Wisdom Of The Week

Make no mistake: I am not suggesting that liberals adopt a fuzzy, gentler version of their politics. I am not suggesting they compromise their issues for the sake of playing nice. What I am suggesting is that they consider how the issues they actually fight for have drifted away from their egalitarian intentions.

I am suggesting that they notice how hating and ridiculing the people they say they want to help has led them to stop helping those people, too.

I am suggesting that in the case of a Kim Davis, liberalism resist the impulse to go beyond the necessary legal fight and explicitly delight in punishing an old foe.

I am suggesting that they instead wonder what it might be like to have little left but one's values; to wake up one day to find your whole moral order destroyed; to look around and see the representatives of a new order call you a stupid, hypocritical hick without bothering, even, to wonder how your corner of your poor state found itself so alienated from them in the first place. To work with people who do not share their values or their tastes, who do not live where they live or like what they like or know their Good Facts or their jokes.

This is not a call for civility. Manners are not enough. The smug style did not arise by accident, and it cannot be abolished with a little self-reproach. So long as liberals cannot find common cause with the larger section of the American working class, they will search for reasons to justify that failure. They will resent them. They will find, over and over, how easy it is to justify abandoning them further.They will choose the smug style.

Maybe the cycle is too deeply set already. Perhaps the divide, the disdain, the whole crack-up are inevitable. But if liberal good intentions are to make a play for a better future, they cannot merely recognize the ways they've come to hate their former allies. They must begin to mend the ways they lost them in the first place.

- The smug style in American liberalism

Quote of the Day

The technocratic illusion is that poverty results from a shortage of expertise, whereas poverty is really about a shortage of rights. The emphasis on the problem of expertise makes the problem of rights worse. The technical problems of the poor (and the absence of technical solutions for those problems) are a symptom of poverty, not a cause of poverty. This book argues that the cause of poverty is the absence of political and economic rights, the absence of a free political and economic system that would find the technical solutions to the poor’s problems. The dictator whom the experts expect will accomplish the technical fixes to technical problems is not the solution; he is the problem.

William Easterly, The Tyranny of Experts: Economists, Dictators, and the Forgotten Rights of the Poor

Quote of the Day

First,  education  is  not  solely  about  the  acquisition  of  speci c  tools  to  use  in  a  subsequent  career. As one of the greatest creations of human civilization, mathematics should be taught alongside science, literature,  history,  and art in order to pass along the jewels of our culture from one generation to the next.  We humans are far more than the jobs we do and the careers we pursue. Education is a preparation for life, and only part of that is the mastery of specic work skills.

- Introduction to Mathematical Thinking by Keith Devlin

Quote of the Day

Formulas that assign equal weights to all the predictors are often superior, because they are not affected by accidents of sampling.

- Daniel Kahneman

Quote of the Day

If you want to really hurt you parents, and you don't have the nerve to be gay, the least you can do is go into the arts. I'm not kidding. The arts are not a way to make a living. They are a very human way of making life more bearable. Practicing an art, no matter how well or badly, is a way to make your soul grow, for heaven's sake. Sing in the shower. Dance to the radio. Tell stories. Write a poem to a friend, even a lousy poem. Do it as well as you possible can. You will get an enormous reward. You will have created something.

- Kurt Vonnegut, A Man Without a Country

Quote of the Day

Even bigger machines, entailing even bigger concentrations of economic power and exerting ever greater violence against the environment, do not represent progress: they are a denial of wisdom. Wisdom demands a new orientation of science and technology towards the organic, the gentle, the nonviolent, the elegant and beautiful.

- E.F. Schumacher,Small Is Beautiful: Economics as if People Mattered

Quote of the Day

The world is in greater peril from those who tolerate or encourage evil than from those who actually commit it.

- Albert Einstein

You Can't Program Passion

Khire tells Inverse, “I think that A.I. has the ability to tell the world that you need to be more human again.”Khire is one of the developers behind an A.I. called “Emma/Mansi.” Emma was launched last year in the financial markets in “stealth mode” (meaning it is being used, but hasn’t had a major release announcement). But beyond what it’s doing for Wall Street, Emma offers a glimpse into how A.I. might affect our lives in the future.

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Emma is currently working in the financial market, taking in massive amounts of quantitative and qualitative data about Exchange-Traded Funds (ETFs). With that info, the A.I. can make predictions of which ETFs will be profitable. Emma still needs humans to help teach it particular skill sets, but eventually the technology will be able to function on its own.

Yet the core idea behind Emma isn’t to make human traders obsolete — it’s to cut the busy work. Eventually, Khire wants to apply his A.I. to other industries, like accounting, writing, and even medical diagnosis.

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Medicine is another area that A.I. can improve people’s lives. People visit the doctor countless times around the world, but a high number of those people don’t actually need to see a doctor in person. And in certain parts of the world, people can’t see a doctor in person.

“In India, parts of Africa, Myanmar, there are people who literally don’t have access to healthcare,” Khire says. “But they do have Facebook and WhatsApp. One way to bring affordable healthcare for them is essentially an A.I.-driven doctor who can give prescriptions and diagnose basic stuff.”

It’s ironic to believe that A.I. will make interpersonal communication cool again. But it’s also not that hard of an idea to get excited about — if people can get over the fear of losing their job, that is.

“In the realm of A.I., even if you have a humanoid, it’s never really going to be able to replace a human in its entirety,” Khire says. The technology will eventually exist for A.I. to run the world itself, but flesh and blood has something A.I. never will: passion. And as Khire says, “you can’t program passion.”

- More Here

Quote of the Day

I choose my friends for their good looks, my acquaintances for their good characters, and my enemies for their good intellects.

- Oscar Wilde

Outwitting Poachers with AI

With support from the National Science Foundation (NSF) and the Army Research Office, researchers are using artificial intelligence (AI) and game theory to solve poaching, illegal logging and other problems worldwide, in collaboration with researchers and conservationists in the U.S., Singapore, Netherlands and Malaysia.

"In most parks, ranger patrols are poorly planned, reactive rather than pro-active, and habitual," according to Fei Fang, a Ph.D. candidate in the computer science department at the University of Southern California (USC).

Fang is part of an NSF-funded team at USC led by Milind Tambe, professor of computer science and industrial and systems engineering and director of the Teamcore Research Group on Agents and Multiagent Systems.

Their research builds on the idea of "green security games" -- the application of game theory to wildlife protection. Game theory uses mathematical and computer models of conflict and cooperation between rational decision-makers to predict the behavior of adversaries and plan optimal approaches for containment. The Coast Guard and Transportation Security Administration have used similar methods developed by Tambe and others to protect airports and waterways.

"This research is a step in demonstrating that AI can have a really significant positive impact on society and allow us to assist humanity in solving some of the major challenges we face," Tambe said.

- More Here

Wisdom Of The Week

We believe in dreams at the moonshot factory. But enthusiastic skepticism is not the enemy of boundless optimism. It's optimism's perfect partner. It unlocks the potential in every idea. We can create the future that's in our dreams.

- Astro Teller: The unexpected benefit of celebrating failure

Quote of the Day

When one tugs at a single thing in nature, he finds it attached to the rest of the world.

- John Muir

Need Big Theory Not Big Data To Revolutionize Medicine

The worship of big data downplays many issues, some profound. To make sense of all this data, researchers are using a type of artificial intelligence known as neural networks. But no matter their “depth” and sophistication, they merely fit curves to existing data. They can fail in circumstances beyond the range of the data used to train them. All they can, in effect, say is that “based on the people we have seen and treated before, we expect the patient in front of us now to do this”.

Still, they can be useful. Two decades ago, one of us (Peter) used big data and neural networks to predict the thickening times of complex slurries (semi-liquid mixtures) from infrared spectrums of cement powders. But, even though this became a commercial offering, it has not brought us one iota closer to understanding what mechanisms are at play, which is what is needed to design new kinds of cement.

The most profound challenge arises because, in biology, big data is actually tiny relative to the complexity of a cell, organ or body. One needs to know which data is important for a particular objective. Physicists understand this only too well. The discovery of the Higgs boson at CERN’s Large Hadron Collider required petabytes of data; nevertheless, they used theory to guide their search. Nor do we predict tomorrow’s weather by averaging historic records of that day’s weather – mathematical models do a much better job with the help of daily data from satellites.

Some even dream of minting new physical laws by mining data. But the results to date are limited and unconvincing. As Edward put it: “Does anyone really believe that data mining could produce the general theory of relativity?"

- More Here

Quote of the Day

My desire and wish is that the things I start with should be so obvious that you wonder why I spend my time stating them. This is what I aim at because the point of philosophy is to start with something so simple as not to seem worth stating, and to end with something so paradoxical that no one will believe it.

- Bertrand Russell, The Philosophy of Logical Atoms

What I've Been Reading

With the baby boomer retirements looming, so that far fewer workers will soon work to support far more dependents, we as a society need to do everything we can to store more wealth. To prepare for this, we need to store wealth in one or more of the four ways above: stockpiles, tangible physical infrastructure, intangible improvements, and human capital. 

Bypass Wall Street: A Biologist's Guide to the Rat Race by Joanna Masel. Human relationships are messy.. but yet Masel insists its better than blindly trusting Wall Street to invest for the future. I grew up in India and watching the messy human relationships getting more messier when rupees came into play. So I am in the neither/nor team.

Sometimes we have a choice in how we estimate things. We can either be precise, or we can be accurate, but we cannot always be both. This trade-off is well know to engineers who work in measurement systems.

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To understand how the difference between precision and accuracy affects investing, consider the stock of some company. Its long-term value to Jen's retirement portfolio depends on the future profits of the company compared to the returns that one could get buying a different financial asset instead. We can't know this true value. Only with hindsight, many years later, could an analyst look back and say that a good price would have been $105.67. This is its real, but unknowable value. Stuck in the present with no time machine, the best analyst can do is estimate that the stock is worth about $100, plus or minus $10 or so. He can't be more precise than that, but he is in fact quite accurate, only about 5% off. On the market, the stock is trading for $122.39. This is very precise, down to the cent, but less accurate: it is 22% off. Our analyst estimate is more accurate, while the market is more precise.

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Their precision is a lure that Jen (we) should ignore. To invest more successfully in the future, we need accuracy instead.

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A short-term trader quickly learns whether he is doing a good job being precise. He either succeeds in making money, year after year, buy buying low and selling high, or he doesn't. His incentive is to succeed in his short term task. He get plenty of feedback as to whether he is doing a good job. This frequency of feedback is a major reason why humans make the mistake of favoring precision over accuracy. But to successfully invest in our long-term interest as a society, we need to become more accurate. In the fight for accuracy, precision is a false god and our enemy. In her search for good investments, Jen therefore resolves to ignore the allure of precision. 

Quote of the Day

Suckers think that you cure greed with money, addiction with substances, expert problems with experts, banking with bankers, economics with economists, and debt crises with debt spending.

- Nassim Nicholas Taleb, The Bed of Procrustes: Philosophical and Practical Aphorisms

First Contact with Tensor Flow

Free Tensor Flow content from Jordi Torres (and you buy the book as well) - highly recommended , brilliant !!

The purpose of this book is to help to spread this knowledge among engineers who want to expand their wisdom in the exciting world of Machine Learning. I believe that anyone with an engineering background may find applications of Deep Learning, and Machine Learning in general, valuable to their work.

Given my background, the reader probably will wonder why I have proposed this challenge of writing about this new Deep Learning technology. My research focus is gradually moving from supercomputing architectures and runtimes to execution middleware’s for big data workloads, and more recently to platforms for Machine Learning on massive data.

Precisely by being an engineer, not a data scientist, I think I can contribute with this introductory approach to the subject, and that it can be helpful for many engineers in the early stages; then it will be their choice to go deeper into what they need.

Quote of the Day

The dinosaurs disappeared because they could not adapt to their changing environment. We shall disappear if we cannot adapt to an environment that now contains spaceships, computers — and thermonuclear weapons.

- Arthur C. Clarke

We Might Be Totally Wrong About Why the Dinosaurs Went Extinct

Most of us have heard of the giant asteroid impact, and the possibility that volcanoes played a role is also well-known. But a complementary school of thought contends that neither of these two events gives us the full story. Rather, some researchers say the dinosaur lineage was slowly pruning itself for many millions of years prior to the KT-boundary. Until now, this idea has seen limited scientific support.

“Previous studies were quite simple,” Manabu Sakamoto, a paleontologist at the University of Reading and lead author on the new study told Gizmodo. “They counted the number of [dinosaur] species around at each age or time interval to see which ones were peaking or troughing when. To be honest, it’s not a very statistical approach.”

Sakamoto and his colleagues used a more rigorous procedure, measuring the number of times new dinosaur species emerged (so-called “speciation events”) throughout geologic history. Over the Triassic and Jurassic, dinosaur diversity was on the rise, but by the early Cretaceous, speciation had begun to plateau. By the mid to late-Cretaceous, the rate of dinosaur evolution had taken a sharp downturn. It would continue to fall for millions of years before the Chixculub impact.

“New species weren’t being produced as fast as species were going extinct,” Sakamoto explained. “That made the dinosaurs vulnerable to drastic environmental changes—especially something like an apocalypse.”

- More Here

Quote of the Day

In order to control over one's senses, one has to be humble and modest. It is the learning that makes man humble. A ruler with an inflated ego and arrogance cannot be a good ruler. If he gets down to solving the people's Problems , He has to become humble to succeed.

- Chanakya

Quote of the Day

Philosophy calls for simple living, not for doing penance, and the simple way of life need not be a crude one.

- Seneca, Letters from a Stoic

Quote of the Day

No account of Pauli and his attitude to people would be complete without mention of his critical remarks, for which he was known and sometimes feared throughout the world of physics…

No doubt many of the stories of this kind circulated about him are apocryphal, but the examples below come from reliable sources or from conversations at which the writer was present…

Quite recently, a friend showed him the paper of a young physicist which he suspected was not of great value but on which he wanted Pauli’s views. Pauli remarked sadly ‘It is not even wrong.’

- Pauli and Not Even Wrong

Wisdom Of The Week

The African elephant brain had more neurons than the human brain. And not just a few more: a full three times the number of neurons, 257 billion to our 86 billion neurons. But—and this was a huge, immense “but”—a whopping 98 percent of those neurons were located in the cerebellum, at the back of the brain. In every other mammal we had examined so far, the cerebellum concentrated most of the brain neurons, but never much more than 80 percent of them. The exceptional distribution of neurons within the elephant brain left a relatively meager 5.6 billion neurons in the whole cerebral cortex itself. Despite the size of the African elephant cerebral cortex, the 5.6 billion neurons in it paled in comparison to the average 16 billion neurons concentrated in the much smaller human cerebral cortex.

So here was our answer. No, the human brain does not have more neurons than the much larger elephant brain—but the human cerebral cortex has nearly three times as many neurons as the over twice as large cerebral cortex of the elephant. Unless we were ready to concede that the elephant, with three times more neurons in its cerebellum (and, therefore, in its brain), must be more cognitively capable than we humans, we could rule out the hypothesis that total number of neurons in the cerebellum was in any way limiting or sufficient to determine the cognitive capabilities of a brain.

Only the cerebral cortex remained, then. Nature had done the experiment that we needed, dissociating numbers of neurons in the cerebral cortex from the number of neurons in the cerebellum. The superior cognitive capabilities of the human brain over the elephant brain can simply—and only—be attributed to the remarkably large number of neurons in its cerebral cortex.

- Excerpted from The Human Advantage: A New Understanding of How Our Brain Became Remarkable by Suzana Herculano-ouzel

Quote of the Day

I would never die for my beliefs because I might be wrong.

- Bertrand Russell

Quote of the Day

Consciousness is only possible through change; change is only possible through movement.

- Aldous Huxley, The Art of Seeing

Quote of the Day

Meditation is the dissolution of thoughts in Eternal awareness or Pure consciousness without objectification, knowing without thinking, merging finitude in infinity.

- Voltaire

Quote of the Day

With limited training data, a more constrained model tends to perform better.

- Christopher D. Manning, Introduction to Information Retrieval

Study Used CRISPR to Introduce HIV-Resistance Mutation Into Human Embryos

In the paper, Fan, who works at Guangzhou Medical University in China, and his team say that they collected a total of 213 fertilized human eggs between April and September 2014. The fertilized eggs, donated by 87 patients, were unsuitable for implantation as part of in vitro fertility therapy, because they contained an extra set of chromosomes.

Fan’s team used CRISPR–Cas9 genome editing to introduce into some of the embryos a mutation that cripples an immune-cell gene called CCR5. Some humans naturally carry this mutation (known as CCR5Δ32) and they are resistant to HIV, because the mutation alters the CCR5 protein in a way that prevents the virus from entering the T cells it tries to infect.

Genetic analysis showed that 4 of 26 human embryos targeted were successfully modified. But not all the embryos’ chromosomes harboured the CCR5Δ32 mutation — some contained unmodified CCR5, whereas others had acquired different mutations.

George Daley, a stem-cell biologist at Children’s Hospital Boston in Massachusetts, says that the paper’s main advance is the use of CRISPR to introduce a precise genetic modification successfully. “This paper doesn’t look like it offers much more than anecdotal evidence that it works in human embryos, which we already knew,” he says. “It’s certainly a long way from realizing the intended potential” — a human embryo with all its copies of CCR5 inactivated.

“It just emphasizes that there are still a lot of technical difficulties to doing precision editing in human embryo cells,” says Xiao-Jiang Li, a neuroscientist at Emory University in Atlanta, Georgia. He thinks that researchers should work out these kinks in non-human primates, for example, before continuing to modify the genomes of human embryos using techniques such as CRISPR.

- More Here

Quote of the Day

The secret of all victory lies in organising the non-obvious.

- Oswald Spengler

How to Read a Book a Week

• Start with the author. Who wrote the book? Read his or her bio. If you can find a brief interview or article online about the author, read that quickly. It will give you a sense of the person’s bias and perspective.
• Read the title, the subtitle, the front flap, and the table of contents. What’s the big-picture argument of the book? How is that argument laid out? By now, you could probably describe the main idea of the book to someone who hasn’t read it.
• Read the introduction and the conclusion. The author makes their case in the opening and closing argument of the book. Read these two sections word for word but quickly. You already have a general sense of where the author is going, and these sections will tell you how they plan to get there (introduction) and what they hope you got out of it (conclusion).
• Read/skim each chapter. Read the title and anywhere from the first few paragraphs to the first few pages of the chapter to figure out how the author is using this chapter and where it fits into the argument of the book. Then skim through the headings and subheadings (if there are any) to get a feel for the flow. Read the first sentence of each paragraph and the last. If you get the meaning, move on. Otherwise, you may want to read the whole paragraph. Once you’ve gotten an understanding of the chapter, you may be able to skim over whole pages, as the argument may be clear to you and also may repeat itself.
• End with the table of contents again. Once you’ve finished the book, return to the table of contents and summarize it in your head. Take a few moments to relive the flow of the book, the arguments you considered, the stories you remember, the journey you went on with the author. 

- More Here

Quote of the Day

In the future, the great division will be between those who have trained themselves to handle these complexities and those who are overwhelmed by them -- those who can acquire skills and discipline their minds and those who are irrevocably distracted by all the media around them and can enver focus enough to learn.

- Robert Greene, Mastery

Quote of the Day

So, if people didn’t settle down to take up farming, why then did they embark on this entirely new way of living? We have no idea – or actually, we have lots of ideas, but we don’t know if any of them are right. According to Felipe Fernández-Armesto, at least thirty-eight theories have been put forward to explain why people took to living in communities: that they were driven to it by climatic change, or by a wish to stay near their dead, or by a powerful desire to brew and drink beer, which could only be indulged by staying in one place.

- Bill Bryson, At Home: A Short History of Private Life

Wisdom Of The Week

An “aha moment” is often described as a sudden insight or epiphany that radically changes a person’s perspective. It can be a decision-making moment, spiritual realization or creative breakthrough. Something clicks in the brain and — pop! — things just seem to fall into place.

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Dr. Kyra Bobinet is a University of California, San Francisco and Harvard Public Health graduate who teaches neuroscience and health engagement design at the Stanford School of Medicine. Bobinet also runs a design firm called engagedIN that focuses on engaging people in well-being and behavior change. “My whole passion is why we don’t do what we know we should do, and designing for the disparity between those two aspects of our brain,” says Bobinet.

According to Bobinet, an aha moment like Okupe’s is actually the result of many individual thoughts, conscious or unconscious, that accumulate over time. “Every time I have the thought, ‘oh, I should do this’ or ‘I want to be that’ it throws a penny in the jar of my implicit memory,” she says. The struggle between what people want to do versus what they actually do can result in “cognitive dissonance,” which they may not be consciously aware of. After building up as patterns in someone’s implicit memory, a realization can occur.

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Someone experiencing an aha moment can feel jolted, like they’ve been hit by a flash of lightning. But that’s not the case, at least from a neurological perspective. According to Dr. James Giordano, a professor of neurology at Georgetown University Medical, big decisions — even those precipitated by aha moments — can be years in the making. “A lot of the information that we’re beginning to acquire about [emotional and rational decision-making] is coming from this relatively new field called neuroeconomics,” he says. “We’re looking at the neurological and cognitive processes that are involved in decision making and how individuals will use various resources and services to make life decisions that affect their behaviors and their outcomes.”

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For others looking to find their own aha moment, Bobinet suggests practicing mindfulness, like the yoga and meditation mentioned by Gavle, could free them from the brain’s more inhibitive functions. According to Bobinet, the prefrontal cortex is a part of the brain’s frontal lobe that keeps us in check. “It keeps us from saying the wrong things,” she says. “It’s the area where we’re most self-conscious.”

Bobinet also says that aha moments are often paired with an increase in activity on the brain’s right temporal lobe, which lights up during creative activity. “This area, called the anterior cingulate, opens your vista of what you consider to be a possible solution,” says Bobinet. “As it is stimulated, you start to consider things that are unusual solutions or may be normally dominated by your realities, your biases or your prejudices.”

- More Here

Quote of the Day

The more people there are crowded into a space, the harder it becomes to thrive there. Working in such a field will tend to wear you out as you struggle to get attention, to play the political games, to win scarce resources for yourself. You spend so much time at these games that you have little time left over for true mastery. You are seduced into such fields because you see others there making a living, treading the familiar path. You are not aware of how difficult such a life can be.

- Robert Greene, Mastery

Reason in Dogs - Paper Published in 1904

A friend of mine, Mr. W., owns a Manchester terrier of vhich he is very fond, and for that reason receives rather more than doggy attention. The dog passes most of his ime in the library, where a basket and rug are provided for lim, but he prefers, when it is possible, to take possession of his master's easy chair.

- Full paper here

Quote of the Day

To avoid sucker problems, substitute the abstract "government" with "bureaucrats/politicians" & "science" with "scientists/journal editors".

- Nassim Taleb

The Surprising Habits of Original Thinkers - Adam Grant

Know that being quick to start but slow to finish can boost your creativity, that you can motivate yourself by doubting your ideas and embracing the fear of failing to try, and that you need a lot of bad ideas in order to get a few good ones.
 

Quote of the Day

There is no coming to consciousness without pain. People will do anything, no matter how absurd, in order to avoid facing their own Soul.

- Carl Jung

What I've Been Reading

Galton had discovered that regression toward the mean was not the result of biological change, but rather was a simple consequence of the imperfect correlation between parents and offspring, and that lack of prefect correlation was a necessary requirement for Darwin, or else there would be no intergenerational variation and no natural selection.

The influence was not only in biology. The variance components idea became key to much quantitative and educational psychology. And Galton's idea of separating permanent and transient effects was at the heart of the model that economist Milton Friedman proposed in 1957 in this Theory of the Consumption Function, for which he won the 1976 Nobel Prize.

The Seven Pillars of Statistical Wisdom by Stephen M. Stigler. A small book but each page is power packed with extremely relevant information. Brilliant read for folks who are interested in machine learning.

1. Aggregation - It allows one to gain information by discarding information (mean). 
2. Information Measurement - Information on accuracy does not come linearly with data but its promotional to square root of number of observations. 
3. Likelihood - The use of probability to calibrate inference, be it confidence interval or a Bayesian posterior probability (p-value, bayesian inference etc). 
4. Intercomparison - Statistical comparisons does not need to be made with respect to external data but can often be made in terms interior to the data themselves (t-test etc). 
5. Regression - Regression introduced modern multivariate analysis and the tools needed for any theory of inference. Before this apparatus of conditional distributions was introduced, truly general Bayes's theorem was not feasible. So this pillar is central to Bayesian as well as causal inference. 
6. Experimental Design - This involves great subtleties: the ability to structure models for the exploration of high dimensional data with the simultaneous consideration of multiple factors, and the creation through randomization of a basis for inference that relied only minimally upon modeling. 
7. Residual - The most common appearances in statistics are our model diagnostics (plotting residuals), but more important is the way we explore high-dimensional spaces by fitting and comparing nested models. Every test for significance of a regression coefficient is an example, as is every exploration of a time series. 

Quote of the Day

Politics is a way of ruling divided societies without undue violence.

- Bernard Crick, In Defence of Politics

Quote of the Day

The original question, 'Can machines think?' I believe to be too meaningless to deserve discussion.

- Alan Turing, Mechanical Intelligence: Collected Works of A.M. Turing

10 Studies That Show The Advantages of Feeling Sad

You're more persuasive when you're sad
For this research released in 2007, participants were provoked into happy or sad moods by watching short films, either featuring comedy or a person dying from illness. Next, they had to write down arguments to persuade someone to change their mind about a controversial issue, such as student fees or Aboriginal land rights in Australia. Across several studies testing variants of this set up, sad people produced more effective messages than happy people, and what's more, their arguments were more persuasive. The effect seemed to be due to the fact that sad people produced more concrete and specific arguments than happy people.

Mild depression may come with enhanced empathy 

Depressed people are normally thought of as being somewhat disengaged from the rest of the world, but in 2005 psychologists at Queen’s University in Canada found that mildly depressed students actually had a heightened ability to detect other people’s emotions from photos that showed only the eye region of their face. Unfortunately, this "advantage" could backfire. The researchers said ultra sensitivity to other people's emotions could cause problems for individuals prone to depression – "by being more sensitive, dysphoric and depressed individuals have more opportunities to deploy their negative biases in interpreting fleeting emotional reactions,” they said.

Being in a grump probably won't affect your mental performance

For a study published this year, researchers had participants complete similar versions of the same mental tests for five consecutive days, including memory and processing speed. Each day before the tests, the participants also completed comprehensive measures of their mood. The participants mood and mental performance fluctuated over the course of the study, but crucially the two were not linked – in other words, there was no evidence that being in a bad mood was associated with performing more poorly on the mental tests.

Sad leaders encourage an analytical thinking style 

In this research from 2013, business students received task instructions and encouragement from a manager who spoke to them via video link. The wording of the leader's guidance was the same for all students, but some of them watched the manager deliver his advice in a happy mood, while the others watched him while he was in a sad mood. After the video, those students who'd watched the happy manager excelled at a creative task (coming up with ideas of what you can do with a glass of water), but meanwhile the students who had the sad manager excelled at sudoku puzzles, used as a measure of analytical thinking.

- More Here

Quote of the Day

Most men and women will grow up to love their servitude and will never dream of revolution.

- Aldous Huxley, Brave New World

Human-Complete Problems !!

I want to explore a particular bunny trail: the relationship between being human and the ability to solve infinite game problems in the sense of James Carse. I think this leads to an interesting perspective on the meaning and purpose of AI.

The phrase human complete is constructed via analogy to the term AI complete, an ambiguously defined class of problems, including machine vision and natural language processing, that is supposed to contain the hardest problems in AI.

That term itself is a reference to a much more precise one used in computer science: NP complete, which is a class of the hardest problems in computer science in a certain technical sense. NP complete is a subset of a larger class known as NP, which is the set of all problems for a certain class of non-God-level computers. It contains another subset called P, which are easy problems in a related technical sense.

It is not known whether P and NP complete are proper subsets of NP. If you can prove that P≠NP, you will win a million dollars. If you can prove P=NP, the terrorists will win and civilization will end. In the diagram above, if you replace the acronyms FG, IG and HC with P, NP and NP Complete, you will get the diagram used to explain computational complexity in standard textbooks.

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The idea is a natural extension of Moravec’s paradox into the negative range. If the apparent hard problems are easy and the apparent easy problems are hard, perhaps the set of meaningful problems does not stop at apparent zero-hardness problems like “do nothing for one clock cycle.”

Perhaps there are anti-hard problems that require negatively increasing amounts of stupidity below zero — or active anti-intelligence, rather than mere lack of intelligence — to solve.

Anti-intelligence in this sense is not really stupidity. Stupidity is the absence of positive intelligence, evidenced by failure to solve challenging problems as rationally as possible. Anti-intelligence is the ability to imaginatively manufacture and inflate non-problems into motives containing absurd amounts of “meaning,” and choosing to pursue them (so lack of anti-intelligence, such as an inability to find humor in a juvenile joke, would be a kind of anti-stupidity).

Perhaps this negative range is what defines human. Perhaps some animals go into this negative range (there have been recent reports about spirituality in chimps), but so far I haven’t seen any non-human entity suffer from, and beat, something like Precious Snowflake syndrome.

It’s pretty easy to get AIs to mimic low, but positive levels of human stupidity, like losing a game of tic-tac-toe, or forgetting to check your mirrors before changing lanes. I can write a program capable of losing tic-tac-toe in 10 minutes.

If you can get your AI anti-intelligent enough to suffer boredom, depression and precious-snowflake syndrome, then we’ll start getting somewhere.

- More Here

The Brachistochrone, with Steven Strogatz

Quote of the Day

Learning without thought is labor lost; thought without learning is perilous.

- Confucius

Wisdom Of The Week

Born was after a unifying theory to relate all the fundamental forces of nature. He also wanted a theory that would explain where these constants came from. Something, he said, to “explain the existence of the heavy, and light elementary particles and their definite mass quotient 1840."

It might seem a little bizarre that Born worried about a couple of constants. The sciences are full of constants—one defines the speed of light, another quantifies the pull of gravity, and so on. We routinely use these numbers, flipping to dog-eared tables in reference books, and coding them into our software without much thought because, well, they are constants. But the weird thing about such constants is that there is no theory to explain their existence. They are universal and they appear to be unchanging. So is the case with the masses of protons and electrons. But time and time again, they are validated through observation and experiment, not theory.

What Born and so many others were after was a unifying theory that would demonstrate that there could only be one unchanging value for a constant. Without this theory, scientists resort to testing limits of a constant. Measuring the constant is a good way to verify that theories using them make sense, that science stands on firm ground. Error from the measurements can be a huge concern. So, instead of validating the masses of protons and electrons, it's useful to measure the ratio of their masses, a number that is free of the burden of units.

The search for a unifying theory continued. Two years after Born's lecture, his Cambridge colleague, Paul Dirac, wondered in a Nature paper whether the constants were indeed constant if one were to look at the entire history of the cosmos. Measurements on earth are useful but it is a tiny blue dot in the vast universe. What Dirac asked decades ago is what physicists continue to ask today. Is it a constant everywhere in the universe? Why is it a constant? How constant? The question lingered even as the decades rolled on. “The most exact value at present for the ratio of proton to electron mass is 1836.12 +/-0.05,” wrote Friedrich Lenz in a 1951 Physical Review Letters paper. “It may be of interest to note that this number coincides with 6pi^5=1836.12.” That was the entire paper.

- Are the Constants of Physics Constant?

Quote of the Day

We humans are more concerned with having than with being.

- Professor Norman from the movie Lucy

Tyler's Conversation With Jonathan Haidt

HAIDT: The most important finding in psychology in the last 50 to 100 years, I would say, is the finding that everything you can measure is heritable. The heritability coefficients vary between 0.3 and 0.6, or 30 to 60 percent of the variance, under some assumptions, can be explained by the genes. It’s the largest piece of variance we can explain.

If you and I were twins separated at birth and raised in different families, our families would pick which religions we were raised in and they would pick how often we go to church or synagogue, but once we’re out on our own, we’re going to both converge on our brain’s natural level of religiosity.

Same with politics, whether you’re on the right or left is not determined by your genes, but you’re predisposed. You find variety and diversity and challenging authority really exciting. If that’s the way you were as a kid, even if you’re raised in a conservative household, once you go to college you’re going to be attracted to more radical left‑wing politics.

[---]

COWEN: Reading through a lot of your past work, which I did to prepare for this conversation. This struck me, and I didn’t expect it to be the case, but at times I was thinking more of Claude Lévi-Strauss, the anthropologist, than I thought I was going to. Underrated or overrated?

HAIDT: Again, well I can’t say, because again it depends where you are. In symbolic anthropology I think he is still quite highly rated, outside of that I think very few people know about him. I read a little bit about, a little bit of his work when I was a postdoc in Chicago with Richard Shweder.

What I remember is just the idea of interpreting cultures as people are making symbols, we live in a rich symbolic world, a world of narrative, we need to interpret those, that I think is quite right, and that’s again what I love about cultural anthropology is it gives you a way of interpreting cultures.
Where it then leads you to deny that there’s also human nature that is based in our evolution, then it becomes a problem. But I just can’t remember which part of those is attributable to Lévi-Strauss.

- More Here

Quote of the Day

To find out what happens to a system when you interfere with it you have to interfere with it (not just passively observe it).

- George E.P. Box