[20:50] ... I'm talking about 65 or 70 percent of kids born to unmarried women. You can't tell me that that doesn't matter. It matters. There could be many explanations for it, but don't try to ignore that fact. Development, the test scores? This whole edifice that we'd built of Diversity and Inclusion, it's founded on a lie, John. Because the issue is performance and the Asians have demonstrated that. The facts are so palpable that it amazes me that people can't look at them. The Asians have demonstrated -- these are people who are second generation descendants; people were born 10,000 miles from here -- it [the USA] is an open society. African-American under-representation is a reflection of African-American under-development. Now, we can go into the historical reasons for that. If the issue is who is to blame ... plenty enough blame to go around. But the fundamental imperative is to enhance the development and that won't happen unless you acknowledge the absence of it. The test scores reflect an inadequate acquisition of functional and cognitive capacities essential to functioning in the modern world and the gaps are enormous etcetera...Now Loury gets really worked up:
[23:50] ... the Afro Studies hustle ... the avoidance of the necessity of failure against standards in order for the standards to be meaningful and for the kind of disciplines and capacities that constitute excellence to be honed and developed. It's a shell game. It's a lie, ok. That's what I'm saying. Just say that the jails are full of black people means that the criminal justice system is racist and to leave it at that when the bodies pile up in Chicago and elsewhere. To talk about Diversity / Inclusion is the way of legitimating and institutionalizing a deferential and racist withholding of judgment from African-American people to perform at the level of excellence at a place like MIT or Caltech or Brown or Columbia or Yale requires. I mean, I'm really really angry about this because people are being dishonest about this in the interest of a Coon Show, John, a Coon Show -- that's what we're talking about ...More at [25:17] The Bonfire of the Black Public Intellectual Vanities. See earlier post Talking Ta-Nehisi Coates, Seriously?
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!
Mary was born in the twenties, when the tests were new and still primitive. Her mother had frozen a dozen eggs, from which came Mary and her sister Elizabeth. Mary had her father's long frame, brown eyes, and friendly demeanor. She was clever, but Elizabeth was the really brainy one. Both were healthy and strong and free from inherited disease. All this her parents knew from the tests -- performed on DNA taken from a few cells of each embryo. The reports came via email, from GP Inc., by way of the fertility doctor. Dad used to joke that Mary and Elizabeth were the pick of the litter, but never mentioned what happened to the other fertilized eggs.See also [1], [2], and [3].
Now Mary and Joe were ready for their first child. The choices were dizzying. Fortunately, Elizabeth had been through the same process just the year before, and referred them to her genetic engineer, a friend from Harvard. Joe was a bit reluctant about bleeding edge edits, but Mary had a feeling the GP engineer was right -- their son had the potential to be truly special, with just the right tweaks ...
Socioeconomic status and genetic influences on cognitive developmentFrom the paper. Note SS/OS = Same/Opposite Sex, SES = Socio-Economic Status.
PNAS doi: 10.1073/pnas.1708491114
Significance
A prominent hypothesis in the study of intelligence is that genetic influences on cognitive abilities are larger for children raised in more advantaged environments. Evidence to date has been mixed, with some indication that the hypothesized pattern may hold in the United States but not elsewhere. We conducted the largest study to date using matched birth and school administrative records from the socioeconomically diverse state of Florida, and we did not find evidence for the hypothesis.
Abstract
Accurate understanding of environmental moderation of genetic influences is vital to advancing the science of cognitive development as well as for designing interventions. One widely reported idea is increasing genetic influence on cognition for children raised in higher socioeconomic status (SES) families, including recent proposals that the pattern is a particularly US phenomenon. We used matched birth and school records from Florida siblings and twins born in 1994–2002 to provide the largest, most population-diverse consideration of this hypothesis to date. We found no evidence of SES moderation of genetic influence on test scores, suggesting that articulating gene-environment interactions for cognition is more complex and elusive than previously supposed.
First, Turkheimer and Horn indicate that “the between-pair variance of MZ pairs decreases in poor environments” (ref. 21, p. 63). Contrary to this relationship, we found that the between-pair variance of SS twins is actually lowest in the highest SES families. Given that SS twins are a relatively equal combination of MZ and DZ twins, one possibility is that a pattern supporting the hypothesis among MZ SS twins is masked by an even stronger pattern in the opposite direction among DZ SS twins. However, Fig. 3 shows that corresponding results for OS twins (all of whom are DZ) give no indication of such a pattern. Between-pair variances in achievement test scores for high-school educated parents of OS twins are higher in all cases than it is for parents without a high school diploma.Via SSC -- thanks, Scott!
Second, Turkheimer and Horn report that “the within-pair variance of MZ twin pairs increases at lower levels of SES: poverty appears to have the effect of making MZ twins more different from each other” (ref. 21, p. 61). We would therefore expect in our data that the within-pair variance for SS twins whose mother did not graduate from high school would be higher than the variance for SS twins whose mother has a high school diploma. However, this is not the case in any of the SS twin comparisons shown in Fig. 3.
Wikipedia: Recent twin and adoption studies suggest that while the effect of the shared family environment is substantial in early childhood, it becomes quite small by late adolescence. These findings suggest that differences in the life styles of families whatever their importance may be for many aspects of children's lives make little long-term difference for the skills measured by intelligence tests.
I'm not sure what is meant by "tipping point" -- I don't think we know yet what qubit technology can be scaled to the point of making Shor's Algorithm feasible. The threat to classical cryptography is still very far off -- you need millions* of qubits and the adversary can always just increase the key length; the tradeoffs are likely to be in favor of the classical method for a long time.These are the Preskill slides I mentioned -- highly recommended. John Preskill is the Feynman Professor of Theoretical Physics at Caltech :-)
Noisy quantum simulators of the type Preskill talks about might be almost possible (first envisioned by Feynman in the Caltech class he gave in the 1980s: Limits to Computation). These are scientifically very interesting but I am not sure that there will be practical applications for some time.
* This is from distant memory so might not be quite right. The number of ideal qubits needed would be a lot less, but with imperfect qubits/gates and quantum error-correction, etc., I seem to remember a result like this. Perhaps millions is the number of gates, not qubits? (See here.)
29:18 [Eventually... Total] Chinese GDP is twice as large as America's so the idea that this great massive economy is going to be a strategic client of the United States that they are kept in line by the US 7th fleet that the US 7th fleet controls its coasts six miles off the ... territorial sea is of course nonsense but this is what the Pivot was all about. This is what Hillary Clinton and Barrack Obama's Pivot was all about was about the reestablishment of US power...
... you know it's simply unreal and if we try and become remain party to that piece of nonsense you know... that's not to say we don't need the US strategically in Asia as a balancing and conciliating power we do, but if we are party to the nonsense that we will line up for the United States to maintain its strategic hegemony in Asia over China we must have troubles...
The Social Origins of InventorsFrom the paper:
Philippe Aghion, Ufuk Akcigit, Ari Hyytinen, Otto Toivanen
NBER Working Paper No. 24110
December 2017
In this paper we merge three datasets - individual income data, patenting data, and IQ data - to analyze the determinants of an individual's probability of inventing. We find that: (i) parental income matters even after controlling for other background variables and for IQ, yet the estimated impact of parental income is greatly diminished once parental education and the individual's IQ are controlled for; (ii) IQ has both a direct effect on the probability of inventing an indirect impact through education. The effect of IQ is larger for inventors than for medical doctors or lawyers. The impact of IQ is robust to controlling for unobserved family characteristics by focusing on potential inventors with brothers close in age. We also provide evidence on the importance of social family interactions, by looking at biological versus non-biological parents. Finally, we find a positive and significant interaction effect between IQ and father income, which suggests a misallocation of talents to innovation.
... IQ has both a direct effect on the probability of inventing which is almost five times as large as that of having a high-income father, and an indirect effect through education ...
... an R-squared decomposition shows that IQ matters more than all family background variables combined; moreover, IQ has both a direct and an indirect impact through education on the probability of inventing, and finally the impact of IQ is larger and more convex for inventors than for medical doctors or lawyers. Third, to address the potential endogeneity of IQ, we focused on potential inventors with brothers close in age. This allowed us to control for family-specific time-invariant unobservables. We showed that the effect of visuospatial IQ on the probability of inventing is maintained when adding these controls.
We look at the effect of an IQ differential between the individual and close brother(s) born at most three years apart.16 This allows us to include family fixed effects and thereby control for family-level time-invariant unobservables, such as genes shared by siblings, parenting style, and fixed family resources. Table 4 shows the results from the regression with family-fixed effects. The first column shows the baseline OLS results using the sample on brothers born at most three years apart. Notice that we include a dummy for the individual being the first born son in the family to account for birth-order effects. The second column shows the results from a regression where we introduce family fixed effects. We lose other parental characteristics than income due to their time-invariant nature.17 The main finding in Table 4 is that the coefficients on "IQ 91-95" and "IQ 96-100" [ these are percentiles, not IQ scores ] in Column 2 (i.e. when we perform the regression with family fixed effects) are the same as in the OLS Column 1. This suggests that these coefficients capture an effect of IQ on the probability of inventing which is largely independent of unobserved family background characteristics, as otherwise the OLS coefficients would be biased and different from the fixed effects estimates.
A generative vision model that trains with high data efficiency and breaks text-based CAPTCHAs
Science 08 Dec 2017: Vol. 358, Issue 6368, eaag2612
DOI: 10.1126/science.aag2612
INTRODUCTION
Compositionality, generalization, and learning from a few examples are among the hallmarks of human intelligence. CAPTCHAs (Completely Automated Public Turing test to tell Computers and Humans Apart), images used by websites to block automated interactions, are examples of problems that are easy for people but difficult for computers. CAPTCHAs add clutter and crowd letters together to create a chicken-and-egg problem for algorithmic classifiers—the classifiers work well for characters that have been segmented out, but segmenting requires an understanding of the characters, which may be rendered in a combinatorial number of ways. CAPTCHAs also demonstrate human data efficiency: A recent deep-learning approach for parsing one specific CAPTCHA style required millions of labeled examples, whereas humans solve new styles without explicit training.
By drawing inspiration from systems neuroscience, we introduce recursive cortical network (RCN), a probabilistic generative model for vision in which message-passing–based inference handles recognition, segmentation, and reasoning in a unified manner. RCN learns with very little training data and fundamentally breaks the defense of modern text-based CAPTCHAs by generatively segmenting characters. In addition, RCN outperforms deep neural networks on a variety of benchmarks while being orders of magnitude more data-efficient.
RATIONALE
Modern deep neural networks resemble the feed-forward hierarchy of simple and complex cells in the neocortex. Neuroscience has postulated computational roles for lateral and feedback connections, segregated contour and surface representations, and border-ownership coding observed in the visual cortex, yet these features are not commonly used by deep neural nets. We hypothesized that systematically incorporating these findings into a new model could lead to higher data efficiency and generalization. Structured probabilistic models provide a natural framework for incorporating prior knowledge, and belief propagation (BP) is an inference algorithm that can match the cortical computational speed. The representational choices in RCN were determined by investigating the computational underpinnings of neuroscience data under the constraint that accurate inference should be possible using BP.
RESULTS
RCN was effective in breaking a wide variety of CAPTCHAs with very little training data and without using CAPTCHA-specific heuristics. By comparison, a convolutional neural network required a 50,000-fold larger training set and was less robust to perturbations to the input. Similar results are shown on one- and few-shot MNIST (modified National Institute of Standards and Technology handwritten digit data set) classification, where RCN was significantly more robust to clutter introduced during testing. As a generative model, RCN outperformed neural network models when tested on noisy and cluttered examples and generated realistic samples from one-shot training of handwritten characters. RCN also proved to be effective at an occlusion reasoning task that required identifying the precise relationships between characters at multiple points of overlap. On a standard benchmark for parsing text in natural scenes, RCN outperformed state-of-the-art deep-learning methods while requiring 300-fold less training data.
CONCLUSION
Our work demonstrates that structured probabilistic models that incorporate inductive biases from neuroscience can lead to robust, generalizable machine learning models that learn with high data efficiency. In addition, our model’s effectiveness in breaking text-based CAPTCHAs with very little training data suggests that websites should seek more robust mechanisms for detecting automated interactions.
Chess24: 20 years after DeepBlue defeated Garry Kasparov in a match, chess players have awoken to a new revolution. The AlphaZero algorithm developed by Google and DeepMind took just four hours of playing against itself to synthesise the chess knowledge of one and a half millennium and reach a level where it not only surpassed humans but crushed the reigning World Computer Champion Stockfish 28 wins to 0 in a 100-game match. All the brilliant stratagems and refinements that human programmers used to build chess engines have been outdone, and like Go players we can only marvel at a wholly new approach to the game. ...ArXiv preprint:
Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning AlgorithmExcerpt:
The game of chess is the most widely-studied domain in the history of artificial intelligence. The strongest programs are based on a combination of sophisticated search techniques, domain-specific adaptations, and handcrafted evaluation functions that have been refined by human experts over several decades. In contrast, the AlphaGo Zero program recently achieved superhuman performance in the game of Go, by tabula rasa reinforcement learning from games of self-play. In this paper, we generalise this approach into a single AlphaZero algorithm that can achieve, tabula rasa, superhuman performance in many challenging domains. Starting from random play, and given no domain knowledge except the game rules, AlphaZero achieved within 24 hours a superhuman level of play in the games of chess and shogi (Japanese chess) as well as Go, and convincingly defeated a world-champion program in each case.
Finally, we analysed the chess knowledge discovered by AlphaZero. Table 2 analyses the most common human openings (those played more than 100,000 times in an online database of human chess games (1)). Each of these openings is independently discovered and played frequently by AlphaZero during self-play training. When starting from each human opening, AlphaZero convincingly defeated Stockfish, suggesting that it has indeed mastered a wide spectrum of chess play.
My meeting in Beijing with Hugo Barra, who runs all international expansion for Xiaomi — the cool smartphone maker and highest-valued startup in China, at around $45 billion or so — was scheduled for 11 pm, but got delayed because of other meetings, so it started at midnight. (Hugo had a flight to catch at 6:30 am after that.)
In China, there is a company work culture at startups that's called 9/9/6. It means that regular work hours for most employees are from 9 am to 9 pm, six days a week. If you thought Silicon Valley has intense work hours, think again.
For founders and top executives, it's often 9/11/6.5. That's probably not very efficient and useful (who's good as a leader when they're always tired and don't know their kids?) but totally common.
Teams get locked up in hotels for weeks before a product launch, where they only work, sleep and work out, to drive 100 percent focus without distractions and make the launch date. And while I don't think long hours are any measure of productivity, I was amazed by the enormous hunger and drive. ...
When I was a beginning grad student, they had a series of lectures by faculty members to the new students about theoretical research, and one of the people who gave such a lecture was Wheeler. He drew a picture on the blackboard of the universe visualized as an eye looking at itself. I had no idea what he was talking about. It’s obvious to me in hindsight that he was explaining what it meant to talk about quantum mechanics when the observer is part of the quantum system. I imagine there is something we don’t understand about that. [ Italics mine ]The picture he refers to is reproduced below.
I met him in Boston in 1977, when I was getting interested in the connection between physics and mathematics. I attended a meeting, and there was this young chap with the older guys. We started talking, and after a few minutes I realized that the younger guy was much smarter than the old guys. He understood all the mathematics I was talking about, so I started paying attention to him. That was Witten. And I’ve kept in touch with him ever since.The closest thing I have read to a personal intellectual history of Witten is his essay Adventures in Physics and Math, which I highly recommend. The essay addresses some common questions, such as What was Ed like as a kid? How did he choose a career in Physics? How does he know so much Mathematics? For example,
In 2001, he invited me to Caltech, where he was a visiting professor. I felt like a graduate student again. Every morning I would walk into the department, I’d go to see Witten, and we’d talk for an hour or so. He’d give me my homework. I’d go away and spend the next 23 hours trying to catch up. Meanwhile, he’d go off and do half a dozen other things. We had a very intense collaboration. It was an incredible experience because it was like working with a brilliant supervisor. I mean, he knew all the answers before I got them. If we ever argued, he was right and I was wrong. It was embarrassing!
(Fields Medalist Michael Atiyah, on what it was like to collaborate with Witten)
At about age 11, I was presented with some relatively advanced math books. My father is a theoretical physicist and he introduced me to calculus. For a while, math was my passion. My parents, however, were reluctant to push me too far, too fast with math (as they saw it) and so it was a long time after that before I was exposed to any math that was really more advanced than basic calculus. I am not sure in hindsight whether their attitude was best or not.A great video, suggested by a commenter:
Science: Last month, astronomers wowed the world when they announced that they had seen two neutron stars merge, apparently creating heavy elements such as gold and platinum and spewing them into space. Nuclear physicists here at Michigan State University (MSU) also cheered the find. They are building an atom smasher, the $730 million Facility for Rare Isotope Beams (FRIB), that could decipher exactly how those elements were forged in the inferno. “We were hoping to see an event like this someday,” says Witold Nazarewicz, an MSU theorist and FRIB's chief scientist.Note this is an old schematic, from 2008 or so.
First proposed in 1999, the project didn't get the greenlight for construction from the Department of Energy (DOE) until 2014. But since then, progress has been rapid. In what was a grassy patch behind MSU's existing nuclear physics laboratory now stands an imposing 200-meter-long building. In its basement, technicians are installing the first section of FRIB's 500-meter-long linear accelerator, which will shoot beams of nuclei ranging from hydrogen to uranium into a graphite target to blast out short-lived new isotopes. In this context, isotope is just another word for nucleus—one that makes for a better acronym.
The accelerator at the Facility for Rare Isotope Beams will create short-lived nuclei thought to be forged in neutron star mergers.
The project is on budget and ahead of schedule, and most of the major technological puzzles have been solved, says Thomas Glasmacher, FRIB's project director. “We don't have anything that we don't know how to do,” he says. Other physicists are impressed with the progress. “The moment they could, they ran with this project,” says Kate Jones, an experimental nuclear physicist at the University of Tennessee in Knoxville. “It's very impressive when you look down in the basement and see all the kit they've got.”
FRIB's nuclei will be key to understanding how neutron-star mergers make heavy elements. Spotted by gravitational-wave detectors in the United States and Italy and telescopes around the world, the violent collision produced an afterglow that over days faded from bright blue to dimmer red (Science, 20 October, p. 282). The light show jibed with astrophysicists' model of a so-called kilonova, in which the disintegrating neutron stars fling neutron-rich matter into space. The model predicts that in the debris, a chain of nuclear interactions known as the rapid neutron process, or r-process, quickly generates most of the elements heavier than iron. (Other elements emerge from supernova explosions and the deaths of smaller stars, from cosmic ray interactions, and also as leftovers lingering from the big bang.)
For astrophysicists, the observation marked a triumph for the kilonova model. For nuclear physicists, it's just the beginning. In the r-process, a nucleus gains weight by gobbling up one neutron after another. At the same time, the nucleus can change its chemical identity through radioactive beta decay, which turns a neutron into a proton and bumps the nucleus up the periodic table of elements. Exactly how the nucleus evolves depends on the speed of the decay and the probability that it will soak up another neutron.
Those parameters are poorly known. “Honestly, the nuclear physics is not in good shape,” says MSU nuclear astrophysicist Hendrik Schatz. “Most of the nuclei involved have not been identified and the theory has not been developed.” FRIB aims to change that by making as many of the neutron-laden nuclei as possible and measuring their masses and lifetimes. That might seem like a hopeless task, as the r-process involves dozens of intermediate nuclei. However, only a few key nuclei—the slowest decayers and absorbers—should act as bottlenecks to control the process and determine which elements are made in greatest abundance, Schatz explains.
Such data would better constrain models of heavy element production in neutron star mergers. The abundances could then be compared with those observed in the universe to determine whether merging neutron stars are the only astrophysical sites of the r-process, Jones says. Many astrophysicists have suggested as much, but that's a leap, she says. “It's very easy to say, ‘Oh, we've found the site for the r-process—Well done!’ In reality this is just opening a door.”
The 1400 physicists who have signed up to use FRIB will perform many other experiments, ranging from trapping and measuring the properties of a single exotic nucleus, to measuring a hail of novel nuclei scattering off a particular target nucleus. Data from the experiments will feed into a more comprehensive theory of the structure of the nucleus, Nazarewicz says. Physicists already have a fundamental theory of the innards of protons and neutrons, particles called quarks and gluons, and how they interact. But using that theory, known as quantum chromodynamics, to predict nuclear structure is effectively impossible: It is so computationally complex that supercomputers are needed just to simulate the proton and neutron.
To model the behavior of nuclei, theorists now rely on various approximate “effective theories” that work for some nuclei but not others. FRIB's grandest goal, Nazarewicz says, is to develop a deeper understanding that will enable theorists to weave these disparate and sometimes discordant theories together into a coherent whole.
First, researchers have to finish the accelerator. In September, they fired a test beam through its first section, made of copper cavities that work at room temperature. They are now installing the main accelerating modules, which are made of superconducting niobium and must be chilled with liquid helium to 2 K. Researchers hope to send beams through the cold accelerator next year. In 2021, they plan to tear down a wall and connect the finished accelerator to the existing lab so that new experiments can begin. ...
The empires Glubb studied had a lifespan of about ten human generations, or two hundred and fifty years, despite changing factors such as technology. Glubb describes a pattern of growth and decline, with six stages: the Ages of Pioneers, Conquest, Commerce, Affluence, Intellect and Decadence. He pointedly avoided writing about India or China, focusing rather on middle and western Eurasia, stating that his knowledge was inadequate to the task.
Note that six stages in 10 generations means that significant change can occur over one or two generations -- a nation can pass from one age to the next, as I believe we have in America during my lifetime.
... There does not appear to be any doubt that money is the agent which causes the decline of this strong, brave and self-confident people. The decline in courage, enterprise and a sense of duty is, however, gradual. The first direction in which wealth injures the nation is a moral one. Money replaces honour and adventure as the objective of the best young men. Moreover, men do not normally seek to make money for their country or their community, but for themselves. Gradually, and almost imperceptibly, the Age of Affluence silences the voice of duty. The object of the young and the ambitious is no longer fame, honour or service, but cash. Education undergoes the same gradual transformation. No longer do schools aim at producing brave patriots ready to serve their country. [ Or to discover great things for all mankind! ] Parents and students alike seek the educational qualifications which will command the highest salaries. ...
Duty, Honor, Country:
The unbelievers will say they are but words, but a slogan, but a flamboyant phrase. Every pedant, every demagogue, every cynic, every hypocrite, every troublemaker, and I am sorry to say, some others of an entirely different character, will try to downgrade them even to the extent of mockery and ridicule.
The 21st century American reality (the Age of Decadence):
"Yeah, I calculated the NPV, and, you know, it's just not worth it for me. I really believe in your project, though. And, I share your passion. Good luck."
CNN: The Justice Department is actively investigating Harvard University's use of race in its admissions policies and has concluded the school is "out of compliance" with federal law, according to documents obtained by CNN. ...Wall Street Journal
[Click through for DOJ letter to Harvard. Harvard refused to supply admissions data to DOJ as requested for Title VI investigation of bias against Asian-Americans.]
WSJ: ... The Justice Department, whose Civil Rights Division is conducting the investigation into similar allegations, said in a letter to Harvard’s lawyers, dated Nov. 17 and reviewed by the Journal, that the school was being investigated under Title VI of the Civil Rights Act of 1964, which bars discrimination on the basis of race, color and national origin for organizations that receive federal funding. The letter also said the school had failed to comply with a Nov. 2 deadline to provide documents related to the university’s admissions policies and practices.From DOJ web site:
The department told Harvard it “may file a lawsuit” to enforce compliance if Harvard doesn’t hand over the documents by Dec. 1, according to a separate letter dated Nov. 17 from John M. Gore, the acting assistant attorney general for the Civil Rights Division.
... if a federal judge finds Harvard has violated Title VI, the court has broad authority to issue a remedy, such as ordering the university to change its admissions policies, the experts say.
Schools in violation of Title VI can also lose access to federal funds.
TITLE VI OF THE CIVIL RIGHTS ACT OF 1964
42 U.S.C. § 2000D ET SEQ.
OVERVIEW OF TITLE VI OF THE CIVIL RIGHTS ACT OF 1964
Title VI, 42 U.S.C. § 2000d et seq., was enacted as part of the landmark Civil Rights Act of 1964. It prohibits discrimination on the basis of race, color, and national origin in programs and activities receiving federal financial assistance. As President John F. Kennedy said in 1963:
Simple justice requires that public funds, to which all taxpayers of all races [colors, and national origins] contribute, not be spent in any fashion which encourages, entrenches, subsidizes or results in racial [color or national origin] discrimination.
In the future there will be two kinds of jobs. Workers will eitherI've been pushing Michigan State University to offer a coding bootcamp experience to all undergraduates who want it: e.g., Codecademy.com. The goal isn't to turn non-STEM majors into software developers, but to give all interested students exposure to an increasingly important and central aspect of the modern world.
Tell computers what to do
or
Be told by computers what to do
Abstract: We apply methods from Compressed Sensing (L1-penalized regression; Donoho-Tanner phase transition with noise) to the UKBB dataset of 500k SNP genotypes. We construct genomic predictors for several complex traits. Our height predictor captures nearly all of the predicted SNP heritability for this trait -- thereby resolving the missing heritability problem. Actual heights of most individuals in validation tests are within a few cm of predicted heights. I also discuss application of these methods to polygenic disease risk: sparsity estimates (of the number of causal loci), combined with phase transition scaling analysis, allow estimates of the amount of case | control data required to construct good predictors.Here's how people + robots handle your spit sample to produce a SNP genotype:
MIT Technology Review
Eugenics 2.0: We’re at the Dawn of Choosing Embryos by Health, Height, and More
Will you be among the first to pick your kids’ IQ? As machine learning unlocks predictions from DNA databases, scientists say parents could have choices never before possible.
Nathan Treff was diagnosed with type 1 diabetes at 24. It’s a disease that runs in families, but it has complex causes. More than one gene is involved. And the environment plays a role too.
So you don’t know who will get it. Treff’s grandfather had it, and lost a leg. But Treff’s three young kids are fine, so far. He’s crossing his fingers they won’t develop it later.
Now Treff, an in vitro fertilization specialist, is working on a radical way to change the odds. Using a combination of computer models and DNA tests, the startup company he’s working with, Genomic Prediction, thinks it has a way of predicting which IVF embryos in a laboratory dish would be most likely to develop type 1 diabetes or other complex diseases. Armed with such statistical scorecards, doctors and parents could huddle and choose to avoid embryos with failing grades.
IVF clinics already test the DNA of embryos to spot rare diseases, like cystic fibrosis, caused by defects in a single gene. But these “preimplantation” tests are poised for a dramatic leap forward as it becomes possible to peer more deeply at an embryo’s genome and create broad statistical forecasts about the person it would become.
The advance is occurring, say scientists, thanks to a growing flood of genetic data collected from large population studies. ...
Spotting outliers
The company’s plans rely on a tidal wave of new knowledge showing how small genetic differences can add up to put one person, but not another, at high odds for diabetes, a neurotic personality, or a taller or shorter height. Already, such “polygenic risk scores” are used in direct-to-consumer gene tests, such as reports from 23andMe that tell customers their genetic chance of being overweight.
For adults, risk scores are little more than a novelty or a source of health advice they can ignore. But if the same information is generated about an embryo, it could lead to existential consequences: who will be born, and who stays in a laboratory freezer.
“I remind my partners, ‘You know, if my parents had this test, I wouldn’t be here,’” says Treff, a prize-winning expert on diagnostic technology who is the author of more than 90 scientific papers.
Genomic Prediction was founded this year and has raised funds from venture capitalists in Silicon Valley, though it declines to say who they are. Tellier, whose inspiration is the science fiction film Gattaca, says the company plans to offer reports to IVF doctors and parents identifying “outliers”—those embryos whose genetic scores put them at the wrong end of a statistical curve for disorders such as diabetes, late-life osteoporosis, schizophrenia, and dwarfism, depending on whether models for those problems prove accurate. ...
This week, Genomic Prediction manned a booth at the annual meeting of the American Society for Reproductive Medicine. That organization, which represents fertility doctors and scientists, has previously said it thinks testing embryos for late-life conditions, like Alzheimer’s, would be “ethically justified.” It cited, among other reasons, the “reproductive liberty” of parents.
... Hsu’s prediction is that “billionaires and Silicon Valley types” will be the early adopters of embryo selection technology, becoming among the first “to do IVF even though they don’t need IVF.” As they start producing fewer unhealthy children, and more exceptional ones, the rest of society could follow suit.
“I fully predict it will be possible,” says Hsu of selecting embryos with higher IQ scores. “But we’ve said that we as a company are not going to do it. It’s a difficult issue, like nuclear weapons or gene editing. There will be some future debate over whether this should be legal, or made illegal. Countries will have referendums on it.”
The Physicist and the Neuroscientist: A Tale of Two ConnectomesMore Bobby, with more hair.
Steve burst into Bobby's lab, a small metal box under one arm. Startled, Bobby nearly knocked over his Zeiss electron microscope.
I've got it! shouted Steve. My former student at DeepBrain sent me one of their first AGI's. It's hot out of their 3D neuromorphic chip printer.
This is the thing that talks and understands quantum mechanics? asked Bobby.
Yes, if I just plug it in. He tapped the box -- This deep net has 10^10 connections! Within spitting distance of our brains, but much more efficient. They trained it in their virtual simulator world. Some of the algos are based on my polytope paper from last year. It not only knows QM, it understands what you mean by "How much is that doggie in the window?" :-)
Has anyone mapped the connections?
Sort of, I mean the strengths and topology are determined by the training and algos... It was all done virtually. Printed into spaghetti in this box.
We've got to scan it right away! My new rig can measure 10^5 connections per second!
What for? It's silicon spaghetti. It works how it works, but we created it! Specific connections... that's like collecting postage stamps.
No, but we need to UNDERSTAND HOW IT WORKS!
...
Why don't you just ask IT? thought Steve, as he left Bobby's lab.
Previous versions of AlphaGo initially trained on thousands of human amateur and professional games to learn how to play Go. AlphaGo Zero skips this step and learns to play simply by playing games against itself, starting from completely random play. In doing so, it quickly surpassed human level of play and defeated the previously published champion-defeating version of AlphaGo by 100 games to 0.Rapid progress from a random initial state is rather amazing, but perhaps something we should get used to given that:
It is a shame that very few working physicists, even theoreticians, have thought carefully and deeply about quantum foundations. Perhaps Weinberg's fine summary will stimulate greater awareness of this greatest of all unresolved problems in science.and quoted Weinberg:
... today there is no interpretation of quantum mechanics that does not have serious flaws.Posts on this blog related to the Born Rule, etc., and two of my papers:
The measure problem in many worlds quantum mechanics
On the origin of probability in quantum mechanics
Loury (@19min): "He's a good writer but not a deep thinker, and he's being taken seriously as if he was a deep thinker... he's talented I mean there's not any doubt about that but the actual analytical content of the argument, there are gaping holes in it..."On the dangers of Identity Politics:
Loury (@21min): Coates' immersion in a racialist conception of American Society ... everything through the lens of race ... is the mirror image or the flip side of a white nationalist conception about American society in which everything is viewed in terms of race and Williams in the review includes extensive reportage from his interview of Richard Spencer the white nationalist leader ... and has Spencer saying back to him in effect I'm glad that people eatin' up Tallahassee cause I'm glad that they're taking it in because it's a thoroughly racialized conception. It's racial essentialism at its utmost and that primes them: they really believe in race, these liberals who are reading Coates, and that means I can flip them says Richard Spencer. The day will come given their belief in race -- I can persuade them that they're white. Coates wants that they regret and lament and eschew the fact that they're white. Richard Spencer dreams of a day in which, them seeing themselves as white, they'll get tired of hating themselves and flip over to the side of being proud ...I've been reading Coates for years, since he was a relatively unknown writer at The Atlantic. Here are very good Longform Podcast interviews which explore his early development: 2015, 2014, 2012.
