#Infinite_Powers: The_Story_of_Calculus-The_ Language_of_ the_Universe - #Steven_Strogatz - Review

     Often, the public thinks that scientific breakthroughs happen when lone geniuses discover something new, but in reality, discoveries occur when people improve upon the work of others. In ‘Infinite Powers’ Strogatz traces the methods used by Archimedes and moves on to Newton and Leibniz, who refined the use of calculus. Along the way, with plenty of illustrations and interesting insights we get to know about contributions from Fermat, Galileo and Descartes. This apart the contributions of Indian, Arabic, and Chinese mathematicians is also included, and the 'Infinite Powers' continues on to Fourier, Katherine Johnson and Sophie Germain.

    We even get to see how calculus is being used today to treat HIV patients, to create microwaves, and help the 787 fly. The Infinity concepts start with Pizza proof – based on radius, if the one with larger radius is suitable for getting more of it (One 18-inch pizza or Two 12-inch, which is greater?). Well, the one 18-inch has more pizza! This is shown in the light of a curvy top having a length equal to half the circumference - C/2.  So, a parallelogram made of inverted cuts will be flatter if the number is more (infinite) Then A=R*C/2; 1/3=0.333 and the discussion on infinity thus continues.

In the following passages, important mentions of the book are listed in the order of chapters.

    Infinite polygons have flatter outcome – For a circle where the number of polygons take the denominator, like 6/0.1=60 or 6/0.01 is 600 (6 being constant) it would be indicative that smaller the number (polygons) bigger is the answer. As the denominator approaches zero the answer becomes bigger and bigger so that we cannot divide by zero any more to avoid a value going big!

    Likewise, Zeno’s paradox carries a similar concept. Every single step you need to talk would require a half of that step so that it can be expressed as: 1+0.1+0.01+0.001 +….=1.111 sec. This is equated with Achilles concept where it would take 10+t to catch-up a tortoise (t is time).  Zeno meets Planck’s length root h/C³ (10^-35m). If one takes a large possible distance – say diameter of the Universe - and divide by smallest possible distance (h), the most one would need to express becomes obvious.

    iPhone tracks the distance covered while walking using calculus – length of the stride multiplied by the height of the person is the distance travelled (in km). Similar idea is applied to calculate circumference of each step which is a fine straight line; pi=C/d.

    Many circle-ellipse-parabola drawings and segments are found in the third chapter of the book. For instance, the Quadratic parabola = 1+1/4+1/16+1/32, illustration was intuitive. An animation for facial surgery and Avtar’s (movie) face carry great level of polygonal details, and this became extravagant when this was the first instance to use polygon for creating faces. Use of rotating screw for propelling goes back to Archimedes.

    Laws of motion: Knowledge of what comes from a moment into existence and then perishes – Plato on objective geometry. The apparent position of the stars -parallax - finger shifting sideways when you view with an eye closed – Galileo, Copernicus, Aristotle and Ptolemy get due credits for using calculus in letting us know where we are weighed up in the Universe.

    Water clock invention was also based on calculus and the law of odd numbers gets a mention:1+3+5+7=16 which is 4 squares (4²) likewise, 1+3+5=9 which is 3 squares (3²). This concept is explained diagrammatically with good figures.

        Swings take same amount of time and only the speed varies! This was first checked by using Chandeliers in a Cathedral. This was later confirmed in the case of stars and our own Earth which has an elliptical orbit thus getting to roll speeder at the Perigees! Kepler who had damaged vision and hands due to smallpox, did works for establishing laws of planetary motions. Over elliptical orbits equal areas cover equal times, so planets have to move faster at places thus do not have constant speeds. The closer they get to the sun the faster they move.  T²/A³ is same for all planets – T is the time, and A is the average distance from the sun. Thus T²=A³ for Venus it is about T² 0.378 and A³=0.378.

Latitude can be ascertained by looking at the Sun or Stars, but longitudes have no counterpart. Galileo helped solve it and found that fifteen (15) degree longitude translates to 1000 miles at equator – Navigation by Huygens in creating a position of the pivotal point amidst a traverse used the concept of Calculus.  GPS uses at least 4 of the 24 satellites (orbiting at 12000 miles over head) for this purpose – Time received vs time transmitted in GPS would not be possible without calculus. Wireless or GPS to atomic clocks that use Cesium atoms use calculus. 

    Dawn of differential calculus discusses the aspect of Algebra meeting geometry. For instance: An XY plane expresses relationship between two parameters and a simple example includes number of slices taken vs calories consumed with a bread; thus Y=200X.  Through equations shapes are arrived at and Descartes and Fermat used this concept in studies leading to optimization of how to do things in the best possible way. This way designing of boxes to stuff as much gold as possible is described using a simple geometry in metric values:  10x10x25=45 (adding boxes) or 10x10x25 = 2500 (getting volume) but in the place of above if 15x15x15 size is used, it might give a volume of 3375 which is better room compared with 2500 (which means change is geometrical parameters for getting best volume).

    Fermat helped FBI which had millions of records of fingerprints storing and retrieving them through calculus - quite similar to JPG and MP3 formats retrieval using the algorithm. This chapter also includes the concept of bending of light that helped Snell arrive at his famous formula for refractive index.

    In Crossroads it was a pleasing aspect to see that a Function of function is power function.  And thus, an Exponential function would help one arrive at how bacteria multiply. Likewise, Logarithm is used for non-round numbers, and this enables us to write any positive number as powers of ten. Exponential growth and decay mechanism, similarly, use the same concept and is applied to reduce noise off a microphone when it picks up the sound of its own speaker. This is the same with nuclear chain reactions.

    In a further explanation on the Y and X factors the author clearly explains what dy/dx actually mean; for instance, it is (-velocity) that is rate of speed. Dy/dt is acceleration on a graph of distances and against time for a moving car the slope is indicative of a car’s speed – universal rate.  Area under the curve is important factor.  Linear function of the constant rates for instance in the case of slice, 400 calories/2 slices is 200 calories/slice. Many aren’t aware of using calculus dy\dx curves for velocity which can give distance covered. 

    Infinitesimal piece of curve as parabola helps us to understand a couple of caveats about derivatives. A curve with V shape is exampled with a sharp corner at one point and when we zoom into it, it will look like a corner. However, if it is a curve, it might not look like a corner.  Derivative as rates of change of day length help us to know how much extra sunlight a year can be obtained. Usain bolt Running style and slowing down near the end point leading to losing the first place is an example of this derivative application. 

    Leibnitz introduced the word calculus which means small stone. Incidentally, Newton and Leibnitz had these calculi (stones) in bladder and kidney, and it is written that the former died of this stone in bladder.  Integration is global operation instead of microscope we are using telescope and peering far off into the future (past?). The concept of pi gets a cue - 3.14 corresponds to 3+10⁰+1(1/10)¹ + 4(1/10)².   

    Mathematician from Kerala solved power series related to cosine and sine. Jyestadeva and Nilantha attributed the set to Madhava (1350-1425) in what is Kerala school of Mathematics and Astronomy today. Newtown had mashed up work of Greeks, Islamic Algebra and French geometry for arriving at infinity principle.

    Fictions of the mind: Infinitesimals supposed to be the tiniest number, smaller than everything but greater than nothing! For instance, 2³ is 8, but (2.001)³? Algebra has answers for that; x+dx may be used to get at (x+dx)³ or using Pascal’s triangle it can be arrived at 8+12 dx+6 dx² + dx³.

    Differentials can also be used to describe the fundamentals of the calculus; Upshot of dA=ydx=f(x) dx. Altimeter for measuring the altitude lot of number fractions illustrated with a grand sketch.  The author goes on to justify that finding HIV with assistance from calculus dV/V=-cdt was possible with greater accuracy based on the above principles. Similarly, estimation of virus mutation (at every genome) was also done using calculus.

    The calculus comes to aid in describing the Universe.  Planck, Einstein, Bohr, Dirac, and Heisenberg used calculus in all their calculations. With statistics initiating the estimation of gravity using F=ma, Moon’s acceleration was compared to the acceleration of the falling bodies on Earth and with that of Galileo’s experiment. It was differentiated by 60² according to the inverse law prediction. Moon was 60 times farther from the center of the Earth. Known as Two-body problem, the irregularities in the orbit of Uranus suggested an unknown planet (calculus) and using astronomy it was proved as ‘Neptune’.

    Katherin Johnson of NASA used calculus to predict the position of moving space crafts and to bring back John Glenn, the first American to orbit the Earth. NASA has a building named after her! 

    A bowl of soup is a discrete collection of molecules all bouncing erratically. Then, if you think the soup as continuum using x,y,z for the given point at temp T, partial differentiation makes ordinary differentiation equation a child’s play.  Pejorative is using art of differential equation that depend on just one variable.

        The final chapter has talks about the flights inspired from kites and birds. Dreamliner of Boeing applied Mathematics and Calculus to anticipate how the airplane’s wing would flex when working at 600 miles an hour - avoiding aeroelastic flutter, a nastier version of venetian blinds. Marking waves, standing, sinusoidal, Fourier series and String theory (vibration burst out of some of sine waves), and overtones, all get through this application of calculus.  Appearance of patient after facial surgery, flow of blood through artery, rumbling of ground after earthquake etc. all use the concept of calculus.

    A derivative of sine wave is another sine wave shifted by a quarter cycle (for other waves it gets distorted), so Sine wave is always efficient. Chaldini Patterns in guitar gets a mention too.

    Microwave ovens which used microwaves during world wars as Magnetron for detecting signals can be used to calculate the speed of light. ‘Frequency’ of vibrations (listed on the door frame of ovens) multiplied by ‘Wavelength’ can give that! (2.45 billion cy/sec into 12cm wavelength is close to the speed of light = 29.4 billion cm/sec). Percy Spencer had placed peanut cluster besides these Magnetrons, and he found later that it was like cooked one leading to the discovery of heating using MW. It was later tested with eggs.  Calculus provides the analysis in CT and brain imaging.

        The Future of calculus would be dealing with application to biology over writhing number of DNA. The diameter of typical nucleus is about 5 millionth of a meter and is 400,000 times smaller than DNA! That has to fit inside this smaller!! Not only this the alignment or arrangement is so neat that the DNA copy (multiplication) is flawless!!!

    Non-Linearity is a factor that is solved by Calculus. For instance, if you listen to your favourite songs again and again, the same pleasure is not doubled as cause and effect are proportional.

    Chaos over contour maps is discussed in detail followed by role of computers in getting Artificial Intelligence to the fore. But the eye-catching postulate of this book is when the author mentions Quantum Electron Dynamics. QED merges Maxwell’s theory of Electricity & Magnetism with Heisenberg’s & Schrodinger’s Quantum Theory and Einstein’s Special relativity, which turns out to be a pleasant aspect when you close the book and imagine how we all are enjoying this merger!

#Artificial_Intelligence - A Guide for Thinking Humans - #Melanie_Mitchell - Review

As titled, the entire book is an optimal guide for all thinking humans.  The author begins the book with a sketch of the history of AI research from its birth in the 1950s, and outlines its key figures and significant ideological branches. These are broadly classified as symbolic (conscious reasoning) and sub-symbolic (sub-conscious learning) with the latter being biologically inspired structures which learn patterns and rules via lots of data.

     AI is a technological endeavour, and like other big sci-fi dreams - deep space travel, cheap clean energy, trans-humanism - there is an enormous gap between our current capability and our vividly imagined end point (with most registering it as ‘fear’). It's a gap that's easy to dismiss while breathlessly fretting over superintelligence and singularities, but that gap is filled with some extremely difficult challenges that we currently have little idea how to approach, let alone solve. That is why, probably, data sets and data analysis is to the fore in all branches of science and technology.

 The author comes out with various examples of the data sets and training basis for the machines. (and the book is full of illustrations as well). We have heard about ‘Big Data’ but never realized that this would end up with such an extended benefit. It is perhaps for this reason that any data in general and scientific one in particular is being accepted for publication by most publishers. Earlier, this used to be the same data that would be rejected citing no novelty or creativity in the matter. If you have a repeat data the caveat for its publication would be a geo-tag (as the project would be new for that place and the results vary, credibly).

Here is the brief summary of the various sections in the book, rather guide:

 # The first and the simple start is ‘definition’ - “Define your terms or we shall never understand one another”. IQ which is measured in single scale can thus be differentiated with various dimensions – emotional, verbal, spatial, logical social etc.

 That GPS actually was shorted for 'General Problem Solver' rather than what we have assumed today was a surprise for me.

    The author explains the initiation of logical coding with a simple old school puzzle of two men with a man-eater trying to cross a river with one boat so that only two species are allowed in the boat or trip once or at a time and the man should never be left alone at the mercy of man-eater. The coding would then be working out various combinations using symbols, ifs, buts….

     Mitchell wonders over why we trust a review from a person who is a friend and give weightage to his opinion over others’. She meant to convey that the machine might not be able to analyze the ‘trust’ factor despite it having all the data!  There is a lot more discussion on perception of figures by the machine so that data alone (imagine all sorts of) cannot help it.

Getting along new ideas create lot of optimism breakthrough!

 # Neural network takes the second (entire) chapter with a lot of discussion on the ‘layers’ and is discussed with a view on human brain from which most of the inspiration for analyses is procured.  There is always an input layer and an output layer which are not hidden and what happens inside the hidden layer is based on data and subsequent logics. AI spring and AI winter intervene in between.

 Anthropomorphize is a language that machines might think is based on Turing’s test.

In this connection Ray Kurzweils ‘Text to Speech’ analysis is suggested to give futuristic prognostications machine.  His books “The age of spiritual machines” and “The singularity is near” is suggested for further reading.

# The concept of exponential growth is mentioned with a story of a Sage visiting a neighboring rich king and challenging to answer any question asked by the ‘Darbar’. The sage extracts promise from the king that he be given grains that double over the chessboard, each time he answers correctly. The king at first laughs over it and agrees only to realize in dismay that by the time second row of the chess (16 squares) get covered, about 65,536 grains got accumulated (~ 2 kg). Here it should make a difference between the man and machine. While the king realizes the wisdom of the sage, the machine might not!

# Raw info from pictures in obtained from simple queries like: who, what, when, where and why. This section has many examples that are simple as well. But when it comes to transformation into ‘wisdom’, the marvelous nature of the brain could never be understood. How brain transforms visual info into what the scene can be hard for the machine to accomplish. For instance, a dog with human is hard for the machines to recognize if the picture is not clear. So, the data scientists built a network called ConvNet (Convolutional Neural network), where the Shades of pictures are pixelated and the values given and evaluation is done.

# PASCAL gets a tribute as one of the early machine level language and is implemented by Amazon as Mechanical Turk which still requires human intelligence to work with for its market place.

 # That Facebook with which we were happier when it was started as a social platform had actually a hidden objective. It gathered all our data and registered a patent for classifying our photos with emotions behind expressions.  Using similar logic Twitter filtered pornographic images. And for the analytical part it required huge number of CPU’s and it was then that the Nvidia’s GPUS stock prices increased 1000% when ConvNet and ImageNet usage doubled.

#  Facebook says ‘thankyou’ because it was able to differentiate persons using imaging techniques and was able to offer ‘tag’ for persons. Likewise, Flickr used pictures for its training to recognize them via machines. There is description of Long tail graph with many good examples, simple though and that might give an idea on how anyone can consider simple failure possibilities into avoiding catastrophes. This is basically a figuring graph that talks about the likelihood of things that may appear while performing (i.e. if you want to train a driver-less car you have to mention what all it can come across, like more traffic lights and less often a lion on the street).

# Images with blurry background predicting animals and Camera face determination seeing blinking Asians or racially denigrating species have been some output by the machines, particularly with Deep Neural network.

# Ethical AI section deals a lot with the ethics a machine might not ‘know’. If you have asked a driver-less car to take you home it cannot determine if it really knows what it need to know. It might warrant a misuse of the car. Google’s DeepMind has thus postulated a lot for the beneficial ethics of face recognition (similar to FB asking to tag you).

 #  Fundamental rules of Robotics by Asimov get mentioned and it is always exciting to read.

“A robot must not injure a human” and further rules make a pleasant reading. It is here that the author talks about a simple Trolley problem. There is a picture of a woman with a trolley trying to cross a road and she is engrossed over mobile while doing the cross. If an unmanned vehicle suddenly came across such a woman and if it were to avoid hitting her it would have to make a swerve in a opposite direction that may kill more than this single woman. So then should the car go ahead and kill one instead of six?

# That Steve Jobs started his career when Atari, a breakout game was assigned to him might provide solace to all the gamers who are struggling with a slow IT future. But Steve was a hard worker and he probably knew the future of the machines that might have helped him achieve his goals. The concept of Supervised learning vs Reinforcement learning is then discussed to lessen the projected dangers expected of the machines. Similarly, another stalwart gets his name mentioned: Checkers and Chess code writer Arthur Samuel of IBM who coined the word ML.

     The probability and statistics are useful when you have prediction rather than performance. Deep Blue, another network-based ML firm has made a good foray into many areas, particularly chess where every position may have 35 moves on an average. Similarly, Monte Carlo, the simulation techniques on probability, including electron position evaluation, was first used to design the atom bomb (Manhattan project) with a family of computer algorithm and so these still do a great job (including Quantum Mechanics).

# The information derived from data with any result or conclusion often takes time for the machine. If not for the processor, it would never beat humans who have now started to lag behind machines leaving the latter do all the stuff. The various conclusions drawn from a single story is discussed in many pages with interesting results that prove that AI cannot beat human intelligence. Here is the story: In a restaurant a customer orders some food which gets unfortunately charred by the cook and the waitress presents the food to the customer with an excuse but the man leaves the restaurant murmuring some words (machines cannot get that while humans can guess his dismay). The waitress' last words were “why is he so bent”?

Now this story is fed to machine with a translator and different languages interpret different views which makes the reading interesting (Word2Vec initially). But it is only the human being who can understand well that the customer went without eating! (Gracias: Neural network layer). One language interpreting machine was able to conclude the angular geometry!!! (bent).

     A new rule of the thumb probably displaces 80-20 rule for the learners to 90-10 – the first 90% of a project takes about 10% of time and the last 10% taking 90% of time.

In the end, the author puts forward the speculations around AI as the expectations associated with it are very high. There is no exact conclusion about the future of the AI and only incremental or infinitesimal changes in the technological front over a period would be to the fore. People who know coding, algorithms and data science would have tough time to train machines to get closer to the natural intelligence. And those without any data or algorithm would be left pondering in uncertainty.

#Determined: Life_Without_Free_Will by #Robert_Sapolsky – Review

     The forty years that the author spent as a neuro-scientist of human beings has been funneled into a one-word fact ‘Determined’ in the form of a book with a big, splashy write-up, both in number of pages and ambitions. 

    Robert Sapolsky sums up that we do not have ‘free will’ because our actions resulted from prior causes, which themselves resulted from prior causes, which….., corollary with the answer Einstein got over a question on how the Earth is balanced – Turtles all the way down (a seamless chain of causality stretching back in time), and uses a very sensible way of explaining ‘no free will’ on a large and small scale connecting both in the same instance. He leads us through this causal chain of events that goes back to seconds (caused by neurons firing), to minutes (caused by a thought, memory, emotion, or sensory stimulus), hours to days (hormones), to months (long-term experiences, e.g. depression), to years and decades (e.g. childhood, genetics), and centuries (the culture of ancestors).

     Sapolsky duly argues that the activity of brain precedes conscious awareness of actions and introduces us to some reliable episodes in the first few chapters. His central point is that “we are nothing more or less than the cumulative biological and environmental luck, over which we had no control”.

      This book is both about the science of why there is no free will (if you do not agree that there is no free will, at first instance) and the science of how we might best live once we accept that. Science, of course, is relevant; but that does not make free will a scientific question. It occurred to me that slavery, not on anyone's will and which has been rampant through ages is morally wrong beyond doubt.

The empirical facts about slavery are relevant, but this does not make the issue of the moral justifiability of slavery a logical question. How we should adjust our attitudes and behavior in light of a belief in determinism, if we were to acquire such a belief, is definitely not a scientific question.  Much of the book is devoted to establishing that our behavior (choices/formations of intentions and actions) is determined in this sense, and thus not free. Sapolsky holds that this implies we cannot legitimately be held morally responsible for it!

 Sapolsky concludes: “You cannot decide all the sensory stimuli in your environment, (Quantum effects) your hormone levels this morning (depending on the available chemicals inside you), whether something traumatic happened to you in the past (not in your control), the socioeconomic status of your parents (almost all can recount this fact), your fetal environment (no choice), your genes (again), whether your ancestors were farmers or herders - we are nothing more or less than the cumulative biological and environmental luck, over which we had no control, that has brought us to any moment”.

 Here is the unit-wise abstract covered in 15 chapters albeit with a lot of foot-notes and elaborate appendix, that is not included here.

 # The introductory chapter is well begun with the goal being “there is no free will” and those who do not believe in that being proved wrong. Due to the cumulative biological and environmental luck a society often holds people morally responsible for the actions every individual denies and this is attributed to the neuron which functions with a causeless cause.

# Slowly moving up to ‘consciousness’ that is often the unsolved mystery with the neuroscientists on where it is stored, this author calls it an ‘irrelevant hiccup’. This is where our matter meets the energy of the Universe.

 # The intention to shoot is crime and how missing a shot absolves the shooter of the crime is considered as something not in our control. Thus if the shooter can press the button for shooting, it is triggered by the molecule in the brain which connects the matter around us to the consciousness part of our existence. For such a task to be taken up the hormone glucocorticoids mobilises energy from the cell and the hippocampus raises the levels of these to execute it.

 # The actual work of the author is probably described in this unit where it was interesting to learn that the ‘frontal cortex’ is the last part of the brain to develop – and is least shaped by genes and most helped by environment!  That is why some mature slowly and hence childhood environment is held essential for the development of a person including the way he develops in the womb.

 # The process in Pre-Frontal Cortex is held responsible for the analyzing skills a person might develop. Doing the right thing when it is the hardest improves cognition and based on these, humans can evolve out what is right and what is not. An example that is quoted is the mention of ‘months’ in order. After September, October follows but with a mention of August the brain can try to correct the process  and might go on to account for the change in actual 'value'. It is here the value of dopamine comes to the fore and craves for something new or novel. This process is adequate during adulthood.

 # The influence of chaos on us is then narrated as predictability over time. An example is how the “Moon influences the Sun”, which actually means that “Earth influences how the Moon influences the Sun on Earth”! This part of the book has elaborate mazes and puzzles that would warrant a skip if one is not interested in probing them. I did skip.

 # After the rendition of chaos, the relationship between it and 'free will' is accounted next. Indeterminism of Chaos means that although it does not help you prove that there is free will, it lets you prove that you cannot prove that there is not! Even if Chaoticism is unpredictable it is still deterministic.

 # The outcome of these is considered “Emergent complexity”. A waterfall maintains constant emergent features over time despite no water molecule participates in the waterfall-ness more than once. Here the author uses few more examples like Slime mould experimentation, Snow flake construction, branching capillary leaf, diffusion-based geometry etc. Somehow the Pareto distribution principle is discussed (the 80-20 rule). But an interesting part in this chapter was that most proteins in our bodies are specialists interacting only with the handful of other proteins forming small functional units. This is important as we do not supply interacting ‘chemicals’ for these interactions resulting in deficiency of essential chemicals in the body and subsequent malfunctioning.

 # The isomerism, a functional one that is often described in chemistry is best depicted here (keto-enol tautomerism). While the ‘enol’ form of the hormone may lead to estrogen production the ‘keto’ form leads to testosterone and thus a small flip between these isomers (of the order of 100000 flips per second) might result in the birth of a girl or a boy!

 # Quantum Indeterminacy is explained with ample examples including Brownian Motion of the molecules in solution. These particles bumping around randomly may interact and lead to quantum entanglement or non-locality or wave-function collapse or even QM tunneling. It was tough to account why the author says this here, but wave-particle duality could come in handy if one is aware of this – the outcome that is unpredictable.

 # If free will is random, then believing in religious person to be spiritual is left to one’s choice because a religion is organized over several years and gets refined over time so that spirituality has no connection whatsoever as it may be found in normal persons as well (how did he get that? No free will). Quantum healing by an Indian author and other similar books get mentions here. The author randomly choses several facts pertaining to the body functionality to prove this. Tubulin with 445 amino acids with a good number of atoms in this molecule plays a vital role in the hippocampus where one can find several synapses and the law of numbers cannot account for the quantum bubbling that happens there.

 # If free will is a myth, our actions are the mere amoral outcome of biological luck for which we are not responsible. Then why not run amok? There is random mention about DNA, ECG or EEG and the number of countries where people do not believe in God is related with spiritual thoughts.  Religious pro-sociality is mostly about religious people being nice to people like themselves! From micro to macro.

 # The biology underlying your change in behaviour is the same as when a sea slug learns to avoid a shock administered by a researcher. Some correlations with the negative feelings and human reflexes are correlated here with those of animals’ behaviour. This follows an elaborate discussion related to the experimental animal Aplysia whose functionality with a siphon system is sketched out with lots of figures, some including sensors. Suddenly there is Donald Trump’s quote on Mexicans!

 # The last chapters seem to be not very coherent with the aim with which the book was started. There is more about history and the society. How the medicinal system in earlier days was classified into four basic catergories like black and yellow bile, Phlegm, blood and how the seizures (epileptic) in humans were considered as an amusing by the evil spirit. This is then related to thoughts in our brain. Most people have an internal voice in their heads narrating events, reminding us with the tasks ahead and intruding with unrelated thoughts.

 # The Joy of punishment elaborately discusses the history related to punishing the cheaters over several ages. The shocking info about the Nobel Prize winner Breivik gunning down about 69 people just as casually as one could have a walk in the lawn and escaping punishment was something that the Norway government could not resolve amicably. A Nobel man running amok was an uncontrolled event.

 # “After you have pooped, do you wipe front to back or back to front” was a questionnaire over a few European countries.  Those choosing 'front to back' were considered right and those otherwise were supposed to lose friends!  Another one was on 'Leptin' which is there among obese people and has been remarked as a disease by many. There is a poem in the last chapter that I did not read because it seemed out of context. People in future will always marvel at what we did not know. Time!

#Brave_New Words - How_AI_ will_ Revolutionize_ Education (and why that's a good thing) - by Salman Khan #Review

     After coming across a praise heaped by Bill Gates over Salman Khan of Khan Academy, I decided to have a go with this book.  When everyone associated with education is swayed both in positive and negative directions under the influence of information flow, this book presents an optimistic and practical insight on how artificial intelligence will revolutionize education in the coming years. The author proves that the fear that AI will overtake jobs from humans is unfounded. Only persons who don’t accept AI will be left out and embracing AI is not a task no one can accomplish.

Khan's book serves as an invaluable guide for anyone seeking to understand the implications of AI for learning - from parents and teachers to administrators and policymakers. ‘Brave New Words….’ presents a breath of air in that sense, clearly explaining how the Khan Academy has partnered with OpenAI, to provide its own platform for AI named "Khanmigo" promising to offer the best possible integration of AI and education.

As a respected pioneer in educational technology He accessibly explains the core technologies underpinning this AI revolution and lays out specific ways they can be leveraged to provide each learner with adaptive instruction and feedback tailored to their unique needs, interests and pace. While acknowledging that AI is still in a beta stage technologically, Khan compellingly makes the case that its thoughtful adoption in classrooms will enhance, rather than replace, human interaction and creativity.

            Beyond the classroom, Khan explores the broader societal implications of educational AI - from its potential to make hiring more meritocratic to the ethical considerations in its development and deployment. His insights provide a valuable roadmap on how we can proactively shape these technologies as an overwhelming force for good.

            At its core, Brave New Words is a profoundly hopeful book, reflecting Khan's lifelong passion to harness technology to improve lives through learning. While educational AI undoubtedly brings new risks and challenges that require ongoing vigilance, Khan convincingly argues the opportunities for expanding educational access and efficacy are simply too great to ignore. For anyone who cares about the future of education, this book is essential reading.

            Khan sees this technology being used not just in the classroom, but as a way to help parents monitor their children's progress, offer therapy, and even facilitate conversation among families, which he shows he has already carried out.  These are helpful, because of the anxiety of speaking in class, or the difficulty of getting our kids to tell us about their day.

The beginning is a bang, but as you go on you may realise that there is more about his own AI platform and this entire book is basically a really long ad for Khanmigo with ample quotes and examples from it.

#The_Laws_of_Human_Nature by Robert Greene - Review

 

    This is another book that I would classify under the 'fast-read' category because of its narration about human tendencies rather than laws. For an efficient slow reading, one must be in his early 20s as later on he might learn by himself these facts of life. It just appeared to me that with each chapter I was assigning people around me with all the laws and characters the author was mentioning. As most of his 'reviews' were around human nature one might find some or other author of these types of thoughts or reviews around the literature of his time. I found some of his despairs in the voices of some Urdu writers like Akbar Allahabadi, Meer Taqi Meer, and Khaleel Gibran (Persian). But this book is not void of worth as the author has classified the tendencies into laws that can serve to forewarn a beginner who experiences rational emotions around him as he starts working.

 Here is the list of 'laws' from this book

 1. The Law of Irrationality

Often people are dominated by emotions and behave irrationally without realizing it. This is the source of bad decisions and negative patterns in life. Example: Athenes prospered when it was led by Pericles in 400 BC, who is believed to have been a very rational man. After he left the political arena Athenes started to regress.

 2. The Law of Narcissism

Many people are narcissists and thus focus and admire on themselves. This hinders success when interacting with others is essential.   Example: Joseph Stalin — the premier of the Soviet Union — was a very charming and influential person. He was also a narcissist who killed many people during his reign. Leo Tolstoy — a Russian novelist — and his wife Sonya were both narcissists. Their relationship was complicated.

 3. The Law of Role-playing

People tend to wear the mask that shows them in the best possible light hiding their true personality. Example: Milton Erickson — an American psychiatrist and psychologist of the 20th century — was paralysed when he was young and became a master reader of people body language.

 4. The Law of Compulsive Behaviour

People never do something just once. They will inevitably repeat bad behaviour.    Example: Howard Hughes Jr. — an American business magnate, investor, record-setting pilot, engineer, film director, and philanthropist — had a weak character since his childhood. He managed to disguise it in his early career which brought him success. However, it manifested later in his life and resulted in many failures including Hughes Aircraft Company.

5. The Law of Covetousness

People continually desire to possess what they don’t have.  Example: Coco Chanel — a French fashion designer and businesswoman — became so successful not only because she created great products but because she understood that people desire what they don’t have and created an air of mystery around her work.

6. The Law of Short-sightedness

People tend to overreact to present circumstances and ignore what will happen in the future. Example: The South Sea Company — a British joint-stock company founded in 1711 — became known as the South Sea Bubble. It was obvious that the company could not succeed long-term but it didn’t stop many people from investing in its shares.

7. The Law of Defensiveness

People don’t like when someone is trying to change their opinion. Example: Lyndon Johnson — the 36th president of the United States — gained his influence and power by focusing on others, letting them do the talking, letting them be the stars of the show.

8. The Law of Self-sabotage

Our attitude determines much of what happens in our life.  Example: Anton Chekhov — a Russian playwright and short-story writer — had a tough childhood but despite that was able to change his life by changing his view of the world from negative to positive.

9. The Law of Repression

People are rarely who they seem to be. Lurking beneath their polite, affable exterior is inevitably a dark, shadow side consisting of the insecurities and the aggressive, selfish impulses they repress and carefully conceal from public view. Example: Richard Nixon — the 37th president of the United States — always had a positive image in the public. Everything changed after the Watergate scandal which revealed his hidden personality.

10. The Law of Envy

People are envious.  Example: Mary Shelley — author of the novel Frankenstein — was betrayed by her close friend who envied her.

11. The Law of Grandiosity

Even a small measure of success can elevate our natural grandiosity — an unrealistic sense of superiority, a sustained view of oneself as better than others. This can make us lose contact with reality and make irrational decisions.  Example: Michael Eisner had to resign from the CEO position of The Walt Disney Company. In the author’s opinion, the cause is Eisner’s grandiosity elevated by previous successes.

12. The Law of Gender Rigidity

All of us have masculine and feminine qualities. But in the need to present a consistent identity in society, we tend to repress these qualities, overidentifying with the masculine or feminine role expected of us. Thereby we lose valuable dimensions to our character.  Example: Caterina Sforza became an Italian noblewoman and Countess of Forlì and Lady of Imola. Such titles were unusual for women in her time. In the author’s opinion, her masculine qualities helped her to achieve this.

13. The Law of Aimlessness

People become most successful when they have a sense of purpose in their life. Example: Martin Luther King Jr. is best known for advancing civil rights through nonviolence and civil disobedience. His calling directed his actions and helped him go through many failures in his life.

14. The Law of Conformity

We have a side to our character that we are generally unaware of and is related to social life. We tend to become different people when we operate in groups of people such that we unconsciously imitate others. Thus we act and believe differently. Example: Gao Yuan’s story in his book Born Red showed that people in groups behave emotionally and excitedly.

15. The Law of Fickleness

People are always ambivalent about those in power. They want to be led but also to feel free; they want to be protected and enjoy prosperity without making sacrifices; they both worship the king (leader) and want to kill him.    Example: Elizabeth I — Queen of England and Ireland in the 16th century — had to constantly prove herself as the leader of the country.

16. The Law of Aggression

On the surface, the people around you appear so polite and civilized. But beneath the mask, they are all inevitably dealing with frustrations. They have a need to influence people and gain power over circumstances.    Example: John D. Rockefeller — an American oil industry business magnate — used aggressive strategies to gain power and control.

17. The Law of Generational Myopia

You are born into a generation that defines who you are more than you can imagine and this generation wants to separate itself from the previous one to set a new tone for the world. In the process, it forms certain tastes, values, and ways of thinking that you as an individual internalize. As you get older, these generational values and ideas tend to close you off from other points of view, constraining your mind. Example: King Louis XVI of France is shown as an example of someone out of tune with the times. He fell victim to the French Revolution when France was declared to be a Republic and abolished the monarchy.  Keep yourselves updated?

18. The Law of Death Denial

Most people spend their lives avoiding the thought of death.  Example: Mary Flannery O’Connor — an American novelist and short story writer — was diagnosed with systemic lupus erythematosus when she was 27. Her proximity to death was a call to stir herself to action and she used this aspect to teach her selves what really mattered and to help her steer clear of the petty squabbles and concerns that plagued others.

    Some of the chapters can drag you as the author repeats the same point, and you get the feeling that the book could have been made shorter without loss of content. It is also difficult to tell which ideas are supported by solid science/research and which are not, as this is not referred to anywhere. Some ideas are backed by solid historical and scientific evidence, such as a chapter on narcissism, but in other sections, the ideas are more ambiguous, as, for example, when the author seems to believe that Milton Erickson recovered quicker from polio through the mental stimulation of his nerves.

     Also, there could have been more evolutionary psychology as there is nothing more fundamental to our nature and this could have included the cognitive biases. But overall the book can be enjoyed as there is a lot of advice related to the ‘laws’ mentioned.