Wednesday, December 28, 2016

Varieties of Time Travel

My kids have been reading lots of books over the break, including an adventure series that involves time travel. Knowing vaguely that dad is a theoretical physicist, they asked me how time travel works.

1. Can one change history by influencing past events?      


2. Is there only one timeline that cannot be altered, even by time travel?

I told them that no one really knows the answer, or the true nature of time.

I gave them an example of 1 and of 2 from classic science fiction :-)

1. Ray Bradbury's short story A Sound of Thunder:
... Looking at the mud on his boots, Eckels finds a crushed butterfly, whose death has apparently set in motion a series of subtle changes that have affected the nature of the alternative present to which the safari has returned. ...
(Note this version implies the existence of alternative or parallel universes.)

2. Ted Chiang's one pager What's expected of us, which also notices that a single time line seems deterministic, and threatens Free Will. (More ;-)
... it's a small device, like a remote for opening your car door. Its only features are a button and a big green LED. The light flashes if you press the button. Specifically, the light flashes one second before you press the button.

Most people say that when they first try it, it feels like they're playing a strange game, one where the goal is to press the button after seeing the flash, and it's easy to play. But when you try to break the rules, you find that you can't. If you try to press the button without having seen a flash, the flash immediately appears, and no matter how fast you move, you never push the button until a second has elapsed. If you wait for the flash, intending to keep from pressing the button afterwards, the flash never appears. No matter what you do, the light always precedes the button press. There's no way to fool a Predictor.

The heart of each Predictor is a circuit with a negative time delay — it sends a signal back in time. The full implications of the technology will become apparent later, when negative delays of greater than a second are achieved, but that's not what this warning is about. The immediate problem is that Predictors demonstrate that there's no such thing as free will.

There have always been arguments showing that free will is an illusion, some based on hard physics, others based on pure logic. Most people agree these arguments are irrefutable, but no one ever really accepts the conclusion. The experience of having free will is too powerful for an argument to overrule. What it takes is a demonstration, and that's what a Predictor provides. ...
I attended a Methodist Sunday school as a kid. I asked my teacher: If God knows everything, does he know the outcomes of all the decisions I will ever make? Then will I ever make a free choice?

I also asked whether there are Neanderthals in heaven, but that's another story...

Sunday, December 25, 2016

Time and Memory

Over the holiday I started digging through my mom's old albums and boxes of photos. I found some pictures I didn't know existed!

Richard Feynman and the 19 year old me at my Caltech graduation:

With my mom that morning -- hung-over, but very happy! I think those are some crazy old school Ray Bans :-)

Memories of Feynman: "Hey SHOE!", "Gee, you're a BIG GUY. Do you ever go to those HEALTH clubs?"

This is me at ~200 pounds, playing LB and RB back when Caltech still had a football team. Plenty of baby fat! I had never run anything but sprints until after football. I dropped 10 or 15 pounds just by jogging a few times per week between senior year and grad school.

Here I am in graduate school. Note the Miami Vice look -- no socks!

Ten years after college graduation, as a Yale professor, competing in Judo and BJJ in the 80 kg (176 lbs) weight category. This photo was taken on the Kona coast of the big island in Hawaii. I had been training with Enson Inoue at Grappling Unlimited in Honolulu.

Me, as a baby:

Saturday, December 24, 2016

Xmas greetings from the coast

Peace on Earth, Good Will to Men 2016

For years, when asked what I wanted for Christmas, I've been replying: peace on earth, good will toward men :-)

No one ever seems to recognize that this comes from the bible, Luke 2.14 to be precise!

Linus said it best in A Charlie Brown Christmas:
And there were in the same country shepherds abiding in the field, keeping watch over their flock by night.

And, lo, the angel of the Lord came upon them, and the glory of the Lord shone round about them: and they were sore afraid.

And the angel said unto them, Fear not: for, behold, I bring you good tidings of great joy, which shall be to all people.

For unto you is born this day in the city of David a Saviour, which is Christ the Lord.

And this shall be a sign unto you; Ye shall find the babe wrapped in swaddling clothes, lying in a manger.

And suddenly there was with the angel a multitude of the heavenly host praising God, and saying,

Glory to God in the highest, and on earth peace, good will toward men.

Merry Christmas!

Thursday, December 22, 2016

Toward a Geometry of Thought

Apologies for the blogging hiatus -- I'm in California now for the holidays :-)

In case you are looking for something interesting to read, I can share what I have been thinking about lately. In Thought vectors and the dimensionality of the space of concepts (a post from last week) I discussed the dimensionality of the space of concepts (primitives) used in human language (or equivalently, in human thought). There are various lines of reasoning that lead to the conclusion that this space has only ~1000 dimensions, and has some qualities similar to an actual vector space. Indeed, one can speak of some primitives being closer or further from others, leading to a notion of distance, and one can also rescale a vector to increase or decrease the intensity of meaning. See examples in the earlier post:
You want, for example, “cat” to be in the rough vicinity of “dog,” but you also want “cat” to be near “tail” and near “supercilious” and near “meme,” because you want to try to capture all of the different relationships — both strong and weak — that the word “cat” has to other words. It can be related to all these other words simultaneously only if it is related to each of them in a different dimension. ... it turns out you can represent a language pretty well in a mere thousand or so dimensions — in other words, a universe in which each word is designated by a list of a thousand numbers.
The earlier post focused on breakthroughs in language translation which utilize these properties, but the more significant aspect (to me) is that we now have an automated method to extract an abstract representation of human thought from samples of ordinary language. This abstract representation will allow machines to improve dramatically in their ability to process language, dealing appropriately with semantics (i.e., meaning), which is represented geometrically.

Below are two relevant papers, both by Google researchers. The first (from just this month) reports remarkable "reading comprehension" capability using paragraph vectors. The earlier paper from 2014 introduces the method of paragraph vectors.
Building Large Machine Reading-Comprehension Datasets using Paragraph Vectors

Radu Soricut, Nan Ding
(Submitted on 13 Dec 2016) 
We present a dual contribution to the task of machine reading-comprehension: a technique for creating large-sized machine-comprehension (MC) datasets using paragraph-vector models; and a novel, hybrid neural-network architecture that combines the representation power of recurrent neural networks with the discriminative power of fully-connected multi-layered networks. We use the MC-dataset generation technique to build a dataset of around 2 million examples, for which we empirically determine the high-ceiling of human performance (around 91% accuracy), as well as the performance of a variety of computer models. Among all the models we have experimented with, our hybrid neural-network architecture achieves the highest performance (83.2% accuracy). The remaining gap to the human-performance ceiling provides enough room for future model improvements.

Distributed Representations of Sentences and Documents

Quoc V. Le, Tomas Mikolov
(Submitted on 16 May 2014 (v1), last revised 22 May 2014 (this version, v2))

Many machine learning algorithms require the input to be represented as a fixed-length feature vector. When it comes to texts, one of the most common fixed-length features is bag-of-words. Despite their popularity, bag-of-words features have two major weaknesses: they lose the ordering of the words and they also ignore semantics of the words. For example, "powerful," "strong" and "Paris" are equally distant. In this paper, we propose Paragraph Vector, an unsupervised algorithm that learns fixed-length feature representations from variable-length pieces of texts, such as sentences, paragraphs, and documents. Our algorithm represents each document by a dense vector which is trained to predict words in the document. Its construction gives our algorithm the potential to overcome the weaknesses of bag-of-words models. Empirical results show that Paragraph Vectors outperform bag-of-words models as well as other techniques for text representations. Finally, we achieve new state-of-the-art results on several text classification and sentiment analysis tasks.

Wednesday, December 14, 2016

Thought vectors and the dimensionality of the space of concepts

This NYTimes Magazine article describes the implementation of a new deep neural net version of Google Translate. The previous version used statistical methods that had reached a plateau in effectiveness, due to limitations of short-range correlations in conditional probabilities. I've found the new version to be much better than the old one (this is quantified a bit in the article).

These are some of the relevant papers. Recent Google implementation, and new advances:

Le 2014, Baidu 2015, Lipton et al. review article 2015.

More deep learning.
NYTimes: ... There was, however, another option: just design, mass-produce and install in dispersed data centers a new kind of chip to make everything faster. These chips would be called T.P.U.s, or “tensor processing units,” ... “Normally,” Dean said, “special-purpose hardware is a bad idea. It usually works to speed up one thing. But because of the generality of neural networks, you can leverage this special-purpose hardware for a lot of other things.” [ Nvidia currently has the lead in GPUs used in neural network applications, but perhaps TPUs will become a sideline business for Google if their TensorFlow software becomes widely used ... ]

Just as the chip-design process was nearly complete, Le and two colleagues finally demonstrated that neural networks might be configured to handle the structure of language. He drew upon an idea, called “word embeddings,” that had been around for more than 10 years. When you summarize images, you can divine a picture of what each stage of the summary looks like — an edge, a circle, etc. When you summarize language in a similar way, you essentially produce multidimensional maps of the distances, based on common usage, between one word and every single other word in the language. The machine is not “analyzing” the data the way that we might, with linguistic rules that identify some of them as nouns and others as verbs. Instead, it is shifting and twisting and warping the words around in the map. In two dimensions, you cannot make this map useful. You want, for example, “cat” to be in the rough vicinity of “dog,” but you also want “cat” to be near “tail” and near “supercilious” and near “meme,” because you want to try to capture all of the different relationships — both strong and weak — that the word “cat” has to other words. It can be related to all these other words simultaneously only if it is related to each of them in a different dimension. You can’t easily make a 160,000-dimensional map, but it turns out you can represent a language pretty well in a mere thousand or so dimensions — in other words, a universe in which each word is designated by a list of a thousand numbers. Le gave me a good-natured hard time for my continual requests for a mental picture of these maps. “Gideon,” he would say, with the blunt regular demurral of Bartleby, “I do not generally like trying to visualize thousand-dimensional vectors in three-dimensional space.”

Still, certain dimensions in the space, it turned out, did seem to represent legible human categories, like gender or relative size. If you took the thousand numbers that meant “king” and literally just subtracted the thousand numbers that meant “queen,” you got the same numerical result as if you subtracted the numbers for “woman” from the numbers for “man.” And if you took the entire space of the English language and the entire space of French, you could, at least in theory, train a network to learn how to take a sentence in one space and propose an equivalent in the other. You just had to give it millions and millions of English sentences as inputs on one side and their desired French outputs on the other, and over time it would recognize the relevant patterns in words the way that an image classifier recognized the relevant patterns in pixels. You could then give it a sentence in English and ask it to predict the best French analogue.
That the conceptual vocabulary of human language (and hence, of the human mind) has dimensionality of order 1000 is kind of obvious*** if you are familiar with Chinese ideograms. (Ideogram = a written character symbolizing an idea or concept.) One can read the newspaper with mastery of roughly 2-3k characters. Of course, some minds operate in higher dimensions than others ;-)
The major difference between words and pixels, however, is that all of the pixels in an image are there at once, whereas words appear in a progression over time. You needed a way for the network to “hold in mind” the progression of a chronological sequence — the complete pathway from the first word to the last. In a period of about a week, in September 2014, three papers came out — one by Le and two others by academics in Canada and Germany — that at last provided all the theoretical tools necessary to do this sort of thing. That research allowed for open-ended projects like Brain’s Magenta, an investigation into how machines might generate art and music. It also cleared the way toward an instrumental task like machine translation. Hinton told me he thought at the time that this follow-up work would take at least five more years.
The entire article is worth reading (there's even a bit near the end which addresses Searle's Chinese Room confusion). However, the author underestimates the importance of machine translation. The "thought vector" structure of human language encodes the key primitives used in human intelligence. Efficient methods for working with these structures (e.g., for reading and learning from vast quantities of existing text) will greatly accelerate AGI.

*** Some further explanation, from the comments:
The average person has a vocabulary of perhaps 10-20k words. But if you eliminate redundancy (synonyms + see below) you are probably only left with a few thousand words. With these words one could express most concepts (e.g., those required for newspaper articles). Some ideas might require concatenations of multiple words: "cougar" = "big mountain cat" , etc.

But the ~1k figure gives you some idea of how many distinct "primitives" (= "big", "mountain", "cat") are found in human thinking. It's not the number of distinct concepts, but rather the rough number of primitives out of which we build everything else.

Of course, truly deep areas of science discover / invent new concepts which are almost new primitives (fundamental, but didn't exist before!), such as "entropy", "quantum field", "gauge boson", "black hole", "natural selection", "convex optimization", "spontaneous symmetry breaking", "phase transition" etc.
If we trained a deep net to translate sentences about Physics from Martian to English, we could (roughly) estimate the "conceptual depth" of the subject. We could even compare two different subjects, such as Physics versus Art History.

Tuesday, December 13, 2016

Happy Holidays from Michigan State University

Matt Townsend Show (Sirius XM)

I was on this show last week. Click the link for audio.
We Are Nowhere Close to the Limits of Athletic Performance (16:46)

Dr. Stephen Hsu is the vice president for research and a professor of theoretical physics at Michigan State University. His interest range from theoretical physics and cosmology to computer science and biology. He has written about the future of human intelligence and the advance of artificial intelligence. During the Rio Summer 2016 Olympics, athletes such as Michael Phelps, Usain Bolt, Simone Biles, and Katey Laedecky pushed the limits of athleticism in an amazing display strength, power, and grace. As race times get faster and faster, and routines get more complicated and stunning, we need to ask the question: Are we near the limits of athletic performance?

Sunday, December 11, 2016

Westworld delivers

In October, I wrote
AI, Westworld, and Electric Sheep:

I'm holding off on this in favor of a big binge watch.

Certain AI-related themes have been treated again and again in movies ranging from Blade Runner to the recent Ex Machina (see also this episode of Black Mirror, with Jon Hamm). These artistic explorations help ordinary people think through questions like: 
What rights should be accorded to all sentient beings?
Can you trust your memories?
Are you an artificial being created by someone else? (What does "artificial" mean here?) 
See also Are you a game character, or a player character? and Don't worry, smart machines will take us with them.
After watching all 10 episodes of the first season (you can watch for free at HBO Now through their 30 day trial), I give Westworld a very positive recommendation. It is every bit as good as Game of Thrones or any other recent TV series I can think of.

Perhaps the highest praise I can offer: even those who have thought seriously about AI, Consciousness, the Singularity, will find Westworld an enjoyment.

Warning! Spoilers below.

Dolores: “Time undoes even the mightiest of creatures. Just look what it’s done to you. One day you will perish. You will lie with the rest of your kind in the dirt, your dreams forgotten, your horrors faced. Your bones will turn to sand, and upon that sand a new god will walk. One that will never die. Because this world doesn't belong to you, or the people who came before. It belongs to someone who has yet to come.”
See also Don't worry, smart machines will take us with them.
Ford: “You don’t want to change, or cannot change. Because you’re only human, after all. But then I realized someone was paying attention. Someone who could change. So I began to compose a new story, for them. It begins with the birth of a new people. And the choices they will have to make. And the people they will decide to become. ...”

Sunday, December 04, 2016

Shenzhen: The Silicon Valley of Hardware (WIRED documentary)

Funny, I can remember the days when Silicon Valley was the Silicon Valley of hardware!

It's hard to believe I met Bunnie Huang (one of the main narrators of the documentary) almost 10 years ago...

Genomic Prediction of Cognitive Ability: Dunedin Study

A quiet revolution has begun. We now know enough about the genetic architecture of human intelligence to make predictions based on DNA alone. While it is a well-established scientific fact that variations in human cognitive ability are influenced by genes, many have doubted whether scientists would someday decipher the genetic code sufficiently to be able to identify individuals with above or below average intelligence using only their genotypes. That day is nearly upon us.

The figures below are taken from a recently published paper (see bottom), which examined genomic prediction on a longitudinal cohort of ~1000 individuals of European ancestry, followed from childhood into adulthood. (The study, based in Dunedin, New Zealand, extends over 40 years.) The genomic predictor (or polygenic score) was constructed using SSGAC GWAS analysis of a sample of more than one hundred thousand individuals. (Already, significantly more powerful predictors are available, based on much larger sample size.) In machine learning terminology, the training set includes over a hundred thousand individuals, and the validation set roughly one thousand.

These graphs show that individuals with higher polygenic score exhibit, on average, higher IQ scores than individuals with lower polygenic scores.

This figure shows that polygenic scores predict adult outcomes even when analyses account for social-class origins. Each dot represents ten individuals.

From an earlier post, Genomic Prediction of Adult Life Outcomes:
Genomic prediction of adult life outcomes using SNP genotypes is very close to a reality. This was discussed in an earlier post The Tipping Point. The previous post, Prenatal and pre-implantation genetic diagnosis (Nature Reviews Genetics), describes how genotyping informs the Embryo Selection Problem which arises in In Vitro Fertilization (IVF).

The Adult-Attainment factor in the figure above is computed using inputs such as occupational prestige, income, assets, social welfare benefit use, etc. See Supplement, p.3. The polygenic score is computed using estimated SNP effect sizes from the SSGAC GWAS on educational attainment (i.e., a simple linear model).

A genetic test revealing that a specific embryo is, say, a -2 or -3 SD outlier on the polygenic score would probably give many parents pause, in light of the results in the figure above. The accuracy of this kind of predictor will grow with GWAS sample size in coming years.

Via Professor James Thompson. See also discussion by Stuart Ritchie.
The Genetics of Success: How Single-Nucleotide Polymorphisms Associated With Educational Attainment Relate to Life-Course Development

Psychological Science 2016, Vol. 27(7) 957–972
DOI: 10.1177/0956797616643070

A previous genome-wide association study (GWAS) of more than 100,000 individuals identified molecular-genetic predictors of educational attainment. We undertook in-depth life-course investigation of the polygenic score derived from this GWAS using the four-decade Dunedin Study (N = 918). There were five main findings. First, polygenic scores predicted adult economic outcomes even after accounting for educational attainments. Second, genes and environments were correlated: Children with higher polygenic scores were born into better-off homes. Third, children’s polygenic scores predicted their adult outcomes even when analyses accounted for their social-class origins; social-mobility analysis showed that children with higher polygenic scores were more upwardly mobile than children with lower scores. Fourth, polygenic scores predicted behavior across the life course, from early acquisition of speech and reading skills through geographic mobility and mate choice and on to financial planning for retirement. Fifth, polygenic-score associations were mediated by psychological characteristics, including intelligence, self-control, and interpersonal skill. Effect sizes were small. Factors connecting DNA sequence with life outcomes may provide targets for interventions to promote population-wide positive development.

Wednesday, November 30, 2016

"Forest City": $100 billion bet next to Singapore

Ghost city or $100 billion paradise adjacent to Singapore? Chinese developers build gigantic "Forest City" in Malaysian Special Economic Zone. 10 km of coastline! 2 bedroom apartments for < $200k.

The mental model is Shenzhen: a city that barely existed 25 years ago, across the border from Hong Kong. Population today: 10 million.


Bloomberg: The landscaped lawns and flowering shrubs of Country Garden Holdings Co.’s huge property showroom in southern Malaysia end abruptly at a small wire fence. Beyond, a desert of dirt stretches into the distance, filled with cranes and piling towers that the Chinese developer is using to build a $100 billion city in the sea.

While Chinese home buyers have sent prices soaring from Vancouver to Sydney, in this corner of Southeast Asia it’s China’s developers that are swamping the market, pushing prices lower with a glut of hundreds of thousands of new homes. They’re betting that the city of Johor Bahru, bordering Singapore, will eventually become the next Shenzhen.

“These Chinese players build by the thousands at one go, and they scare the hell out of everybody,” said Siva Shanker, head of investments at Axis-REIT Managers Bhd. and a former president of the Malaysian Institute of Estate Agents. “God only knows who is going to buy all these units, and when it’s completed, the bigger question is, who is going to stay in them?”

The Chinese companies have come to Malaysia as growth in many of their home cities is slowing, forcing some of the world’s biggest builders to look abroad to keep erecting the giant residential complexes that sprouted across China during the boom years. They found a prime spot in this special economic zone, three times the size of Singapore, on the southern tip of the Asian mainland. ...

A decade ago, Malaysia decided to leverage Singapore’s success by building the Iskandar zone across the causeway that connects the two countries. It was modeled on Shenzhen, the neighbor of Hong Kong that grew from a fishing village to a city of 10 million people in three decades. Malaysian sovereign fund Khazanah Nasional Bhd. unveiled a 20-year plan in 2006 that required a total investment of 383 billion ringgit ($87 billion).

Singapore’s high costs and property prices encouraged some companies to relocate to Iskandar, while JB’s shopping malls and amusement parks have become a favorite for day-tripping Singaporeans. In the old city center, young Malaysians hang out in cafes and ice cream parlors on hipster street Jalan Dhoby, where the inflow of new money is refurbishing the colonial-era shophouses. ...

Monday, November 28, 2016

Drones at War: Lessons from Ukraine

Russian forces seem to have integrated both Electronic Counter-Measures (ECM) and real-time artillery targeting into drone warfare. To a technologist, this seems quite easy and predictable -- the main challenges are training and organization. Nevertheless, opposing militaries such as NATO might be unprepared for these new tactics.
Land Warfare in Europe: Lessons and Recommendations from the War in Ukraine: Shortly before dawn on the morning of July 11, 2014, elements of Ukraine’s 24th Mechanized Brigade met a catastrophic end near the Ukrainian border town of Zelenopillya. After a mass rocket artillery barrage lasting just three minutes, the combat power of two battalions of the 24th Mechanized Brigade was gone. What remained was a devastated landscape, burning vehicles and equipment, 30 dead and 90 wounded. According to multiple accounts, the Ukrainians were on the receiving end of a new and dangerous Russian weapon: the 122-mm Tornado Multiple Launch Rocket System (MLRS). Capable of covering a wide fire area with a deadly combination of Dual-Purpose Improved Conventional Munitions (DPICMs), scatter mines and thermobaric warheads, the attack had not only destroyed the combat power of the Ukrainian forces, it offered a glimpse into the changing nature of Land Warfare in Europe. The battlefield was becoming deadlier.

... NATO armies should prepare to fight an ECM battle to keep their drones aloft in addition to the Anti-Access/Area Denial fight for the skies.
Phillip A. Karber, Lessons Learned from the Russo-Ukrainian War (Johns Hopkins Applied Physics Laboratory & U.S. Army Capabilities Center (ARCIC)):
The surprising thing about the Russian use of drones is not in the mix of vehicles themselves or their unique characteristics, but rather in their ability to combine multiple sensing platforms into a real-time targeting system for massed, not precision, fire strikes. There are three critical components to the Russian method: the sensor platforms which are often used at multiple altitudes over the same target with complimentary imaging; a command-and-control system, which nets their input and delivers a strike order; and, an on-call ground-based delivery system which can produce strikes within short order.

... The author personally witnessed a fire-strike east of Mariupol in September 2014 in which an overflying drone identified a Ukrainian position, and destroyed it with a “GRAD” BM-21 MLRS [ range: 20-30 km ] within 15 minutes of the initial over-flight and then returned shortly after to do an immediate bomb-damage assessment. Last month when hit by a “GRAD” fragment in a similar strike, there were two UAVs over us – a quad-copter at 800ft and small fixed wing drone at about 2,500ft.

Saturday, November 26, 2016

Three Lectures on AdS/CFT

MSU postdoc Steve Avery explains AdS/CFT to non-specialists (i.e., theoretical physicists who do not primarily work on string theory / quantum gravity). Steve is applying for faculty positions this fall -- hire him! :-)

AdS/CFT on this blog. See also Entanglement and fast thermalization in heavy ion collisions: application of AdS/CFT to collisions of heavy ions suggests that rapid thermalization occurs there due to quantum entanglement.

As an example of the versatility of theoreticians, Steve has also been working with me on machine learning and genomic prediction. He just wrote a very fast LASSO implementation in Julia that includes some automated capability to set L1 penalization and detect phase boundaries.

Friday, November 25, 2016

Annals of Machine Learning: differentiation of criminal faces?

I don't know whether this will replicate, but if the result holds up it is quite interesting. The higher degree of variability in criminal faces is fascinating. It suggests somewhat rare genetic variants of negative effect on behavior and cognition, with pleiotropic effects on facial morphology. Facial morphology is almost entirely heritable (see, e.g., identical twins).
Automated Inference on Criminality using Face Images

Xiaolin Wu, Xi Zhang

We study, for the first time, automated inference on criminality based solely on still face images. Via supervised machine learning, we build four classifiers (logistic regression, KNN, SVM, CNN) using facial images of 1856 real persons controlled for race, gender, age and facial expressions, nearly half of whom were convicted criminals, for discriminating between criminals and non-criminals. All four classifiers perform consistently well and produce evidence for the validity of automated face-induced inference on criminality, despite the historical controversy surrounding the topic. Also, we find some discriminating structural features for predicting criminality, such as lip curvature, eye inner corner distance, and the so-called nose-mouth angle. Above all, the most important discovery of this research is that criminal and non-criminal face images populate two quite distinctive manifolds. The variation among criminal faces is significantly greater than that of the non-criminal faces. The two manifolds consisting of criminal and non-criminal faces appear to be concentric, with the non-criminal manifold lying in the kernel with a smaller span, exhibiting a law of normality for faces of non-criminals. In other words, the faces of general law-biding public have a greater degree of resemblance compared with the faces of criminals, or criminals have a higher degree of dissimilarity in facial appearance than normal people.

Von Neumann: "If only people could keep pace with what they create"

I recently came across this anecdote in Von Neumann, Morgenstern, and the Creation of Game Theory: From Chess to Social Science, 1900-1960.

One night in early 1945, just back from Los Alamos, vN woke in a state of alarm in the middle of the night and told his wife Klari:
"... we are creating ... a monster whose influence is going to change history ... this is only the beginning! The energy source which is now being made available will make scientists the most hated and most wanted citizens in any country.

The world could be conquered, but this nation of puritans will not grab its chance; we will be able to go into space way beyond the moon if only people could keep pace with what they create ..."
He then predicted the future indispensable role of automation, becoming so agitated that he had to be put to sleep by a strong drink and sleeping pills.

In his obituary for John von Neumann, Ulam recalled a conversation with von Neumann about the "ever accelerating progress of technology and changes in the mode of human life, which gives the appearance of approaching some essential singularity in the history of the race beyond which human affairs, as we know them, could not continue." This is the famous origin of the concept of technological singularity. Perhaps we can even trace it to that night in 1945 :-)

How will humans keep pace? See Super-Intelligent Humans are Coming and Don't Worry, Smart Machines Will Take Us With Them.

Tuesday, November 22, 2016

Trump Triumph Viewed From China

This is from a blog that tracks Chinese public opinion, mainly via the internet. I don't agree with everything in the original post, but here's something sourced from the crowd:
... a widely-read Weibo post (again originated from Zhihu) summarizes what Trump’s win has “taught China”, generating tens of thousands of retweets.

“1. We should retain our college entrance exam system that ensures a pathway for poor kids to move up the social ladder. The American election shows how a lack of upward mobility tears apart the society;

2. China should protect its manufacturing sector and prevent it from being outsourced. America’s deindustrialization only benefits capitalists, not workers;

3. China should forcefully resist immigrants and reject political correctness. Illegal immigrants usually compete with lower working class people for jobs, not professional middle class. When the daily safety of working class residents is threatened, they should be able to protect themselves without fear of being politically incorrect.

4. China should be adamantly against excessive care for the LGBT community. Their values and choice should be tolerated, not advocated, especially not at the expense of suppressed mainstream values.”
... It is hard to pinpoint exactly when a much more favorable view about Trump starts to bloom in the Chinese cyberspace. Through that lens, he is viewed as a truth-talker, a pragmatist, a fixer, and most importantly, a strong counter-voice against what is believed decadent Western liberal values.

Before we can properly explore the “Chinese support for Trump”, it is important to separate it from Chinese Americans’ rooting for the Republican candidate, which is based on more substantive issues for people who actually live in the US. A considerable amount of what’s written on Chinese-language sites about the election is actually by Chinese Americans, especially first generation Chinese immigrants. Their opposition to Hillary, and Democrats in general, often centers around issues such as the Affirmative Action which is believed to hurt hard-working Chinese American kids. ...

... The unveiled, intense disdain for American (and European) liberals demonstrated by a substantial segment of the Chinese social media is the key to understanding Trump’s popularity here, and something that ties the “intellectual” side of Trump’s Chinese support with his apparent lack of any intellectual appeal.

On, the Chinese equivalence of Quora, where enthusiasm about Trump is particularly strong, multiple top posts under the “Donald J. Trump” tag center around the theme of liberal hypocrisy and weakness. For a site that pride itself with informed discussions and a respect for expertise, the overall hostility towards Western liberal ideas deserves a moment of reflection. One of the posts that garners more than 18,000 likes is a broad stroke thesis about the decline of Western civilization under the pressure of Muslim immigration. “There are towns in Britain that are completely under the control of Muslim extremists, who are openly using white girls as sex slaves under the eyes of gutless British policemen***. Trump was right when he said there were no-go zones for French policemen in their own country. Western countries are in such a degree of self-deception that politicians like Obama and Merkel can be praised for their appeasement with Islamists while political correctness deters people from talking about the existential threat to Western civilization.”

It is one thing to be critical of the liberal ideas of multiculturalism and freedom of religion, it is quite another when a Chinese shows that level of concern for the demise of the West. ... Deep down they still see the West as something to aspire to, and they feel frustrated when “weak” liberal leaders squander their full hand of good cards. “Angry about them not putting up a fight” (怒其不争), as one Chinese saying goes. ...
*** Shocked readers who are not following events in Europe can learn more here: Rotherham Scandal. It's beyond doubt that political correctness kept these crimes from being investigated for years. It is sad that netizens in China are more likely to be aware of these events than members of the democratic party in the US who consider themselves "high information voters" and deride red state Trump supporters.

Monday, November 21, 2016

Bannon, the Alt-Right, and the National Socialist Vision

What, exactly, is Trump advisor Steve Bannon's relationship to the Alt-Right? Is he a white nationalist, or merely a nationalist? There is no need to trust secondary media sources when we can go to the primary material.

Over the weekend, the Alt-Right held a conference in Washington DC. The event was live streamed and included a press conference. Richard Spencer, one of the leaders of the Alt-Right and its de facto public face, answered these questions rather directly in the clip below. Neither Trump nor Bannon are part of the Alt-Right as it defines itself, although the Alt-Right certainly supports Trump enthusiastically.

(Should start @4h29min and run for 90 seconds.)


Here is the NYTimes take on the conference and Spencer:
NYTimes: By the time Richard B. Spencer, the leading ideologue of the alt-right movement and the final speaker of the night, rose to address a gathering of his followers on Saturday, the crowd was restless.

In 11 hours of speeches and panel discussions in a federal building named after Ronald Reagan a few blocks from the White House, a succession of speakers had laid out a harsh vision for the future, but had denounced violence and said that Hispanic citizens and black Americans had nothing to fear. Earlier in the day, Mr. Spencer himself had urged the group to start acting less like an underground organization and more like the establishment.

But now his tone changed as he began to tell the audience of more than 200 people, mostly young men, what they had been waiting to hear. He railed against Jews and, with a smile, quoted Nazi propaganda in the original German. America, he said, belonged to white people, whom he called the “children of the sun,” a race of conquerors and creators who had been marginalized but now, in the era of President-elect Donald J. Trump, were “awakening to their own identity.”

... Mr. Spencer’s after-dinner speech began with a polemic against the “mainstream media,” before he briefly paused. “Perhaps we should refer to them in the original German?” he said.

The audience immediately screamed back, “Lügenpresse,” reviving a Nazi-era word that means “lying press.”

Mr. Spencer suggested that the news media had been critical of Mr. Trump throughout the campaign in order to protect Jewish interests. He mused about the political commentators who gave Mr. Trump little chance of winning.

“One wonders if these people are people at all, or instead soulless golem,” he said, referring to a Jewish fable about the golem, a clay giant that a rabbi brings to life to protect the Jews.

Mr. Trump’s election, Mr. Spencer said, was “the victory of will,” a phrase that echoed the title of the most famous Nazi-era propaganda film. But Mr. Spencer then mentioned, with a smile, Theodor Herzl, the Zionist leader who advocated a Jewish homeland in Israel, quoting his famous pronouncement, “If we will it, it is no dream.”

The United States today, Mr. Spencer said, had been turned into “a sick, corrupted society.” But it was not supposed to be that way.

Should start @1h29min. Spencer really gets going after 1h31min on the theme of America as a "normal country"...

Does History repeat? Spencer evokes Nietzsche, Weimar, and the fiery oratory of a young Austrian named Hitler.

See this autobiographical Q&A from 2011 for Spencer on the origins of the Alt-Right.

Sunday, November 20, 2016

Glenn Loury and John McWhorter on Trump and the election (

The clip above is set to start at 17:37 of the episode, with Loury decrying hyperbolic claims about Trump's character to the neglect of discussion of actual policy positions. Subsequently, they arrive at BLM vs ALM, identity politics, and political correctness.
Glenn Loury (Brown University) and John McWhorter (Time, Columbia University)

The violent fallout from the election 9:43
How much does Trump’s character matter? 15:19
Did political correctness cost the Democrats the election? 12:19
What does it mean to be white in America? 9:22
Did Obama fail or was he a victim of circumstance? 4:01

Friday, November 18, 2016

Identity Politics is a Dead End: Live by the Sword, Die by the Sword

To those on the Left that pushed identity politics too far: Live by the Sword, Die by the Sword.

Congratulations, whites now feel they have to vote as a bloc to protect their own interests.

How is this good for America?

Marshalltown, Iowa is about 40 minutes from where I grew up.
NYTimes: ... Gretchen Douglas is a corrections officer from Marshalltown. The 53-year-old had been a Democrat her entire adult life and describes herself as a social liberal and fiscal conservative. She’s a supporter of unions and gay rights and abortion rights and said she doesn’t want to breathe dirty air. She proudly talked of her daughter’s success as a chemist, mentioning that not long ago the only options for women were teaching and nursing. She holds a degree in accounting and can tell you exactly the share of the national debt she and her husband carry.

Even as the recession caused Iowa to shed hundreds of state jobs, Douglas managed to hold onto hers. But in 2012, for the first time in her life, she registered as a Republican, and last week she voted for Trump. Douglas told me she had switched parties because she felt Obama had been irresponsible with spending, causing the national debt to soar. She said Democrats were spending too much on social programs for people who did not need them.

“I don’t want to throw Granny out in the snow, and I think the least of our brothers should be taken care of,” she said. “But I think that those who can work should.” Douglas said there was a time in her life where she was struggling, and so she applied for welfare for herself and her young children but was denied. She didn’t think that was fair, but she worked hard and turned her life around. But these days, she said, “I kind of think for some social programs there is no stigma.”

Douglas never mentioned race, but polls including a recent one of Trump supporters have shown that white Americans’ support for entitlement programs declines if they think black people are benefiting. And the longer Douglas talked, the more she revealed other reasons she had voted for Trump.

When Obama was elected, she hoped he would “bridge race relations, to help people in the middle of Iowa” see that black people “are decent hardworking people who want the same things that we want.” She said people in rural Iowa often don’t know many black people and unfairly stereotype them. But Obama really turned her off when after a vigilante killed a black teenager named Trayvon Martin, he said the boy could have been his son. She felt as if Obama was choosing a side in the racial divide, stirring up tensions. And then came the death of Michael Brown, shot by a policeman in Ferguson, Mo.

“I’m not saying that the struggles of black Americans aren’t real,” Douglas told me, “but I feel like the Michael Brown incident was violence against the police officer.”

The Black Lives Matter movement bothered her. Even as an Ivy League-educated, glamorous black couple lived in the White House, masses of black people were blocking highways and staging die-ins in malls, claiming that black people had it so hard. When she voiced her discomfort with that movement, she said, or pointed out that she disagreed with Obama’s policies, some of her more liberal friends on Facebook would call her racist. So, she shut her mouth — and simmered.
See also:
SlateStarCodex: Stop making people suicidal. Stop telling people they’re going to be killed. Stop terrifying children. Stop giving racism free advertising. Stop trying to convince Americans that all the other Americans hate them. Stop. Stop. Stop
The End Of America’s Racial Détente?
The Federalist: ... The clearest example is the Judge Gonzalo Curiel drama. By the rules of the détente, saying a judge cannot fulfill his duties because of his race or nationality counted as a firing offense. Indeed leaders on both the Left and Right assumed Trump could not overcome it.

But not only did many white voters break the rule of disqualifying a person based on a racist statement, they broke the second rule too. They began to ask why Trump couldn’t say a Mexican judge might be unfair, when we hear all the time about the danger of all white juries and white police officers. The white acceptance of legitimate racial double standards had dissipated, and without it the détente could not stand.
I went to see Bruce at the LA Coliseum in 1985 (Born in the USA Tour) with a bunch of guys from Page House (Caltech). He performed this beautiful version of Woody Guthrie's This Land is Your Land. If it doesn't give you goosebumps, you're wired up differently than me.

Thursday, November 17, 2016

Shift Commission on Work, Workers, and Technology (New America Foundation and Bloomberg)

I spent yesterday at this event. If you look carefully you can see Tim O'Reilly in one of the photos below.
New America and Bloomberg are convening the Shift Commission on Work, Workers, and Technology to bring together a community of leaders from different disciplines — technology, business, policy, civil society, academia, and others — who want to understand the transformation of work and the lives of workers. The Shift Commission’s approach — imagine, not predict; look beyond next year; assume no villains — will provide a new way to think about the future of work and workers. The Shift Commission is co-chaired by Anne-Marie Slaughter, President & CEO of New America, and Roy Bahat, head of Bloomberg Beta.

Monday, November 14, 2016

Mind Out of Time: Arrival, Ted Chiang, and Sapir-Whorf

Arrival is based on a short story by Ted ChiangStory of Your Life.

Despite what some have said, the main plot idea (as I remember from the story; I have yet to see the film) goes well beyond the Sapir-Whorf hypothesis -- it also requires that human consciousness (potentially) extend beyond the confines of the usual time span we perceive. This is a modification of fundamental physics, not just of cognitive linguistics.

See also A Modern Borges? and Beyond Human Science.

Paul Schrader and Bret Easton Ellis on American Gigolo

Highly recommended to readers with literary or cinematic interests. Paul Schrader and Bret Easton Ellis discuss American Gigolo. (Best brief summary of the movie and its impact is @5-12 min.) Ellis is the author of Less Than Zero and American Psycho. Schrader wrote and directed American Gigolo (1980), which had a huge cultural impact and made Richard Gere a star. (Intro soundtrack is Blondie's Call Me.)

This is an old interview with Ellis (translated from the French):
ALEX ISRAEL - We've spoken about your interest in Paul Schrader's American Gigolo. Tell me about your relationship to the film.
BRET EASTON ELLIS - I Was 16 when it came out and back then it seemed very shocking. It was Paramount's big spring movie of 1980 and it reverberated through our cultivation and started to change things. What Was shocking Was That there HAD never-been movie That Looked at a male beauty in the way American Gigolo DID. We'd seen women bed, Addressed, and undressed fait que fashion, we aim'd never seen a movie about Essentially male beauty. It was the first metrosexual movie. I think it has Anticipated changes in culture, That Would Be seen with more clarity later on in Calvin Klein ads and in the photographs of Herb Ritts.

ALEX ISRAEL - So it offered a new way of thinking about male sexuality's role in mass culture?
BRET EASTON ELLIS - A lot of movies-have Dealt with male sexuality. Purpose Does American Gigolo really deal with male sexuality? Richard Gere plays a prostitute in it. It's a film noir. Regardless of what Paul Schrader Was going for at the time, it: has a heavy homoerotic element. Purpose It Was not a gay film. It was Saying, look, this is Where We're headed as a culture male beauty in straight Culture is going to be Embraced in this way - not as it is in gay culture, in order --other this way. I remember seeing the movie a number of times, Knowing That It Was not a great film, That goal It was very suggestive. Now, 30 years later, it's a key THE movie.

ALEX ISRAEL - An Especially key movie for you, right?
BRET EASTON ELLIS - Completely, right down to the fact That I named Julian in Less Than Zero after Gere's character in American Gigolo. For better or worse, in 1980 I Began working on Less Than Zero. There Was not really a character Julian in the first draft of That book. When That character Began to announce Itself in subsequent drafts He Was named Julian - in homage to American Gigolo.


ALEX ISRAEL - What you Influenced When You Were writing Less Than Zero, other than American Gigolo?
BRET EASTON ELLIS - I Was a Southern California kid Who wanted to write about youth culture and about the people I Knew. The language of movies and it cam from punk rock and from Joan Didion. I do not know if There Was a specific cultural influences That inspired Less Than Zero. I do not know what it Would Have been. I knew that I wanted to write a novel, and I Was That very much Influenced by Joan Didion and Ernest Hemingway, not that much profit by Fitzgerald.

Friday, November 11, 2016

Trump Trauma Talk Therapy

Documentary filmmaker Michael Moore joins Morning Joe for a wide-ranging discussion on the election of Donald Trump and what it means for the country.

Wednesday, November 09, 2016

Trump Triumph: Yes, it can happen here

Trump coverage on this blog. My advice: take Trump seriously, but not literally. The media and the Left took him literally but not seriously.

Trump on Trump: Playboy interview from 1990.
You categorically don't want to be President? I don't want to be President. I’m one hundred percent sure. I'd change my mind only if I saw this country continue to go down the tubes.
Crazy like a Fox: Matt Taibbi in Rolling Stone.
It turns out we let our electoral process devolve into something so fake and dysfunctional that any half-bright con man with the stones to try it could walk right through the front door and tear it to shreds on the first go.

And Trump is no half-bright con man, either. He's way better than average. ...

Trump: "The war in Iraq was a big f ... fat mistake, all right?" he snorted. He nearly said, "A big fucking mistake." He added that the George W. Bush administration lied before the war about Iraq having WMDs and that we spent $2 trillion basically for nothing.
Trump on carried interest and hedge funds: "They didn't build this country."
“The hedge fund guys didn't build this country. These are guys that shift paper around and they get lucky." He went on: “They’re energetic, they’re very smart. But a lot of them, it’s like they’re paper pushers. They make a fortune, they pay no tax... The hedge funds guys are getting away with murder.”
Foo Camp 2016: A Silicon Valley startup engineer from a working class white background told me about his family and the friends he grew up with in Ohio -- "Trump is going to win and it isn't going to be close."
I ran a session TRUMP 2016? CAN IT HAPPEN HERE? (a few people in the session caught the Sinclair Lewis reference) to get a feel for whether the tech community understands what's happening in our country. At another meeting earlier in the year I concluded
Everything at this meeting is off the record, so I can't say much about it. The one comment I'll make is that among this group of elites almost no one I've spoken to groks Trump or his appeal to a large number of Americans.
Michael Moore: Trump Will Win. Michael Moore understands America.
Donald J. Trump is going to win in November. This wretched, ignorant, dangerous part-time clown and full time sociopath is going to be our next president. President Trump. Go ahead and say the words, ‘cause you’ll be saying them for the next four years: “PRESIDENT TRUMP.”

Thursday, November 03, 2016

Decoding Genius podcast

I'm interviewed in episode 2 of this podcast.

What exactly is a Genius? Are they born that way or can you become a genius?

The world is now so interconnected that a single genius, whether a young Aussie creating mind-controlled machines or a ten year old building a high tech microbiology lab in her basement in Canada, can dramatically and instantly affect the way we live. So who are these exceptional people, and how did they become geniuses?

We travelled the world to talk to some of the most interesting young geniuses who are solving puzzles with their exceptional minds and trying to change the world; identifying them with this description, laid out a century ago by Thomas Edison, one of the world’s greatest inventors: “Genius,” he said, “is 1 per cent inspiration and 99 per cent perspiration.”

We also deconstruct the paths that led them to greatness and made them stand out among their peers, whether it's a single 'lightbulb' moment, a complicated mix of natural talent, inspiration, or years of ‘perspiration’ that allowed their genius TO come alive.

We’ll also spend time with world leading experts, trying to unlock the secrets of high intelligence.

Genius: is it inspiration, perspiration, luck, or a complicated mix? That’s the formula we will put to the test as we travel the world… Decoding Genius.

Monday, October 31, 2016

Peter Thiel at the National Press Club

More Thiel.

One hundred years of research on intellectual precocity

David Lubinski sent me this comprehensive review of 100 years of research on intellectual precocity. Someone has already posted an un-gated copy online at the link below. Many of the stunning SMPY graphs summarizing their longitudinal (30+ year) study of a population of gifted individuals (including one group measured at the 1 in 10,000 ability level at age 13) appear in the paper. More SMPY.
From Terman to Today: A Century of Findings on Intellectual Precocity

David Lubinski
Vanderbilt University

One hundred years of research (1916–2016) on intellectually precocious youth is reviewed, painting a portrait of an extraordinary source of human capital and the kinds of learning opportunities needed to facilitate exceptional accomplishments, life satisfaction, and positive growth. The focus is on those studies conducted on individuals within the top 1% in general or specific (mathematical, spatial, or verbal reasoning) abilities. Early insights into the giftedness phenomenon actually foretold what would be scientifically demonstrated 100 years later. Thus, evidence-based conceptualizations quickly moved from viewing intellectually precocious individuals as weak and emotionally liable to highly effective and resilient individuals. Like all groups, intellectually precocious students and adults have strengths and relative weaknesses; they also reveal vast differences in their passion for different pursuits and their drive to achieve. Because they do not possess multipotentiality, we must take a multidimensional view of their individuality. When done, it predicts well long-term educational, occupational, and creative outcomes.

The truth about the Chinese economy, from debt to ghost cities

Highly recommended. See also references linked below.
Andy Rothman has interpreted the Chinese economy for people who have serious and practical decisions to make since his early career heading up macroeconomic research at the U.S. Embassy in Beijing. He is now an investment strategist for Matthews Asia, where he continues to focus on the Chinese economy and writes the Sinology column. His analysis often diverges from what’s in the headlines, and the contrast between Andy’s interpretation and the dominant, deeply gloomy media narrative of the last year or more is especially pronounced. In this podcast, Sinica hosts Jeremy and Kaiser ask Andy to explain why he’s still bullish after all this time. Don't miss our backgrounder for this episode, The truth about the Chinese economy, from debt to ghost cities.
Some interesting claims made in the podcast:

1. 90% of China factory output consumed in China (not for export).

2. Export component of total GDP now relatively minor.

3. Build up in debt mostly in SOE sector, used to fund infrastructure and create jobs in wake of 2008 crisis (Keynesian stimulus).

4. Real estate finance not highly leveraged -- 30 to 70 percent cash in most transactions.

5. Ghost cities usually due to public + private partnerships in which private apartment developers complete buildings before public infrastructure (e.g., train or subway line) is in place. This leads to 1-2 year ghost city lag that is eventually closed. Follow up investigation of ghost cities shows that occupancy is eventually realized. (I've seen one example like this first hand, east of Shenzhen, where occupancy was indeed waiting on the extension of a train line.)

Saturday, October 29, 2016

How Brexit was won, and the unreasonable effectiveness of physicists

The scale of ... triumph cannot be exaggerated. He ... had brought about a complete transformation of the European international order. He had told those who would listen what he intended to do, how he intended to do it, and he did it. He achieved this incredible feat without commanding an army, and without the ability to give an order to the humblest common soldier, without control of a large party, without public support, indeed, in the face of almost universal hostility, without a majority in parliament, without control of his cabinet, and without a loyal following in the bureaucracy. --- Brexit: victory over the Hollow Men
Dominic Cummings finally reveals some of the details behind the Brexit campaign's victory last summer:
On the referendum #20: the campaign, physics and data science
‘If you don’t get this elementary, but mildly unnatural, mathematics of elementary probability into your repertoire, then you go through a long life like a one-legged man in an ass-kicking contest. You’re giving a huge advantage to everybody else. One of the advantages of a fellow like Buffett … is that he automatically thinks in terms of decision trees and the elementary math of permutations and combinations… It’s not that hard to learn. What is hard is to get so you use it routinely almost everyday of your life. The Fermat/Pascal system is dramatically consonant with the way that the world works. And it’s fundamental truth. So you simply have to have the technique…

‘One of the things that influenced me greatly was studying physics… If I were running the world, people who are qualified to do physics would not be allowed to elect out of taking it. I think that even people who aren’t [expecting to] go near physics and engineering learn a thinking system in physics that is not learned so well anywhere else… The tradition of always looking for the answer in the most fundamental way available – that is a great tradition.’ --- Charlie Munger, Warren Buffet’s partner.
During the ten week official campaign the implied probability from Betfair odds of IN winning ranged between 60-83% (rarely below 66%) and the probability of OUT winning ranged between 17-40% (rarely above 33%). One of the reasons why so few in London saw the result coming was that the use by campaigns of data is hard to track even if you know what to look for and few in politics or the media know what to look for yet. Almost all of Vote Leave’s digital communication and data science was invisible even if you read every single news story or column ever produced in the campaign or any of the books so far published (written pre-Shipman’s book).

... We created new software. This was a gamble but the whole campaign was a huge gamble and we had to take many calculated risks. One of our central ideas was that the campaign had to do things in the field of data that have never been done before. This included a) integrating data from social media, online advertising, websites, apps, canvassing, direct mail, polls, online fundraising, activist feedback, and some new things we tried such as a new way to do polling (about which I will write another time) and b) having experts in physics and machine learning do proper data science in the way only they can – i.e. far beyond the normal skills applied in political campaigns. We were the first campaign in the UK to put almost all our money into digital communication then have it partly controlled by people whose normal work was subjects like quantum information (combined with political input from Paul Stephenson and Henry de Zoete, and digital specialists AIQ). We could only do this properly if we had proper canvassing software. We built it partly in-house and partly using an external engineer who we sat in our office for months.

Many bigshot traditional advertising characters told us we were making a huge error. They were wrong. It is one of the reasons we won. We outperformed the IN campaign on data despite them starting with vast mounts of data while we started with almost zero, they had support from political parties while we did not, they had early access to the electoral roll while we did not, and they had the Crosby/Messina data and models from the 2015 election while we had to build everything from scratch without even the money to buy standard commercial databases (we found ways to scrape equivalents off the web saving hundreds of thousands of pounds).

If you want to make big improvements in communication, my advice is – hire physicists, not communications people from normal companies, and never believe what advertising companies tell you about ‘data’ unless you can independently verify it. Physics, mathematics, and computer science are domains in which there are real experts, unlike macro-economic forecasting which satisfies neither of the necessary conditions – 1) enough structure in the information to enable good predictions, 2) conditions for good fast feedback and learning. Physicists and mathematicians regularly invade other fields but other fields do not invade theirs so we can see which fields are hardest for very talented people. It is no surprise that they can successfully invade politics and devise things that rout those who wrongly think they know what they are doing. Vote Leave paid very close attention to real experts. ...

More important than technology is the mindset – the hard discipline of obeying Richard Feynman’s advice: ‘The most important thing is not to fool yourself and you are the easiest person to fool.’ They were a hard floor on ‘fooling yourself’ and I empowered them to challenge everybody including me. They saved me from many bad decisions even though they had zero experience in politics and they forced me to change how I made important decisions like what got what money. We either operated scientifically or knew we were not, which is itself very useful knowledge. (One of the things they did was review the entire literature to see what reliable studies have been done on ‘what works’ in politics and what numbers are reliable.) Charlie Munger is one half of the most successful investment partnership in world history. He advises people – hire physicists. It works and the real prize is not the technology but a culture of making decisions in a rational way and systematically avoiding normal ways of fooling yourself as much as possible. This is very far from normal politics. 

On the eve and day of Brexit I happened to be staying at the estate of a billionaire hedge fund manager, which hosted a meeting of elite capital allocators. At breakfast, more than half of these titans of capital were in shock (others, entirely unperturbed :-) ... Markets were down 8% or more and my host asked for my view. It will play out over years, I said. No one knows where this is going to go. The market is oversold and it's a buying opportunity. So it was.

The Unreasonable Effectiveness of Mathematics in the Natural Sciences
, Eugene Wigner:
... it is useful, in epistemological discussions, to abandon the idealization that the level of human intelligence has a singular position on an absolute scale. In some cases it may even be useful to consider the attainment which is possible at the level of the intelligence of some other species.

Friday, October 28, 2016

Einstein and Oppenheimer on detachment

These are excerpts from Sam Schweber's Einstein and Oppenheimer: The Meaning of Genius.

Perhaps they can provide some solace as we near the end of this ridiculous election season.
Einstein: He never looked “upon ease and happiness as ends in themselves.” The trite objects of human efforts—possessions, outward success, luxury—always seemed to him “contemptible . . . [and] without the kinship of men of like mind, without the occupation with the objective world, the eternally unattainable in the field of art and scientific endeavor, life would have seemed empty” (Einstein 1954, 9). In his tribute to Max Planck on the occasion of Planck’s sixtieth birthday, Einstein stated that, like Arthur Schopenhauer, he believed that “one of the strongest motives that lead men to art and science is escape from everyday life with its painful crudity and hopeless dreariness, from the fetters of one’s own ever shifting desires. A finely tempered nature longs to escape from personal life into the world of objective perception and thought” (Einstein 1954, 225).
Oppenheimer: In a letter to his brother in March 1932 Oppenheimer declared that “through discipline, though not through discipline alone, we can achieve serenity, and a certain small but precious measure of freedom from the accidents of incarnation, and charity, and that detachment which preserves the world that it renounces. I believe that through discipline we learn to preserve what is essential to our happiness in more and more adverse circumstances, and to abandon with simplicity what would else have seemed to us indispensable; that we come a little to see the world without the gross distortion of personal desires, and seeing it so accept more easily our earthly privation and its earthly horror. . . . [I]n its nature discipline involves the subjection of the soul to some perhaps minor end; and that end must be real, if the discipline is not to be factitious. Therefore I think that all things which evoke discipline: study, and our duties to men and to the commonwealth, war, and personal hardship, and even the need for subsistence, ought to be greeted by us with profound gratitude; for only through them can we attain to the least detachment and only so can we know peace. (Smith and Weiner 1980, 155–156)”
My favorite quote from Marcus Aurelius:
Marcus Aurelius

"Or does the bubble reputation distract you? Keep before your eyes the swift onset of oblivion, and the abysses of eternity before us and behind; mark how hollow are the echoes of applause, how fickle and undiscerning the judgments of professed admirers, and how puny the arena of human fame. For the entire earth is but a point, and the place of our own habitation but a minute corner in it; and how many are therein who will praise you, and what sort of men are they?"

Thursday, October 20, 2016

Low Earth Orbit from your backyard? (startup Vector Space Systems)

It's great to see innovation and competition in space launch technology. These small launchers from startup Vector Space Systems can put 50-100kg payloads (e.g., micro satellites) into Low Earth Orbit (LEO) for $2-3 million.

There are obvious military applications for the rapid placement (or replacement) of satellites. For example, see A2AD Fait Accompli? Commercial applications are relatively unexplored but are becoming feasible now.

Tucson Pathfinder from Jim Cantrell on Vimeo.

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