Ex Machina

The story revolves around a very nice upgrade to modernize Turning test.



Here's the reditt discussion on the Python code shown in the movie

#BlueBook code decryption import sys def sieve(n): x = [1] * n x[1] = 0 for i in range(2,n/2): j = 2 * i while j < n: x[j]=0 j = j+i return x def prime(n,x): i = 1 j = 1 while j <= n: if x[i] == 1: j = j + 1 i = i + 1 return i - 1 x=sieve(10000) code = [1206,301,384,5] key =[1,1,2,2,] sys.stdout.write("".join(chr(i) for i in [73,83,66,78,32,61,32])) for i in range (0,4): sys.stdout.write(str(prime(code[i],x)-key[i])) print

Which when you run with python2.7 you get the following:

ISBN = 9780199226559

Which is the ISBN for the book  Embodiment and the inner life: Cognition and Consciousness in the Space of Possible Minds.

Quote of the Day

Online education also saves the resources associated with context switching. Humans are notoriously bad multitaskers. Each time a high school student has to change classes, she has to quickly stifle the thoughts and questions raised in previous classes to focus on the current class. She has to expend mental resources remembering where the previous session of the current class left off. And when she returns to the class that stimulated the thoughts that had to be stifled, she may not recall them. Far better to focus on—or even to binge on—one subject until she is at a good stopping point.

- ‘Binge Learning’ is Online Education’s Killer App

Wisdom Of The Week

In a 2013 study published in the Journal of Neurophysiology, scientists measured the response from primary visual cortex neurons in macaque monkeys (one of the few animals that see like we do) as they prompted them with chromatic contrasts. They were trying to prove the existing biological model of color perception by testing neuron response after isolating the function of neural channels. If the researchers could see the way the brain mixes colors, they could once and for all find red. But it didn’t work. Instead, “analysis of neuronal contrast—response functions and signal-to-noise ratios yielded no evidence for a special set of ‘cardinal color directions,’ for which visual cortex neurons are particularly sensitive.” Not only couldn’t they find the red-green and blue-yellow channels, nearly half the color neurons also fired in response to brightness changes, suggesting the tripartite channel model is inaccurately simplistic.

Scientific attempts to reduce colors to wavelengths have been equally unsuccessful. If it were simple, then colors as we observe them should match up with what’s called the “surface spectral reflectance,” (SSR) which can be measured with a digital receptor. But if you try to replicate color vision this way, you get far too many colors, and objects lack internal constancy because of the effects of lighting conditions. Where we see shadows, a computer sees a different color. But even when they apply highly sophisticated algorithms for illumination in a 3-D space, researchers have been unable to replicate human levels of color constancy. NYU professor of psychology and neural science Laurence T. Maloney writes that the failure of these SSR models thus far suggests “there are cues present in real scenes that we do not understand.” People are able to use color to judge scenes better than computers and cameras can, and scientists aren’t sure how.

- Review of the new book, Outside Color: Perceptual Science and the Puzzle of Color in Philosophy by M. Chirimuuta

Quote of the Day

IBM Watson is proud to announce a major advance in the transcription of conversational speech. We built a system capable of very low error rates on a popular scientific benchmark that consists of telephone conversations – the NIST Switchboard corpus (“EvalSet-2″). Furthermore, this was achieved by using only  publicly available data (details available on request) to train the underlying models. The performance of our new system – an 8% word error rate – is 36% better than previously reported external results.

- IBM Watson Announcement

Machine Learning - Now Spotting Depression

I'm in a booth with a computer program called Ellie. She's on a screen in front of me. Ellie was designed to diagnose post-traumatic stress disorder and depression, and when I get into the booth she starts asking me questions — about my family, my feelings, my biggest regrets. Emotions seem really messy and hard for a machine to understand. But Skip Rizzo, a psychologist who helped design Ellie, thought otherwise.

When I answer Ellie's questions, she listens. But she doesn't process the words I'm saying. She analyzes my tone. A camera tracks every detail of my facial expressions.
"Contrary to popular belief, depressed people smile as many times as non-depressed people," Rizzo says. "But their smiles are less robust and of less duration. It's almost like polite smiles rather than real, robust, coming from your inner-soul type of a smile."

Ellie compares my smile to a database of soldiers who have returned from combat. Is my smile genuine? Is it forced? Ellie also listens for pauses. She watches to see whether I look off to the side or down. If I lean forward, she notices.

All this analysis seems to work: In studies, Ellie could detect signs of PTSD and depression about as well as a large pool of psychologists.

- More Here

Quote of the Day

Know how to listen and you will profit even from those who talk badly.

- Plutarch

Will Computers Redefine the Roots of Math?

This piece by Kevin Hartnett is one the mindbogglingly brilliant piece I have read this year. Read the whole thing, there is too much math but it definitely gives a great glimpse of what is possible in the future.

For nearly a decade, Voevodsky has been advocating the virtues of computer proof assistants and developing univalent foundations in order to bring the languages of mathematics and computer programming closer together. As he sees it, the move to computer formalization is necessary because some branches of mathematics have become too abstract to be reliably checked by people.

“The world of mathematics is becoming very large, the complexity of mathematics is becoming very high, and there is a danger of an accumulation of mistakes,” Voevodsky said. Proofs rely on other proofs; if one contains a flaw, all others that rely on it will share the error.

This is something Voevodsky has learned through personal experience. In 1999 he discovered an error in a paper he had written seven years earlier. Voevodsky eventually found a way to salvage the result, but in an article last summer in the IAS newsletter, he wrote that the experience scared him. He began to worry that unless he formalized his work on the computer, he wouldn’t have complete confidence that it was correct.

But taking that step required him to rethink the very basics of mathematics. The accepted foundation of mathematics is set theory. Like any foundational system, set theory provides a collection of basic concepts and rules, which can be used to construct the rest of mathematics. Set theory has sufficed as a foundation for more than a century, but it can’t readily be translated into a form that computers can use to check proofs. So with his decision to start formalizing mathematics on the computer, Voevodsky set in motion a process of discovery that ultimately led to something far more ambitious: a recasting of the underpinnings of mathematics.

Quote of the Day

Don't forget the important rule: the secret of happiness is not "being great" - the secret is "growth".

-  James Altucher, The only technique to learn something new

Jim’s Rule of Buts

Jim’s Rule of Buts states, “In any charged conversation, find any statements containing the conjunction ‘but’ and reverse the clauses.”

This is a self-editing rule, and therefore most practical for written communication until you get the hang of it. But once you do, you can start applying it to verbal communication as well, if only because of the disreputable fact that we spend most of the time others are speaking planning what we’re going to say next rather than listening. Or so they say.

The most obvious example of the power of Jim’s Rule of Buts is the classic apology. Compare, “I’m sorry I yelled at you, but what you said made me really angry.” and “What you said made me really angry, but I’m sorry I yelled at you.” As a coordinating conjunction, ‘but’ joins independent and theoretically equal clauses. But in practice, what follows ‘but’ always dominates what precedes it. So if you really want to apologize, and really want to mollify your interlocutor, you really want to make sure the apology itself is in the dominant position. Otherwise, you’re not apologizing; you’re excusing your own conduct.

- More Here

Quote of the Day

Why Brain-to-Brain Communication Is No Longer Unthinkable

Maybe we’re still thinking too small. Maybe an analog to natural language isn’t the killer app for a brain-to-brain interface. Instead, it must be something more global, more ambitious—information, skills, even raw sensory input. What if medical students could download a technique directly from the brain of the world’s best surgeon, or if musicians could directly access the memory of a great pianist? “Is there only one way of learning a skill?” Rao muses. “Can there be a shortcut, and is that cheating?” It doesn’t even have to involve another human brain on the other end. It could be an animal—what would it be like to experience the world through smell, like a dog—or by echolocation, like a bat? Or it could be a search engine. “It’s cheating on an exam if you use your smartphone to look things up on the Internet,” Rao says, “but what if you’re already connected to the Internet through your brain? Increasingly the measure of success in society is how quickly we access, digest and use the information that’s out there, not how much you can cram into your own memory. Now we do it with our fingers. But is there anything inherently wrong about doing it just by thinking?”

Or, it could be your own brain, uploaded at some providential moment and digitally preserved for future access. “Let’s say years later you have a stroke,” says Stocco, whose own mother had a stroke in her 50s and never walked again. “Now, you go to rehab and it’s like learning to walk all over again. Suppose you could just download that ability into your brain. It wouldn’t work perfectly, most likely, but it would be a big head start on regaining that ability.”

- More Here

Quote of the Day

He is richest who is content with the least, for contentment is the wealth of nature.

- Socrates

Thought Vector + Deep Learning = Progress in NLP

Richard Socher, an artificial intelligence scientist at Stanford University, recently developed a program called NaSent that he taught to recognise human sentiment by training it on 12,000 sentences taken from the film review website Rotten Tomatoes.

Part of the initial motivation for developing “thought vectors” was to improve translation software, such as Google Translate, which currently uses dictionaries to translate individual words and searches through previously translated documents to find typical translations for phrases. Although these methods often provide the rough meaning, they are also prone to delivering nonsense and dubious grammar. Thought vectors, Hinton explained, work at a higher level by extracting something closer to actual meaning.
The technique works by ascribing each word a set of numbers (or vector) that define its position in a theoretical “meaning space” or cloud. A sentence can be looked at as a path between these words, which can in turn be distilled down to its own set of numbers, or thought vector.

The “thought” serves as a the bridge between the two languages because it can be transferred into the French version of the meaning space and decoded back into a new path between words.
The key is working out which numbers to assign each word in a language – this is where deep learning comes in. Initially the positions of words within each cloud are ordered at random and the translation algorithm begins training on a dataset of translated sentences.

At first the translations it produces are nonsense, but a feedback loop provides an error signal that allows the position of each word to be refined until eventually the positions of words in the cloud captures the way humans use them – effectively a map of their meanings.

Hinton said that the idea that language can be deconstructed with almost mathematical precision is surprising, but true. “If you take the vector for Paris and subtract the vector for France and add Italy, you get Rome,” he said. “It’s quite remarkable.”

- More Here

Quote of the Day

The key has been to adapt the Silicon Valley start-up culture to industries that had been insulated from disruptive interlopers. Musk set outrageous goals and squeezed unimaginable performance out of his staff. With little money to play with, his companies relied on moving fast and making do. When a SpaceX engineer tells him a supplier has quoted a price of $120,000 for a rocket part, for instance, Musk laughs and says it is no more complicated than a garage-door opener: the engineer eventually finds a way to make the part for $3,900.

- Review of the new book, Elon Musk: How the Billionaire CEO of SpaceX and Tesla is Shaping Our Future by Ashlee Vance

Chimps Have Feelings and Thoughts. They Should Also Have Rights

Thank you Steven Wise, I see you include only Chimps for now since our fellow human apes are too busy thinking about themselves. We all know every species on this planet have feelings and thoughts albeit it cannot be anthropomorphize.

So for centuries, there's been a great legal wall that separates legal things from legal persons. On one hand, legal things are invisible to judges. They don't count in law. They don't have any legal rights. They don't have the capacity for legal rights. They are the slaves. On the other side of that legal wall are the legal persons. Legal persons are very visible to judges. They count in law. They may have many rights. They have the capacity for an infinite number of rights. And they're the masters. Right now, all nonhuman animals are legal things. All human beings are legal persons.

But being human and being a legal person has never been, and is not today, synonymous with a legal person. Humans and legal persons are not synonymous. On the one side, there have been many human beings over the centuries who have been legal things. Slaves were legal things. Women, children, were sometimes legal things. Indeed, a great deal of civil rights struggle over the last centuries has been to punch a hole through that wall and begin to feed these human things through the wall and have them become legal persons.

But alas, that hole has closed up. Now, on the other side are legal persons, but they've never only been limited to human beings. There are, for example, there are many legal persons who are not even alive. In the United States, we're aware of the fact that corporations are legal persons. In pre-independence India, a court held that a Hindu idol was a legal person, that a mosque was a legal person. In 2000, the Indian Supreme Court held that the holy books of the Sikh religion was a legal person, and in 2012, just recently, there was a treaty between the indigenous peoples of New Zealand and the crown, in which it was agreed that a river was a legal person who owned its own riverbed.

Quote of the Day

Anger is an acid that can do more harm to the vessel in which it is stored than to anything on which it is poured.

- Seneca

Wisdom Of The Week

Stephen S. Hall's 2010 book Wisdom: From Philosophy to Neuroscience is one my favorites. I haven't re-read it yet but came across this good summation of what Stephen calls as the “Eight Neural Pillars of Wisdom”:

• Emotional Regulation: the art of coping.
• Knowing What’s Important: the neural mechanism of establishing value and making a judgement.
• Moral Reasoning: the biology of judging right from wrong.
• Compassion: the biology of loving-kindness and empathy.
• Humility: the gift of perspective.
• Altruism: social justice, fairness, and the wisdom of punishment.
• Patience: temptation, delayed gratification and the biology of learning to wait for larger rewards.
• Dealing with Uncertainty: change, ‘meta-wisdom’ and the vulcanization of the human brain. 

And one of my favorite quotes from the book is by Adam Smith who as usual gives us a great insight into human nature:

In a lovely evocation of that timeless fork in the road between material and spiritual well-being, he spoke of two different roads - one of "proud ambition and ostentatious avidity," the other of "humble modestly and equitable justice" - that await our choice. 

Two different models, two different pictures, are held out to us, according to which fashion our own character and behavior; the one more gaudy and glittering in its coloring; the other more correct and exquisitely beautiful in its outline: the one forcing itself upon the notice of every wandering eye; the other attracting the attention of scare any body but most studious and careful observer. 

They are the wise and the virtuous chiefly, a select, though, I am afraid, but a small party, who are the real and steady admirers of wisdom and virtue. The great mob of mankind are the admirers and worshipers, and, what may seem more extraordinary, most frequently the disinterested admirers and worshipers, of wealth and greatness.

What Is Intelligence?

That was the discussion started in my class and to get the conversation started, they added following answers by some great AI researchers.

Dr. Boyang 'Albert' Li provided this link to Pei Wang's paper.  Dr. Li summarized Wang's position in the paper with this quote from the paper:

"Intelligence is the capacity of a system to adapt to its environment while operating with insufficient knowledge and resources."

I also asked Dr. Li to give a personal definition, which he kindly did.  I note that he adds that, for intelligence in general, Wang's remains the best definition.  Here was Li's personal definition:

"My personal definition is probably more like solving difficult problems, or do what humans can do, since these are immediate goals for computational narrative intelligence."

Dr. Michael Helms provided this definition:

"Intelligence is that which we ascribe to a system, for an observed set of system actions under sufficiently varied stochastic conditions, and within a sufficiently complex domain, such that those actions can be interpreted to facilitate the optimization of a self-consistent utility function, taking into account limitations of the systems knowledge and its capability to act, for some definition of sufficiently varied and sufficiently complex that are features of the observer, and not the observed."

Dr. Ashok Goel gave this very thoughtful response:

"What is intelligence? Doesnt that depends on what the meaning of "is" is? Seriously, the question assumes, as do most definitions of intelligence, that there *is* some thing, one specific thing, called intelligence. But what if, like life, like love, intelligence is no one thing with clear boundaries? What if it is just a word we use to denote a complex and intricate ensemble with unclear boundaries that we

do not yet understand? What if once we came to understand intelligence, the question would not make much sense anymore?"

Dr. Swaroop Vattam gave this answer:

"Asking AI researchers what intelligence is is akin to asking a life-sciences researcher what life is. Biology has made a lot of progress without pinning down the definition of life. I think it's the same way for us folks."

******************

I had never thought about this question very clearly and I started tried to define intelligence for the first time and here's my response:

In sprint of this exceptionally interesting class, I would like to add some basic constraints (or representations) for fun before attempting to construct the meaning of intelligence (i.e., if there is meaning):

• I would shed the anthropomorphic view and clearly, include every species on this planet to be considered for evaluation. This finding "Squirrels and chipmunks eavesdrop on birds, sometimes adding their own thoughts." which came out this week is a prime example of our limits of knowledge and begs for our epistemological modesty.
• Intelligence and Wisdom are probably different. The line between them is very blurry and sometimes overlaps but outside of those blurriness both are different entities.
• If something that clearly falls under the realm of intelligence wouldn't automatically exclude itself just because we decided linguistically to add "Artificial" in front of it to make us comfortable or something of that sort. This one could be distributed cognition and similar to ants, eusocial theory of evolution.
• Finally, I wouldn't group intelligence at species level but at an individual level in each species. I think, grouping at species level is one of the crucial reasons we tend anthropomorphize. Asperger's syndrome is one of the clear indicators of this phenomena. Under this criteria, capacity for future intelligence will be in a completely different domain and should not be confused with an entity which has already displayed its intelligence.
• To stress the above point, mastering existing knowledge is not the same as creating new knowledge. As Peter Thiel points out in Zero to One - "Doing what we already know how to do takes the world from 1 to n, adding more of something familiar. But every time we create something new, we go from 0 to 1. The act of creation is "singular", as is the moment of creation, and the result is something fresh and strange."

Drawing from above highly simplified representations and the ideas summarized eloquently in E.O.Wilson's Consilience:Unity of Knowledge, the closet definition of intelligence I can think of is:

An entity can be considered intelligence if it has used it's existing knowledge repository to create or discover new knowledge which was previously unknown to it and does so in a stochastic environment.

Quote of the Day

Beware the barrenness of a busy life.

- Socrates

Quote of the Day

And we had damned well better not forget it, in a fog of faux remorseful “Knowing what we now know...” sanitized history.

- James Fallows, The Right and Wrong Questions About the Iraq War

People Are Blaming Algorithms For The Cruelty of Bureaucracy

Algorithms are impersonal, biased, emotionless, and opaque because bureaucracy and power are impersonal, emotionless, and opaque and often characterized by bias, groupthink, and automatic obedience to procedure. In analyzing algorithms, critics merely rediscover one of the oldest and most fundamental issues in social science: the pathology of bureaucracy and structural authority and power. Algorithms are not products of a “black box”; rather, they are the computational realization and machine representation of the “iron cage” of bureaucracy. As sociologist Max Weber noted a century ago, bureaucratic rationality consists of hierarchal authority, impersonal decision-making, codified rules of conduct, promotion based on achievement, specialized division of labor, and efficiency. Any kind of rational, cost/benefit thinking, however, presupposes a goal or objective. That goal may not always be in the interests of the individuals that a bureaucracy governs. Moreover, institutions may default to standard operating procedures even when doing so has counterproductive, harmful, and even absurd implications.

Today’s automation and data-driven programs are merely the latest and greatest of a long movement toward the automation, optimization, and control of social life—and this story begins not with a revolution in computing but a revolution in human understanding of social relations and governance. Sometime around the mid-19th century, scholars believe, the basic technology of social relations and governance shifted dramatically. Fueled by economic and philosophical thinking and sociological changes, some argue, the notion of society was upended and replaced with notions of utility, preference, and collective welfare. The notion of collective society was replaced by the image of an autonomous and self-interested individual who made rational choices to attain the objectively best outcome for him- or herself. Similarly, political governance became dominated by attempts to achieve social and political control through quantification, measurement, and rational bureaucratic processes. Such “scientific” measures would allow authorities to treat society as a machine that they could program and manipulate to achieve desired objectives. This is not a criticism as much as a simple historical and sociological observation. Such a shift also explains, after all, the origin, nature, and folkways of modern bureaucracy and how governmental and corporate metaphorical machines became slowly infiltrated by real machines.

Modern bureaucracy, as a form of power, was originally justified in terms of scientific and enlightened governance of society and optimization and control of corporate business processes. Another feature of bureaucratic and technocratic thinking was the assumption of paternalism. Whether it was early 20th-century thinking about the madness of crowds or trendy modern behavioral psychology influenced policy ideas about the importance of “nudges,” reformers believed efficient procedures and mechanisms could be designed to help otherwise hapless individuals make better decisions.

- More Here

Quote of the Day

A very disturbing feature of overconfidence is that it often appears to be poorly associated with knowledge - that is, the more ignorant the individual, the more confident he or she might be.

- Robert Trivers, Deceit and Self-Deception: Fooling Yourself the Better to Fool Others

Knowledge != Understanding

This is an absolute and quantified video of what Daniel Kahneman (& Amos Tversky) spent years researching and wrote in his book Thinking Fast and Slow about our biases:

We can be blind to the obvious, and we are also blind to our blindness.

Quote of the Day

Dr. Greene, working with a student, has also found that “squirrels understand ‘bird-ese,’ and birds understand ‘squirrel-ese.’ ” When red squirrels hear a call announcing a dangerous raptor in the air, or they see such a raptor, they will give calls that are acoustically “almost identical” to the birds, Dr. Greene said.

- Do the squirrels and birds understand each other?

War "Exists In An Outside Moral Universe"

When you're in war, the moral universe you carry with you — the moral experience and baggage you brought into it — is suspended. You just don't bring it with you. It exists in an outside moral universe independent of our own.

Everything makes sense and has its own order, until you leave.

I remember the summer I left for the army. It was 2004. I was 18, about to turn 19, and I was working at a parking garage for a minor league baseball team. Someone came up and said, "This woman's having a heart attack." So I radioed my boss to get an ambulance to wait at the entrance to the garage, and I started moving these cars around, getting them away to clear this path. She came down in her car and was able to get out, and the ambulance was able to grab her and take her to the hospital. Luckily, nothing happened.

I was always a person to visit my grandparents and give them a call. I loved foreign films when I was in high school, and reading history, and not passing high school classes. I thought that's what it was all about.

And then I get to Iraq. And I’m going on raids. Throwing people down in their houses in the middle of the night because I don't know if they're good or bad and we don't know, at that point, if we even have the right house.

I remember clearly tracking mud and human waste through people's houses and getting it on their carpets and their rugs and their beds. And tearing their houses apart. And getting into firefights and probably shooting the wrong people. You can't go down and ask them, right?

I went from being proud that I helped this one woman to that.

Then you leave again. And what do you do with that? How are all those three people, before, during, and after war the same person? All three of them existed in different moral universes.

- More Here

Quote of the Day

Can you ever "solve" disease, unemployment, war, or any other societal herpes? Hell no. All you can hope for is to make them manageable enough to allow people to get on with their lives. That's not cynicism, that's maturity.

- Max Brooks, World War Z: An Oral History of the Zombie War

How Do You Know Somebody is Mature or Not?

• Maturity is when you stop trying to change people, and instead focus on changing yourself.
• Maturity is when you accept people for who they are.
• Maturity is when you understand that everyone is right in their own perspective.
• Maturity is when you learn to "let go".
• Maturity is when you are able to drop "expectations" from a relationship and give for the sake of giving.
• Maturity is when you understand that whatever you do, you do for your own peace.
• Maturity is when you stop proving to the world how intelligent you are.
• Maturity is when you focus on positives in people.
• Maturity is when you do not seek approval from others.
• Maturity is when you stop comparing yourself with others.
• Maturity is when you are at peace with yourself.
• Maturity is when you can differentiate between "need" and "want, and you can you can let go of your wants.
• Maturity is when you stop attaching "happiness" to material things.

- Brilliant answers @ Quora

First Warm-Blooded Fish Identified

Wegner is a fisheries biologist at NOAA Fisheries’ Southwest Fisheries Science Center in La Jolla. He first became aware that opah were unlike other fish when a colleague, Owyn Snodgrass, collected a sample of an opah’s gill tissue.

Wegner noticed that the tissue had blood vessels to carry warm blood into the fish’s gills. The blood vessels then wound around those carrying cold blood back to the body core after absorbing oxygen from water. Engineers call this a “counter-current heat exchange.”

In this case, the car radiator-like system means that warm blood leaving the fish’s body core helps to heat up cold blood returning from the respiratory surface of the gills where it absorbs oxygen.

Opah live up to 1000 feet beneath the ocean’s surface in very cold, dimly lit waters, making this discovery all the more remarkable.

The researchers found that the industrious fish constantly flap its fins, which generate body heat. The flapping also speeds up the opah’s metabolism, movement and reaction times.

- More Here

Quote of the Day

Critics who treat 'adult' as a term of approval, instead of as a merely descriptive term, cannot be adult themselves. To be concerned about being grown up, to admire the grown up because it is grown up, to blush at the suspicion of being childish; these things are the marks of childhood and adolescence. And in childhood and adolescence they are, in moderation, healthy symptoms. Young things ought to want to grow. But to carry on into middle life or even into early manhood this concern about being adult is a mark of really arrested development. When I was ten, I read fairy tales in secret and would have been ashamed if I had been found doing so. Now that I am fifty I read them openly. When I became a man I put away childish things, including the fear of childishness and the desire to be very grown up.

- C.S. Lewis

Quote of the Day

The inevitable hypocrisy, which is associated with the all the collective activities of the human race, springs chiefly from this source: that individuals have a moral code which makes the actions of collective man an outrage to their conscience. They therefore invent romantic and moral interpretations of the real facts, preferring to obscure rather than reveal the true character of their collective behavior. Sometimes they are as anxious to offer moral justifications for the brutalities from which they suffer as for those which they commit. The fact that the hypocrisy of man's group behavior... expresses itself not only in terms of self-justification but in terms of moral justification of human behavior in general, symbolizes one of the tragedies of the human spirit: its inability to conform its collective life to its individual ideals. As individuals, men believe they ought to love and serve each other and establish justice between each other. As racial, economic and national groups they take for themselves, whatever their power can command.

The naïve faith of the proletarian is the faith of the man of action. Rationality belongs to the cool observers. There is of course an element of illusion in the faith of the proletarian, as there is in all faith. But it is a necessary illusion, without which some truth is obscured. The inertia of society is so stubborn that no one will move against it, if he cannot believe that it can be more easily overcome than is actually the case.

- Reinhold Niebuhr, Moral Man and Immoral Society

Wisdom Of The Week

Most researchers agree that many challenges remain in the quest to build a practical quantum computer. In a paper published in Nature, Chow's team described its progress in tackling one of those challenges, by designing a way to detect errors on a two-by-two lattice of superconducting quantum bits.

If there are errors in the underlying data stored by any computer then the results of its calculations will be incorrect. Errors rarely occur in the transistors used to build classical computers, and when they do, they are automatically fixed by various error-correction schemes.
Quantum computers are a different story. "Qubits are really susceptible to errors," says Chow. "They can be affected by heat. They can be affected by noise in the environment. They can be affected by stray electromagnetic couplings."

Only one type of error can occur in the information stored by a classical computer, a bit-flip, where a 0 is mistakenly flipped to 1 or vice versa. Qubits suffer from bit-flits but also from phase errors. A superposition state of a qubit, or having the values 0 and 1 at the same time, is denoted as "0+1". A phase error flips the sign of the phase relationship between 0 and 1.

"0+1 and 0-1 are very different in terms of the information that’s in that state," explains Chow. "We have to think of it as an arrow pointing along a sphere. You can point at the south pole and that’s a zero. You can also be pointing at the north pole and that’s a one. You can point along the equator and that’s a 0+1 but if you point to the exact opposite side of that equator, it’s a 0-1." To make things even more complicated, quantum error correction schemes have to avoid measuring qubit data directly since that will cause the value to collapse.

IBM’s new error-detection scheme is based on a technique called surface code which spreads quantum information across many qubits. Two syndrome (or measurement) qubits are coupled with two code, or data qubits. One syndrome qubit reveals whether a bit-flip error has occurred to either of the code qubits, while the other syndrome qubit flags the case where a phase-flip error occurred, all without directly measuring either of the qubits.

But error correction is just one of the obstacles on the rocky road to building a practical quantum computer.

One professor posted a lengthy list of those obstacles on Quora.

- The Golden Age Of Quantum Computing Is Upon Us (Once We Solve These Tiny Problems)

The Book That Inspired Raghu Rajan

Raghuram Rajan is a man known for questioning orthodoxies, notably in a 2005 speech as Chief Economist of the International Monetary Fund, in which he was credited with foreseeing important elements of the global financial crisis. After being appointed as Governor of India’s central bank in 2013, however, Rajan has been more circumspect, pushing a quietly radical agenda of financial openness, but not allowing himself to be painted as a proselytising liberal, out of step with his cautious paymasters in New Delhi. Yet Rajan’s intellectual curiosity—which won him a place in the top 10 of Prospect’s 2014 list of leading world thinkers—still shows through in occasional, thoughtful speeches that stray far outside his remit as central bank head. A few days before Modi’s Independence Day remarks in August, Rajan made just one such intervention, laying out “a hypothesis on the persistence of crony capitalism” in India. His remarks made no mention of Modi. But his intent was clear enough: to explain the structural problems any government wanting to rid India of corruption needs to tackle, especially those rooted in its local democracy.

India’s public services are threadbare, Rajan argued. Citizens cannot rely on the state. Welfare entitlements supposedly provided for the poor mysteriously never appear. State schools and hospitals are dismal. Public goods like water and road repairs are absent too. “This is where the crooked but savvy politician fits in,” Rajan said. “While the poor do not have the money to ‘purchase’ public services that are their right, they have a vote that the politician wants. The politician does a little bit to make life a little more tolerable for his poor constituents—a government job here, a [police report] registered there, a land right honored somewhere else. For this, he gets the gratitude of his voters, and more important, their vote.”

Rajan explained his thesis to me not long afterwards, sitting in his favoured meeting room on the 18th floor of the Reserve Bank of India, where the large windows provide sweeping views over the hubbub of downtown Mumbai below. His inspiration had come during his time in academia, he explained , and in particular from reading Richard Hofstadter, the US liberal historian. Hofstadter’s book The Age of Reform examined the path taken by America, as it first endured and eventually overcame its own era of “robber barons” in the late 19th century. This was a period in which the US looked oddly like contemporary India—a “gilded age” marked by rapid industrial growth, helter-skelter urbanisation, wealthy tycoons and rampant municipal corruption.
 
Hofstadter, Rajan said, had shown that, in the US, a combination of corruption crack-downs and basic improvements in public services eventually reasserted good governance, culminating in the New Deal of the 1930s. But in contemporary India, at the local level at least, there are few mechanisms of accountability to stop political leaders extorting cash to fund services that should be provided by the state. “Obviously, to do some of this, some of these guys need resources,” Rajan told me. “And where do you get resources from? You get resources from business. So it’s sort of an unholy nexus, so to speak. Poor public services, politician fills the gap; politician gets the resources from the businessman, politician gets re-elected by the electorate for whom he’s filling the gap; and electorate turns a blind eye to the deals done with the businessman.”

- More Here

Quote of the Day

Those who can make you believe absurdities, can make you commit atrocities.

- Voltaire

22 Memorable Quotes From The New Elon Musk Book

Great quotes from Ashlee Vance’s new book, Elon Musk: Tesla, SpaceX and the Quest for a Fantastic Future:

• We’re all hanging out in this cabana at the Hard Rock Cafe, and Elon is there reading some obscure Soviet rocket manual that was all moldy and looked like it had been bought on eBay.” — Kevin Hartz, an early PayPal investor, describing an outing in Las Vegas that was intended as a time to celebrate the company’s success.
• “He’s kind of homeless, which I think is sort of funny. He’ll e-mail and say, ‘I don’t know where to stay tonight. Can I come over?’ I haven’t given him a key or anything yet.” — Google chief executive Larry Page on Elon Musk, who owns a home in Los Angeles but doesn’t have a place in Silicon Valley, which he visits weekly for his work at Tesla.
• “That’s my lesson for taking a vacation: vacation will kill you.” — Elon Musk, who nearly died in 2000 from a malaria infection following a trip to Brazil and South Africa.

Quote of the Day

If we have learned one thing from the history of invention and discovery, it is that, in the long run  and often in the short one — the most daring prophecies seem laughably conservative.

- Arthur C. Clarke, The Exploration of Space

Spring Time !!

Quote of the Day

At this point in my story, you might have the following question: What kind of idiot puts himself in a position to be humiliated in front of a thousand people?

It’s a fair question. The answer is a long one. It will take this entire book to answer it right. The short answer is that over the years I have cultivated a unique relationship with failure. I invite it. I survive it. I appreciate it. And then I mug the shit out of it. Failure always brings something valuable with it. I don’t let it leave until I extract that value.

- Scott Adams, How to Fail at Almost Everything and Still Win Big

Elephant Watch

“They were very well organized,” Sissler-Bienvenu recalled. “Very well armed, very strategic, and they implemented ambushes in military style.” Some of the men were believed to be members of Rizeigat, a nomadic Arab group with ties to the janjaweed and to the Darfuri genocide. They cut pieces from the elephants’ ears to use as gris-gris. The manager of a lodge in Bouba-Njida Park, who encountered a group of the poachers on horseback, recalled, “When you looked at them, they stared straight back at you. They didn’t fear anything from anybody.”

As the killings continued, Sissler-Bienvenu went to the press, and soon Le Monde ran a story featuring photographs of elephants with their trunks missing and their faces cut off. A copy of the newspaper found its way to Cameroon’s President, Paul Biya, who was staying at a hotel overlooking Lake Geneva. He ordered an additional three hundred troops into Bouba-Njida, but they, too, failed to drive out the poachers. In the three months that the poachers were in the park, they killed six hundred and fifty elephants.

After leaving Cameroon, the men split into smaller groups, and four of them apparently detoured north, toward Zakouma National Park, in neighboring Chad, where, just outside the park, they slaughtered nine more elephants before rangers spotted their camp from the air. When the rangers reached the camp, three of the poachers were out hunting; the fourth escaped on foot, and his horse was killed in the crossfire. The rangers found thousands of rounds of ammunition, along with uniforms, documents, and phones linking the men to specific Army and paramilitary units in Sudan. The poachers remained at large. Three weeks later, at dawn, as a group of Muslim park guards knelt in prayer, the poachers shot them all in the back. They seized the guards’ horses and fled to Sudan.

- More Here on the worst of mankind.

A question for Stewart Brand - Why don't we re-program some existing animals to save them first before pursing de-extintion? Why don't we genetically alter Elephants with no tusks and Rhino's with no horns to save these species?

Quote of the Day

A useful definition of intelligence… should include both biological and machine embodiments, and these should span an intellectual range from that of an insect to that of an Einstein, from that of a thermostat to that of the most sophisticated computer system that could ever be built.

- James S. Albus

Quote of the Day

Yet in another way, calculus is fundamentally naive, almost childish in its optimism. Experience teaches us that change can be sudden, discontinuous, and wrenching. Calculus draws its power by refusing to see that. It insists on a world without accidents, where one thing leads logically to another. Give me the initial conditions and the law of motion, and with calculus I can predict the future -- or better yet, reconstruct the past. I wish I could do that now.

- Steven H. Strogatz, The Calculus of Friendship: What a Teacher and a Student Learned about Life While Corresponding about Math

Quote of the Day

After the sorts of winters we have had to endure recently, the spring does seem miraculous, because it has become gradually harder and harder to believe that it is actually going to happen. Every February since 1940 I have found myself thinking that this time winter is going to be permanent. But Persephone, like the toads, always rises from the dead at about the same moment. Suddenly, towards the end of March, the miracle happens and the decaying slum in which I live is transfigured.

- George Orwell, Some Thoughts on the Common Toad

Wisdom Of The Week

Yet an other enlightening post from Farnam Street:

“Love allows us gently, respectfully and intimately to slip into the life of another person or animal or even the earth itself and to know it from the inside. In this way, love can become a way of moral knowing that is as reliable as scientific insight.” 

— Arthur Zajonc

In an interview with Krista Tippett, commenting on this phrase, Zajonc, author of Meditation As Contemplative Inquiry: When Knowing Becomes Love, says:

Now this is again something which as a scientist you can’t prove, so I’m not trying to convince anybody. I’m trying to though speak up on behalf of or for those people for whom when they hear that they go, “I know that place. It doesn’t happen all the time, but I know that place.”

At a certain point William James talks about this when he’s writing about mystical experience. It’s noetic. It’s completely compelling for the person who has it, and it doesn’t change anything for the two of you.

To me it’s like teaching. When I’m teaching a class and I’m up at the blackboard, and I’m having my epiphanic moment in front of some differential equation and the students are all looking at me cross-eyed.

…but then you can see the one in the back all of a sudden just got it. Then the one in the front goes, “Oh, I see that, too.” In other words, it can be contagious, but each one has to do it on their own. It’s a moment of insight. Knowledge is not something you can just move across the table, and the other person has it. It’s an invitation to exploration to think, to ideate.

Then there’s that “Aha.” I think you could say that the moment I’m describing there is a moral analog of that moment. Sometimes it happens at the hand of a teacher. You might say a moral teacher or something of that or a moral dilemma that you’re in the middle of and you just can’t see your way through.

Then you make your steps and find that place where all of a sudden it gets clear. That doesn’t mean you can’t make mistakes. Somehow people think because you can make mistakes. To me if you can make a mistake then you can also not make a mistake. They come with each other.

Quote of the Day

Sweet are the thoughts that savour of content, The quiet mind is richer than a crown...

- Robert Greene

Quote of the Day

I remember Bob saying, 'Some people who believe in God are good, and some people who believe in God are not good. So where does that leave you?' He had looked around and decided that religion is responsible for a lot of trouble in the world.' Noyce, always pushing against the limits of accepted knowledge, told Bowers that what bothered him most about organized religions was that 'people don't think in churches.

- Leslie Berlin, The Man Behind the Microchip: Robert Noyce and the Invention of Silicon Valley

The First News Report on the L.A. Earthquake Was Written by a Robot

Robo-journalism is often hyped as a threat to journalists’ jobs. Schwencke doesn’t see it that way.  “The way we use it, it’s supplemental. It saves people a lot of time, and for certain types of stories, it gets the information out there in usually about as good a way as anybody else would. The way I see it is, it doesn’t eliminate anybody’s job as much as it makes everybody’s job more interesting.”

Having spent some years as a local news reporter, I can attest that slapping together brief, factual accounts of things like homicides, earthquakes, and fires is essentially a game of Mad Libs that might as well be done by a machine. If nothing else, a bot seems likely to save beleaguered scribes from scouring the thesaurus for synonyms for “blaze.” (Lacking an ego, Quakebot does not concern itself with elegant variation.) And in the case of earthquakes, an algorithm may actually be better at judging the newsworthiness of a particular small quake than your average gumshoe reporter or editor. Quakebot knows, for instance, that a magnitude less than 3.0 means it’s probably not worth freaking out about, a lesson that over-eager wire reporters don't always grasp.

At the same time, Quakebot neatly illustrates the present limitations of automated journalism. It can’t assess the damage on the ground, can’t interview experts, and can’t discern the relative newsworthiness of various aspects of the story. Schwencke notes that it sometimes generates a report based on a false alert or glitch in the USGS system. (Like many of its human counterparts, Quakebot doesn’t double-check its facts before publishing.)

- More Here

Quote of the Day

Bureaucratic categories and organizational boxes do more than simply separate relevant from irrelevant information. They also produce the social optics that policymakers and bureaucrats use to see the world. Before policymakers can act, they first must come to create a definition and understanding of the situation, and that understanding is mediated by how the institution is organized to think. ...How organizations categorize and carve up the world has a profound impact on how policymakers see the world.

- Michael Barnett, Eyewitness to a Genocide: The United Nations and Rwanda

America’s Epidemic of Unnecessary Care - Atul Gawande

Overtesting has also created a new, unanticipated problem: overdiagnosis. This isn’t misdiagnosis—the erroneous diagnosis of a disease. This is the correct diagnosis of a disease that is never going to bother you in your lifetime. We’ve long assumed that if we screen a healthy population for diseases like cancer or coronary-artery disease, and catch those diseases early, we’ll be able to treat them before they get dangerously advanced, and save lives in large numbers. But it hasn’t turned out that way. For instance, cancer screening with mammography, ultrasound, and blood testing has dramatically increased the detection of breast, thyroid, and prostate cancer during the past quarter century. We’re treating hundreds of thousands more people each year for these diseases than we ever have. Yet only a tiny reduction in death, if any, has resulted.

My last patient in clinic that day, Mrs. E., a woman in her fifties, had been found to have a thyroid lump. A surgeon removed it, and a biopsy was done. The lump was benign. But, under the microscope, the pathologist found a pinpoint “microcarcinoma” next to it, just five millimetres in size. Anything with the term “carcinoma” in it is bound to be alarming—“carcinoma” means cancer, however “micro” it might be. So when the surgeon told Mrs. E. that a cancer had been found in her thyroid, which was not exactly wrong, she believed he’d saved her life, which was not exactly right. More than a third of the population turns out to have these tiny cancers in their thyroid, but fewer than one in a hundred thousand people die from thyroid cancer a year. Only the rare microcarcinoma develops the capacity to behave like a dangerous, invasive cancer. (Indeed, some experts argue that we should stop calling them “cancers” at all.) That’s why expert guidelines recommend no further treatment when microcarcinomas are found.

[---]

No one has yet invented a payment system that cannot be gamed. If doctors are rewarded for practicing more conservative medicine, some could end up stinting on care. What if Virginia Mason turns away a back-pain patient who should have gone to surgery? What if Dr. Osio fails to send a heart patient to the emergency room when he should have? What if I recommend not operating on a tiny tumor, saying that it is just a turtle, and it turns out to be a rabbit that bounds out of control?

Proponents point out that people can sue if they think they’ve been harmed, and doctors’ groups can lose their contracts for low-quality scores, which are posted on the Web. But not all quality can be measured. It’s possible that we will calibrate things wrongly, and skate past the point where conservative care becomes inadequate care. Then outrage over the billions of dollars in unnecessary stents and surgeries and scans will become outrage over necessary stents and surgeries and scans that were not performed.

- More Here

Quote of the Day

True character arises from a deeper well than religion. It is the internalization of moral principles of a society, augmented by those tenets personally chosen by the individual, strong enough to endure through trials of solitude and adversity. The principles are fitted together into what we call integrity, literally the integrated self, wherein personal decisions feel good and true. Character is in turn the enduring source of virtue. It stands by itself and excites admiration in others. It is not obedience to authority, and while it is often consistent with and reinforced by religious belief, it is not piety.

- E.O.Wilson, Consilience: The Unity of Knowledge

To Invent the Future, You Must Understand the Past

It’s a beautiful Saturday morning in May, 2003, and I’m sitting next to Jobs on his living room sofa, interviewing him for a book I’m writing. I ask him to tell me more about why he wanted, as he put it, “to smell that second wonderful era of the valley, the semiconductor companies leading into the computer.” Why, I want to know, is it not enough to stand on the shoulders of giants? Why does he want to pick their brains?

“It’s like that Schopenhauer quote about the conjurer,” he says. When I look blank, he tells me to wait and then dashes upstairs. He comes down a minute later holding a book and reading aloud:

He who lives to see two or three generations is like a man who sits some time in the conjurer’s booth at a fair, and witnesses the performance twice or thrice in succession. The tricks were meant to be seen only once, and when they are no longer a novelty and cease to deceive, their effect is gone.

History, Jobs understood, gave him a chance to see — and see through — the conjurer’s tricks before they happened to him, so he would know how to handle them.

Flash forward eleven years. It’s 2014, and I am going to see Robert W. Taylor. In 1966, Taylor convinced the Department of Defense to build the ARPANET that eventually formed the core of the Internet. He went on to run the famous Xerox PARC Computer Science Lab that developed the first modern personal computer. For a finishing touch, he led one of the teams at DEC behind the world’s first blazingly fast search engine — three years before Google was founded.

Visiting Taylor is like driving into a Silicon Valley time machine. You zip past the venture capital firms on Sand Hill Road, over the 280 freeway, and down a twisty two-lane street that is nearly impassable on weekends, thanks to the packs of lycra-clad cyclists on multi-thousand-dollar bikes raising their cardio thresholds along the steep climbs. A sharp turn and you enter what seems to be another world, wooded and cool, the coastal redwoods dense along the hills. Cell phone signals fade in and out in this part of Woodside, far above Buck’s Restaurant where power deals are negotiated over early-morning cups of coffee. GPS tries valiantly to ascertain a location — and then gives up.

When I get to Taylor’s home on a hill overlooking the Valley, he tells me about another visitor who recently took that drive, apparently driven by the same curiosity that Steve Jobs had: Mark Zuckerberg, along with some colleagues at the company he founded, Facebook.

“Zuckerberg must have heard about me in some historical sense,” Taylor recalls in his Texas drawl. “He wanted to see what I was all about, I guess.”

To invent the future, you must understand the past.

I am a historian, and my subject matter is Silicon Valley. So I’m not surprised that Jobs and Zuckerberg both understood that the Valley’s past matters today and that the lessons of history can take innovation further. When I talk to other founders and participants in the area, they also want to hear what happened before. Their questions usually boil down to two: Why did Silicon Valley happen in the first place, and why has it remained at the epicenter of the global tech economy for so long?

I think I can answer those questions.

- Read rest of this fascinating piece by Leslie Berlin - Here

On The Evolution of Machine Learning

DB: Why is a neural network so powerful compared to the traditional linear and non-linear methods that have existed up until now?

RZ: When you have a linear model, every feature is either going to hurt or help whatever you are trying to score. That’s the assumption inherent in linear models. So the model might determine that if the feature is large, then it’s indicative of class 1; but if it’s small, it’s indicative of class 2. Even if you go all the way up to very large values of the feature, or down to very small values of the feature, you will never have a situation where you say, “In this interval, the feature is indicative of class 1; but in another interval it’s indicative of class 2.”

That’s too limited. Say you are analyzing images, looking for pictures of dogs. It might be that only a certain subset of a feature’s values indicate whether it is a picture of a dog, and the rest of the values for that pixel, or for that patch of an image, indicate another class. You can’t draw a line to define such a complex set of relationships. Non-linear models are much more powerful, but at the same time they’re much more difficult to train. Once again, you run into those hard problems from optimization theory. That’s why for a long while we thought that neural networks weren’t good enough, because they would over-fit, or they were too powerful.  We couldn’t do precise, guaranteed optimization on them. That’s why they (temporarily) vanished from the scene.

DB: Within neural network theory, there are multiple branches and approaches to computer learning. Can you summarize some of the key approaches?

RZ: By far the most successful approach has been a supervised approach where an older algorithm, called backpropagation, is used to build a neural network that has many different outputs.

Let’s look at a neural network construction that has become very popular, called Convolutional Neural Networks. The idea is that the machine learning researcher builds a model constructed of several layers, each of which handles connections from the previous layer in a different way.

In the first layer, you have a window that slides a patch across an image, which becomes the input for that layer. This is called a convolutional layer because the patch “convolves”, it overlaps with itself. Then several different types of layers follow. Each have different properties, and pretty much all of them introduce non-linearities.

The last layer has 10,000 potential neuron outputs; each one of those activations correspond to a particular label which identifies the image. The first class might be a cat; the second class might be a car; and so on for all the 10,000 classes that ImageNet has. If the first neuron is firing the most out of the 10,000 then the input is identified as belonging to the first class, a cat.

The drawback of the supervised approach is that you must apply labels to images while training. This is a car. This is a zoo. Etc.

- Interview with Reza Zadeh

Quote of the Day

Linear models tend to define relationships in terms of roles rather than people: the boss rather than the person actually exerting influence. The organic model tends to define relationships in terms of one unique person to another unique person.

- Gerald M. Weinberg, Becoming a Technical Leader: An Organic Problem-Solving Approach

Quote of the Day

The contempt of risk and the presumptuous hope of success, are in no period of life more active than at the age at which young people chuse their professions. How little the fear of misfortune is then capable of balancing the hope of good luck, appears still more evidently in the readiness of the common people to enlist as soldiers, or to go to sea, than in the eagerness of those of better fashion to enter into what are called the liberal professions.

- Adam Smith, The Wealth of Nations

Wisdom Of The Week

A must read new piece from Robert Trivers - Vignettes of Famous Evolutionary Biologists, Large and Small!! A master piece stressing the importance of humility, flow of knowledge and all those little traits what makes a better scientist and a better human being.

Bill Hamilton was a naturalist of legendary knowledge, especially of insects, but he was also an acute observer of human behavior, right down to the minutiae of your own actions in his presence. Had I noticed, he asked, that lopsided facial expressions in humans are usually male? No, but I have seen it a hundred times since then. He was an evolutionist to the core, and was always heartened by news of fellow evolutionists enjoying some reproductive success. In a similar spirit I take joy in the lives of his three daughters, Helen, Ruth and Rowena, not to mention his many surviving siblings. But the loss of this ‘gentle giant’ is very great. Bill died at the age of 63 on 7 March 2000, from complications after contracting malaria during fieldwork in the Congo in January, work which was designed to locate more exactly the chimpanzee populations that donated HIV-1 to humans, as well as the mode of transmission. This was in service of a theory of HIV-1 spread into East African children via polio vaccination, one I regarded as doubtful from the outset and now firmly disproved, so in one sense, he died in service of trying to prove a falsehood, but he was strong in mind, body and spirit, with many new projects and thoughts under way, and he has been sorely missed ever since.

Bill chose to describe his preferred burial and its aftermath in biologically vivid and poetic terms. He would die in the Brazilian rain forest, his body to be scavenged by burying beetles so that he would later fly out as buzzing beetles “into the Brazilian wilderness between the stars”. But it was not to be. He died in the UK and was buried in Wytham at Oxford and it took the love of the second half of his wife, Luisa, to add her poetry, drawing on his bacterial/cloud/dispersal vision so that “eventually a drop of rain will join you to the flooded forest of the Amazon”.

I am no W.D. and my burial plan is very simple. If dead outside of Jamaica kindly cremate me—inexpensive and no place to point to. If in Jamaica dig a circular hole beneath my favorite large pimento tree, three feet wide and preferably ten feet deep and drop me head-first into the hole. Throw in some dirt and call it a day—no plaques please. I will not become a bright buzzing burrowing beetle or bacterial cloud, just a few more pimento berries when in season. I add the details on positioning my body mostly to annoy my Jamaican friends. They think I should be resting comfortably on my side in a conventional coffin, but if my way—why not standing up?—the strain on my neck upside down is too much for them to bear. I tell them all the nutritional goodness now is in my brain and upper body, hardly a thing of value is below my waist—they can trust me on that—so let’s go deepest with the best.

Quote of the Day

Where do America's most racist people live? "The rural Northeast and South," suggests a new study just published in PLOS ONE.

- Not Everyone in this Country is Nice

Quote of the Day

The best people and organizations have the attitude of wisdom: The courage to act on what they know right now and the humility to change course when they find better evidence.

- Robert Sutton