRISPR can cut out the “bad” DNA, and insert the correct sequence of base pairs. Other uses for CRISPR include mutating animals, potentially making them stronger and faster than biologically standard.  

        So if CRISPR is so great why don’t all doctors use it? CRISPR is fairly accurate, but can sometimes cut out the wrong strand of DNA, creating its own mutation. So as of present day, CRISPR isn’t quite reliable to be tested on humans. Many years into the future, however, technology will not be the factor holding us back from using synthetic biology.

        With so many possibilities and so much new technology, many ethical dilemmas arise. Should people be informed whether they will inherit a disease fifty years later in their life? Can we create new animals to do work for us? Can we give ordinary humans superpowers with one simple operation? Although CRISPR is a new and exciting technology, one must consider the ethics behind such an enormous jump in scientific advancement.



        Ever since 1979, synthetic biology has been an emerging field in science,  allowing us to sequence entire genomes and change genes. The ethics of this field, however, can be questioned, as it allows us to potentially create new organisms, or change them beyond what is natural. This subject can be viewed both positively and negatively. One one hand, this practice includes removing environmental contaminants, creating safer and cleaner air, diagnosing and monitoring disease in eukarya, creating enzymes for biofuels, and developing new drugs and vaccines.

        However, a multitude of negative effects present themselves. One harmful effect of the use of synthetic biology is the creation of new organisms. New organisms could potentially destroy the ecosystem, killing off native species and ruining the environment. Another is bioterrorism, the intentional release of biological agents such as viruses, bacteria, or toxins using CRISPR to intentionally create harmful viruses would have an adverse impact on our world, as it provides weapons stronger than ever before. Although both of these detrimental uses of CRISPR can negatively affect our world, the questionable ethics of gene editing doesn’t stop there. New technologies are allowing scientists to map the entire genome of a human, letting them predict what diseases one can inherit. Although it sounds phenomenal on the surface, the potential action creates a personal conundrum. The question is: do we want to know if we will inherit a disease later in life? If we know we will inherit a non-curable disease such as Parkinson’s, will knowing this information cause us to live our lives differently? So despite the numerous benefits of CRISPR, the massive negative potential of such a technology forces humans to decide what to do with the power vested in gene editing technology.

        CRISPR is a fascinating technology with incredible potential. Using it, we can achieve feats thought to be impossible, making significant advances in the field of synthetic biology. With so much potential, however, much harmful potential presents itself. We can cure diseases, yet will the same technology, create a disease even worse. We can create a safer environment, but can it destroy in a heartbeat with the creation new organisms. With so much potential in gene editing, one question stands out: What will we do with it?


Black Holes

Posted by Pranav Kakhandiki | Jun 20, 2018, 11:00:00 AM


        What exactly is a black hole? Is it a type of star? How big are they? Why are they called “black holes”?

        A black hole is a region of space which has such an intense gravitational field, that not even light can escape it. They are some of the strangest and most interesting objects found in space. Albert Einstein was the first person to predict the existence of them, using his general theory of relativity. The name “black hole”, was given by John Wheeler in 1967, although the first one wasn’t discovered until 1971.



        So how do black holes form? They are created when center of a massive star collapses. This happens when the gravity on themselves is greater than the external pressure caused by temperature. Not all collapsing stars turn into black holes, however. A black hole is determined by the Schwarzschild radius. If the radius of the collapsed star is smaller than the Schwarzschild radius, the it is officially considered a black hole. The event horizon is defined as “the point of no return”, and is a sphere with a radius the same size as the Schwarzschild radius. Once an object passes the event horizon, it can’t escape the gravitational pull of the black hole. Technically speaking, anything can become a black hole of it becomes dense enough. For the Earth to turn into a black hole, it would have to be compressed until it had a radius of 8.7 millimeters! At the center of a black hole, there lies something called a singularity. A singularity supposedly has zero size and infinite density. If an object were to fall into a black hole, then as it approached the singularity, it would become “spaghettified”, due to increasing gravitational pull on different part of the object.


Escape Velocity

        The escape velocity of an object is the minimum velocity which an object needs to escape the gravitational pull of a mass. The equation of escape velocity can be derived by setting the equation of Kinetic energy equal to the gravitational pull of the mass on the object. Doing this, we arrive at the following equation:


        If the mass of an object was big enough so that the escape velocity exceeded the speed of light, we get a black hole. This is how they got the name “black hole”, as not even light can escape their gravitational pull!

Temperature of Black Holes

        What is the temperature of a Black Hole? Is it absolute zero? Are they infinitely hot? To answer this question, we must consider interactions between particles and antiparticles. An antiparticle is defined is the “opposite” of a particle, and is the antimatter counterpart of a particle. Think of it as the difference between an electron and a positron. Particles and Antiparticles are created in random places within the black hole, due to Heisenberg’s uncertainty principle.


        They often “cancel” each other out, but sometimes the pair separates, making the black hole seem like it’s radiating. This radiation is can be used to determine the temperature of a black hole, which is defined by the following equation(Where ‘Kb’ is Boltzmann’s constant, and ‘h’ is Planck’s constant):


Strange Evaporation Paradox

        So if a black hole really radiates, then wouldn’t it lose mass? And using the equation we derived above, as temperature is inversely proportional to mass, then the temperature would increase. If temperature increases, then the black hole would radiate even more, losing more mass. This is the strange evaporation paradox. Strange evaporation doesn’t actually occur, as it would allow black holes to exist for a limited amount of time. It doesn’t occur because the temperature of space near black holes is greater than that of black holes. This allows the space near the black hole to add energy to the black hole, which then adds mass(via E=mc^2).

What defines a black hole?

        Two points define a line. Three points define a plane. What defines a black hole? In other words, what quantities of a black hole would you have to know to figure out exactly what it looks like? Three quantum numbers define a black hole: M, J, and Q. These stand for Mass, Angular Momentum, and Charge.

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Welcome To TheRealSciBlog!

Posted by Pranav Kakhandiki | Jun 13, 2018, 6:00:00 PM


     Welcome to TheRealSciBlog! Have you ever had an itch to learn something new? Do you want to know the latest science news? Are you interested in learning about Black Holes, Artificial Intelligence, Gene Editing, or the myriad of other cool new science topics out there? TheRealSciBlog covers everything, ranging from astrophysics, to microbiology, to Machine Learning! If you’re interested, subscribe to this blog to receive an email whenever a new article is posted. You won’t regret it!