Richard Lowery is a professor of finance at the McCombs School of Business at the University of Texas, Austin. In this conversation, he describes the ideological climate of his university and the consequent negative effects on undergraduate education and freedom of expression on campus.
Steve and Richard discuss:
0:00 Richard Lowery's academic and political background
9:01 Campus environment for academics and faculty members
12:19 Cultural and political dynamics at academic institutions
23:04 How students experience campus culture and political influences
32:13 Public awareness and interest in campus culture
35:50 What happened to the Liberty Institute at UT Austin
Seminar at the Institute of Physics, University of Amsterdam, 17 Jun 2022.
Title: Quantum Hair and Black Hole Information
Abstract: I discuss recent results concerning the quantum state of the gravitational field of a compact matter source such as a black hole. These results demonstrate the existence of quantum hair, violating the classical No Hair Theorems. I then discuss how this quantum hair affects Hawking radiation, allowing unitary evaporation of black holes. Small corrections to leading order Hawking radiation amplitudes, with weak dependence on the external graviton state, are sufficient to produce a pure final radiation state. The radiation state violates the factorization assumption made in standard formulations of the information paradox. These conclusions are consequences of long wavelength properties of quantum gravity: no special assumptions are made concerning short distance (Planckian) physics.
Putting this tweet thread here for future reference. If you read this blog you may want to follow me on Twitter as I sometimes say things there that might be of interest.
In my conversation with @RichardHanania on his podcast we discussed meritocracy and political leadership in PRC. This short video gives a good overview of how it works. Keep in mind CCP ~ 100M people or ~10% of adult population! 1/4https://t.co/dgLrW25fM8
PRC civil service exam appears highly g-loaded and is taken by 1-2M people each year. Further promotion depends on performance over ~20y timescale, purportedly monitored by a dedicated and independent I/O sub-org. 2/4https://t.co/W5YC2juWRI
For example, Yuan Jiajun, frmr gov. of Zhejiang province and Central Committee member, is a PhD in Aero Eng and ran the manned spaceflight program. Resumes of top PRC leaders are qualitatively different from those of western politicians... 3/4https://t.co/CWqjnLdfyT
Tim Palmer is Royal Society Research Professor in Climate Physics, and a Senior Fellow at the Oxford Martin Institute.
He is interested in the predictability and dynamics of weather and climate, including extreme events.
He was involved in the first five IPCC assessment reports and was co-chair of the international scientific steering group of the World Climate Research Programme project (CLIVAR) on climate variability and predictability.
After completing his DPhil at Oxford in theoretical physics, Tim worked at the UK Meteorological Office and later the European Centre for Medium-Range Weather Forecasts. For a large part of his career, Tim has developed ensemble methods for predicting uncertainty in weather and climate forecasts.
In 2020 Tim was elected to the US National Academy of Sciences.
Steve, Corey Washington, and Tim first discuss his career path from physics to climate research and then explore the science of climate modeling and the main uncertainties in state-of-the-art models.
In this episode, we discuss:
00:00 Introduction
1:48 Tim Palmer's background and transition from general relativity to climate modeling
Note added: For some background on the importance of water vapor (cloud) distribution within the primitive cells used in these climate simulations, see:
Low clouds trap IR radiation near the Earth, while high clouds reflect solar energy back into space. The net effect on heating from the distribution of water vapor is crucial in these models. However, due to the complexity of the Navier-Stokes equations, current simulations cannot actually solve for this distribution from first principles. Rather, the modelers hand code assumptions about fine grained behavior within each cell. The resulting uncertainty in (e.g., long term) climate prediction from these approximations is unknown.
This is a balanced and informative article in WIRED, excerpted from author Rachael Pells' forthcoming book, Genomics: How Genome Sequencing Will Change Our Lives.
WIRED: ... Companies such as Genomic Prediction are taking this process much further, giving parents the power to select the embryo they believe to have the best fighting chance of survival both in the womb and out in the world. At the time of writing, Genomic Prediction works with around 200 IVF clinics across six continents. For company cofounder Stephen Hsu, the idea behind preconception screening was no eureka moment, but something he and his peers developed gradually. “We kept pursuing the possibilities from a purely scientific interest,” he says. Over time sequencing has become cheaper and more accessible, and the bank of genetic data has become ever greater, which has provided the opportunity to easily apply machine learning programs to seek out patterns, Hsu explains. “You can have typically millions of people in one data set, with exact measurements of certain things about them—for instance how tall they are or whether they have diabetes—what we call phenotypes. And so it’s relatively straightforward to use AI to build genetic predictors of traits ranging from very simple ones which are only determined by a few genes, or a few different locations in the genome, to the really complicated ones.” As Hsu indicates, the crucial difference with this technology is that it’s not just single mutations like cystic fibrosis or sickle cell anemia that the service makes its calculations on. The conditions embryos are screened for can be extremely complicated, involving thousands of genetic variants across different parts of the genome.
In late 2017, Hsu and his colleagues published a paper demonstrating how, using genomic data at scale, scientists could predict someone’s height to within an inch of accuracy using just their DNA. The research group later used the same method to build genomic predictors for complex diseases such as hypothyroidism, types 1 and 2 diabetes, breast cancer, prostate cancer, testicular cancer, gallstones, glaucoma, gout, atrial fibrillation, high cholesterol, asthma, basal cell carcinoma, malignant melanoma, and heart attacks. ...
Fascinating director's commentary by Ridley Scott. Video cued to start at a point where Scott talks about the conceptual background for the film. The subsequent ~15m are really great, including dreams of unicorns, memories of green, origami, Deckard as replicant.
... a special feature on the Prometheus Blu-ray release makes the film even more interesting by tying it into the Blade Runner universe. Included as an entry in the journal of Peter Weyland (Guy Pearce), who in the film was obsessed with creating artificial life, is the following gem:
A mentor and long-departed competitor once told me that it was time to put away childish things and abandon my “toys.” He encouraged me to come work for him and together we would take over the world and become the new Gods. That’s how he ran his corporation, like a God on top of a pyramid overlooking a city of angels. Of course, he chose to replicate the power of creation in an unoriginal way, by simply copying God. And look how that turned out for the poor bastard. Literally blew up in the old man’s face. I always suggested he stick with simple robotics instead of those genetic abominations he enslaved and sold off-world, although his idea to implant them with false memories was, well… “amusing,” is how I would put it politely.
Bonus: at 1h18m in the video, Tyrell cryogenically preserved at the heart of his great pyramid!
Kishore Mahbubani is Distinguished Fellow at the Asia Research Institute, National University of Singapore.
Kishore enjoyed two distinct careers: in diplomacy (1971 to 2004) and in academia (2004 to 2019). He is a prolific writer and speaker on geopolitics and East-West relations.
He was twice Singapore’s Ambassador to the UN and served as President of the UN Security Council in January 2001 and May 2002.
Mr. Mahbubani joined academia in 2004, when he was appointed the Founding Dean of the Lee Kuan Yew School of Public Policy (LKY School), NUS. He was Dean from 2004 to 2017.
In this episode Steve and Kishore discuss:
0:00 Introduction
2:52 Upbringing in Singapore and Asia's rise
11:35 How western thinking influences China-U.S. relations
23:05 Is China a threat to U.S. hegemony in Asia?
25:52 The United States' long-term strategy for China
32:13 How trade with ASEAN influences U.S.-China relations
40:58 Can ASEAN countries play a diplomatic role between U.S. and China
43:05 Xi Jinping's leadership and the zero-sum view of China
Informal summary: We built a polygenic health index using risk predictors weighted by lifespan impact of the specific disease condition. This index seems to characterize general health. Individuals with higher index scores have decreased disease risk across almost all 20 diseases (no significant risk increases), and longer calculated life expectancy. When estimated Disability Adjusted Life Years (DALYs) are used as the performance metric, the gain from selection among 10 individuals (highest index score vs average) is found to be roughly 4 DALYs. We find no statistical evidence for antagonistic trade-offs in risk reduction across these diseases. Correlations between genetic disease risks are found to be mostly positive and generally mild.
We construct a polygenic health index as a weighted sum of polygenic risk scores for 20 major disease conditions, including, e.g., coronary artery disease, type 1 and 2 diabetes, schizophrenia, etc. Individual weights are determined by population-level estimates of impact on life expectancy. We validate this index in odds ratios and selection experiments using unrelated individuals and siblings (pairs and trios) from the UK Biobank. Individuals with higher index scores have decreased disease risk across almost all 20 diseases (no significant risk increases), and longer calculated life expectancy. When estimated Disability Adjusted Life Years (DALYs) are used as the performance metric, the gain from selection among 10 individuals (highest index score vs average) is found to be roughly 4 DALYs. We find no statistical evidence for antagonistic trade-offs in risk reduction across these diseases. Correlations between genetic disease risks are found to be mostly positive and generally mild. These results have important implications for public health and also for fundamental issues such as pleiotropy and genetic architecture of human disease conditions.
Extrapolating the DALY gain vs Health Index score curve (top figure) to the entire human population (e.g., 10 billion people) results in +30 or +40 DALYs more than average, or something like 120 total years of life. The individual with the highest Health Index score in the world is predicted to live about 120 years.
I wanted to use this in the paper but my collaborators vetoed me 8-)
The days of our years are threescore years and ten; and if by reason of strength they be fourscore years, yet is their strength labour and sorrow; for it is soon cut off, and we fly away
Last week I was in Amsterdam and Utrecht to give seminars on quantum hair and black hole information at the Universities of Utrecht and Amsterdam. The organizers told me I was the first external visitor to give an in-person talk since the COVID lockdowns.
The Utrecht seminar went over 2 hours (unfortunately, 't Hooft was away) and the other over 90 minutes.
Gregory Clark is Distinguished Professor of Economics at UC-Davis. He is an editor of the European Review of Economic History, chair of the steering committee of the All-UC Group in Economic History, and a Research Associate of the Center for Poverty Research at Davis. He was educated at Cambridge University and received a PhD from Harvard University.
His areas of research are long-term economic growth, the wealth of nations, economic history, and social mobility.
Steve and Greg discuss:
0:00 Introduction
2:31 Background in economics and genetics
10:25 The role of genetics in determining social outcomes
16:27 Measuring social status through marriage and occupation
36:15 Assortative mating and the industrial revolution
49:38 Criticisms of empirical data, engagement on genetics and economic history
1:12:12 Heckman and Landerso study of social mobility in US vs Denmark
1:24:32 Predicting cognitive traits
1:33:26 Assortative mating and increase in population variance
More videos from the conference here. (Konrad Zuse!)
See at 50 minutes for an interesting story about von Neumann's role in the implosion mechanism for atomic bombs. vN apparently solved the geometrical problem for the shape of the explosive lens overnight after hearing a seminar on the topic. Still classified?
To solve this problem, the Los Alamos team planned to produce an “explosive lens”, a combination of different explosives with different shock wave speeds. When molded into the proper shape and dimensions, the high-speed and low-speed shock waves would combine with each other to produce a uniform concave pressure wave with no gaps. This inwardly-moving concave wave, when it reached the plutonium sphere at the center of the design, would instantly squeeze the metal to at least twice the density, producing a compressed ball of plutonium that contained about 5 times the necessary critical mass. A nuclear explosion would then result.
Aurea toddles around in her pink sparkly sneakers, climbing up the steps that, to her, are nearly waist high. Her tiny t-shirt is the epitome of how adorable she is. It says “you + me + snuggles.” Aurea’s father, Rafal Smigrodzki, watches over his little girl. He is clearly proud of her.
“She’s very lively. I think she’s a pretty, pretty happy baby,” Smigrodzki said, “a very often smiley baby.”
Of course, Smigrodzki thinks his baby is special — most parents do. But Aurea is indeed unique. She was born almost two years ago and happens to be the first child born as the result of a new type of genetic screening, which carefully selected her embryo.
Smigrodzki and his girlfriend used in vitro fertilization and an advanced selection process from a startup called Genomic Prediction.
The New Jersey startup offers genetic tests and promises to help prospective parents select embryos with the best possible genes. The company says its test can screen embryos for a variety of diseases and health conditions, like heart disease, diabetes, or breast cancer.
Smigrodzki, a neurologist with a PhD in genetics, stumbled across the company in 2017.
“I was always interested and reading about all kinds of new developments,” he said. “And just happened to read an article in the MIT Technology Review about Genomic Prediction.”
This interview with John Mearsheimer was conducted in 2020 on the original Manifold podcast with Corey Washington and Steve Hsu. Parts of the conversation are prescient with respect to US-China relations and the situation in Ukraine.
John Joseph Mearsheimer is an American political scientist and international relations scholar, who belongs to the realist school of thought. He is the R. Wendell Harrison Distinguished Service Professor at the University of Chicago. He has been described as the most influential realist of his generation.
Mearsheimer is best known for developing the theory of offensive realism, which describes the interaction between great powers as being primarily driven by the rational desire to achieve regional hegemony in an anarchic international system. In accordance with his theory, Mearsheimer believes that China's growing power will likely bring it into conflict with the United States.
Steve, Corey, and John discuss:
0:00 A quick message for listeners
1:21 Introduction
2:39 Realist foreign policy worldview
15:46 Proxy conflicts and the U.S.
21:31 U.S. history: a moral hegemon, or just a hegemon? Zinn and Chomsky
Bloomberg: Simone Collins knew she was pregnant the moment she answered the phone. ... Embryo 3, the fertilized egg that Collins and her husband, Malcolm, had picked, could soon be their daughter—a little girl with, according to their tests, an unusually good chance of avoiding heart disease, cancer, diabetes, and schizophrenia.
This isn’t a story about Gattaca-style designer babies. No genes were edited in the creation of Collins’s embryo. The promise, from dozens of fertility clinics around the world, is just that the new DNA tests they’re using can assess, in unprecedented detail, whether one embryo is more likely than the next to develop a range of illnesses long thought to be beyond DNA-based predictions. It’s a new twist on the industry-standard testing known as preimplantation genetic testing, which for decades has checked embryos for rare diseases, such as cystic fibrosis, that are caused by a single gene.
One challenge with leading killers like cancer and heart disease is that they’re usually polygenic: linked to many different genes with complex interactions. Patients such as Collins can now take tests that assess thousands of DNA data points to decode these complexities and compute the disease risks. Genomic Prediction, the five-year-old New Jersey company that handled the tests for her fertility clinic, generates polygenic risk scores, predicting in percentage terms each embryo’s chances of contracting each disease in the panel, plus a composite score for overall health. Parents with multiple embryos can then weigh the scores when deciding which one to implant.
...
This new form of genetic embryo testing appears to move humanity one step closer to control of its evolution. The $14 billion IVF industry brings more than 500,000 babies into the world each year, and with infertility rates rising, the market is expected to more than double this decade. Companies including Genomic Prediction bet many going into that process have seen enough loved ones suffer from a polygenic disease to want risk scoring.
[ Note I think the number of IVF babies born worldwide each year is more like 1 million, but there is some uncertainty in estimates. ]
...
In December, Genomic Prediction doubled its venture funding to about $25 million and says it will use the cash to expand and add to its testing panel. Boston IVF, one of the biggest fertility networks in the US, recently started offering Genomic Prediction’s polygenic testing to its patients, says CEO David Stern. “Like anything else, you have early adopters,” he says. “We have had patients who worked in the biotech field or the Harvard milieu who came in and asked for it.” Stern predicts that, like egg freezing, polygenic embryo testing will grow slowly at first, but steadily, and eventually demand will reflect the powerful appeal of lowering a child’s odds for disease.
...
Believers such as Collins and her husband support government subsidies for fertility and parenthood but aren’t interested in any conversation about slowing down. “This is about the people who care about giving their children every opportunity,” she says. “I do not believe that law or social norms are going to stop parents from giving their kids advantages.”
This article is well-written and informative. It covers polygenic screening from multiple perspectives: the parents who want a healthy child, the IVF doctors and genetic counselors who help the parents toward that goal, the scientists who study polygenic prediction and its ability to differentiate risk among siblings (i.e., embryos), the bioethicists who worry about a slippery slope to GATTACA.
An important point that is not discussed in the article (understandable, given the complexity of the topics listed above), is that precise genotyping of embryos leads to higher success rates in IVF.
... improved success rates resulting from higher accuracy in aneuploidy screening of embryos will affect millions of families around the world, and over 60% of all IVF families in the US.
The SNP array platform allows very accurate genotyping of each embryo at ~1 million locations in the genome, and the subsequent bioinformatic analysis produces a much more accurate prediction of chromosomal normality than the older methods.
Millions of embryos are screened each year using PGT-A, about 60% of all IVF embryos in the US.
Klaus Wiemer is the laborator director for Poma Fertility near Seattle. He conducted this study independently, without informing Genomic Prediction.
There are ~3000 embryos in the dataset, all biopsied at Poma and samples allocated to three testing labs A,B,C using the two different methods. The family demographics (e.g., maternal age) were similar in all three groups. Lab B is Genomic Prediction and A,C are two of the largest IVF testing labs in the world, using NGS.
The results imply lower false-positive rates, lower false-negative rates, and higher accuracy overall from our methods. These lead to a significantly higher pregnancy success rate.
The new technology has the potential to help millions of families all over the world.
This increase in pregnancy success rates was not something we directly aimed for -- rather, we were simply trying to get the most accurate characterization of chromosomal abnormality (aneuploidy) using the high precision genotype from our platform. After Dr. Wiemer surprised us with these results, it became plausible that significant increases in success rates per IVF cycle could still exist as low-hanging fruit. The ~3k embryos used in his study are considered a big sample size in fertility research, whereas in genomics today a big sample is hundreds of thousands or a million individuals.
Prioritizing research in IVF using large sample sizes could plausibly raise success rates per cycle to, e.g., ~80%. The qualitative experience of parents using IVF will improve with average success rates, perhaps relieving much of the angst and uncertainty.
Theodore A. Postol is professor emeritus of Science, Technology, and International Security at the Massachusetts Institute of Technology. He is widely known as an expert on nuclear weapons and missile technology.
Educated in physics and nuclear engineering at MIT, he was a researcher at Argonne National Lab, worked at the Congressional Office of Technology Assessment, and was scientific advisor to the Chief of Naval Operations.
After leaving the Pentagon, Postol helped to build a program at Stanford University to train mid-career scientists to study weapons technology in relation to defense and arms control policy.
He has received numerous awards, including the Leo Szilard Prize from the American Physical Society for "incisive technical analysis of national security issues that [have] been vital for informing the public policy debate", the Norbert Wiener Award from Computer Professionals for Social Responsibility for "uncovering numerous and important false claims about missile defenses", and the Richard L. Garwin Award "that recognizes an individual who, through exceptional achievement in science and technology, has made an outstanding contribution toward the benefit of mankind."
Steve and Ted discuss:
0:00 Introduction
2:02 Early life in Brooklyn, education at MIT, work at the Pentagon
20:27 Reagan’s “Star Wars” defense plan
28:26 U.S. influence on Russia and China’s second-strike capabilities
Ted Postol: ... So, you've got to listen to Putin's voice dispassionately. And when you listen to him, he makes it clear numerous times, numerous times that he doesn't think American missile defense is a worth anything, but he also is worried about an American president who might believe otherwise, and who might take steps against Russia, that would then lead to an action-reaction cycle that would get us, get us all killed.
In other words, he's not just worried about the system, whether it can work, he's worried about American political leadership and what they think, or if they think, or if they know. And that was, you know, I was very receptive to understanding that because that's exactly what I went through, you know, 30 years earlier when I was at the Pentagon, looking at this dog of a missile defense.
And so, the Chinese look at this, they know the Americans are lying to them all the time. I could give you a good story about South Korea and the way we lied to the South Koreans and lied to the Chinese.
I was really furious with that. That was under Secretary of State Hillary Clinton.
And my view is...
And my view is if you're lying to an ally and you're lying, you know, I have very good friends. I'm very, very proud to say I have some very good friends who are high-level diplomats, and I've asked every one of them, would you lie in a negotiation? And every one of them has said, no. In other words, your credibility depends on your honesty.
You might not say something that, you know, could be relevant to a negotiation relevant to your adversary's thinking, but you would never lie because your credibility will, you'll never be believed again. That's their view of this.
And here we were under Hillary Clinton lying to an ally and lying to the Chinese, who I knew through my personal contacts, understood that we were lying to them. I know from personal contacts with the Chinese.
So, how do you expect people to treat you when they know you're a liar? To me, it's just simple human relations. And, and I now understand that because I have friends who are both diplomats and soldiers, and I know, if you have to lie to make a point there's something wrong and you're, you're jeopardizing your credibility with other professionals if, if you do that.
So, we should not be surprised that the Chinese are increasing their forces.
And when Putin marched out this horrifying Poseidon underwater torpedo, could potentially carry a hundred megaton warhead. It's nuclear-powered. It can travel at some very high speed, 50, 60 knots or more, and then it can go quiet, sneak into a Harbor, know coastal Harbor and detonate underwater, and destroy out to 30 or 40 kilometers, a complete area, urban area. And he has this weapon. He made it obvious that he had it. He showed plans for it.
Ted Postol: Well, what he was doing is he was saying to an American president who knows nothing. All right, assuming that the president knows nothing, that your missile defenses will not do anything about this weapon. That's what he did it for. He was an insurance policy toward bad decision-making by American political leadership. That's why he built that weapon. That's why he ordered that weapon built.
So not because, I mean, he may be a monster. That's another issue, but it's not because he was a monster, it's because he made a strategic calculation that that kind of weapon would cause any person, even if they were totally without knowledge and thought of how missile defense could work, to understand that you will not escape retribution if you attack Russia. That's why that weapon was built.
Center for Gravitation and Cosmology, Yangzhou University (May 16 2022)
There were several good questions at the end, and a discussion of the following rather fundamental topic.
In the conventional description of quantum measurement a pure state evolves into a mixed state, with probabilities of distinct outcomes (non-unitary von Neumann projection).
What Hawking suggested is that a black hole (i.e., gravity) causes pure states to evolve into mixed states.
But if pure states already evolve into mixed states in ordinary quantum mechanics, why is it problematic for black hole physics (gravity) to have this effect?
Title: Quantum Hair and Black Hole Information
Abstract: I discuss recent results concerning the quantum state of the gravitational field of a compact matter source such as a black hole. These results demonstrate the existence of quantum hair, violating the classical No Hair Theorems. I then discuss how this quantum hair affects Hawking radiation, allowing unitary evaporation of black holes. Small corrections to leading order Hawking radiation amplitudes, with weak dependence on the external graviton state, are sufficient to produce a pure final radiation state. The radiation state violates the factorization assumption made in standard formulations of the information paradox. These conclusions are consequences of long wavelength properties of quantum gravity: no special assumptions are made concerning short distance (Planckian) physics.
The talk is pitched at a slightly more expert audience than previous versions I have given.
There are interesting comments by and discussions with G. Veneziano, V. Rubakov, Suvrat Raju and others during the seminar.
The Zoom client on ChromeOS does not allow me to see others in the meeting when I share my slides fullscreen. So at times I was not sure whose questions I was responding to!
Abstract: I discuss recent results concerning the quantum state of the gravitational field of a compact matter source such as a black hole. These results demonstrate the existence of quantum hair, violating the classical No Hair Theorems. I then discuss how this quantum hair affects Hawking radiation, allowing unitary evaporation of black holes. Small corrections to leading order Hawking radiation amplitudes, with weak dependence on the external graviton state, are sufficient to produce a pure final radiation state. The radiation state violates the factorization assumption made in standard formulations of the information paradox. These conclusions are consequences of long wavelength properties of quantum gravity: no special assumptions are made concerning short distance (Planckian) physics.
Raghu Parthasarathy is the Alec and Kay Keith Professor of Physics at the University of Oregon. His research focuses on biophysics, exploring systems in which the complex interactions between individual components, such as biomolecules or cells, can give rise to simple and robust physical patterns.
Raghu is the author of a recent popular science book, So Simple a Beginning: How Four Physical Principles Shape Our Living World.
Steve and Raghu discuss:
0:00 Introduction
1:34 Early life, transition from Physics to Biophysics
20:15 So Simple a Beginning: discussion of the Four Physical Principles in the title, which govern biological systems
26:06 DNA prediction
37:46 Machine learning / causality in science
46:23 Scaling (the fourth physical principle)
54:12 Who the book is for and what high schoolers are learning in their bio and physics classes
1:05:41 Science funding, grants, running a research lab
1:09:12 Scientific careers and radical sub-optimality of the existing system
It was a fascinating episode, and I immediately went out and ordered the book! One question that came to mind: given how much of the human genome is dedicated to complex regulatory mechanisms and not proteins as such, it seems unintuitive to me that so much of heritability seems to be additive. I would have thought that in a system with lots of complicated,messy on/off switches, small genetic differences would often lead to large phenotype differences -- but if what I've heard about polygenic prediction is right, then, empirically, assuming everything is linear seems to work just fine (outside of rare variants, maybe). Is there a clear explanation for how complex feedback patterns give rise to linearity in the end? Is it just another manifestation of the central limit theorem...?
steve hsu
This is an active area of research. It is somewhat surprising even to me how well linearity / additivity holds in human genetics. Searches for non-linear effects on complex traits have been largely unsuccessful -- i.e., in the sense that most of the variance seems to be controlled by additive effects. By now this has been investigated for large numbers of traits including major diseases, quantitive traits such as blood biomarkers, height, cognitive ability, etc.
One possible explanation is that because humans are so similar to each other, and have passed through tight evolutionary bottlenecks, *individual differences* between humans are mainly due to small additive effects, located both in regulatory and coding regions.
To genetically edit a human into a frog presumably requires many changes in loci with big nonlinear effects. However, it may be the case that almost all such genetic variants are *fixed* in the human population: what makes two individuals different from each other is mainly small additive effects.
Zooming out slightly, the implications for human genetic engineering are very positive. Vast pools of additive variance means that multiplex gene editing will not be impossibly hard...
This is a long interview I did recently with Cactus Chu, a math prodigy turned political theorist and podcaster. (Unfortunately I can't embed the podcast here.)
My research group contributed a chapter to this new book on Complex Trait Prediction (see below). The book is somewhat unique, covering applications to humans, plants, and animals all in a single volume.
This volume explores the conceptual framework and the practical issues related to genomic prediction of complex traits in human medicine and in animal and plant breeding. The book is organized into five parts. Part One reminds molecular genetics approaches intending to predict phenotypic variations. Part Two presents the principles of genomic prediction of complex traits, and reviews factors that affect its reliability. Part Three describes genomic prediction methods, including machine-learning approaches, accounting for different degree of biological complexity, and reviews the associated computer-packages. Part Four reports on emerging trends such as phenomic prediction and incorporation into genomic prediction models of “omics” data and crop growth models. Part Five is dedicated to lessons learned from case studies in the fields of human health and animal and plant breeding, and to methods for analysis of the economic effectiveness of genomic prediction.
Written in the highly successful Methods in Molecular Biology series format, the book provides theoretical bases and practical guidelines for an informed decision making of practitioners and identifies pertinent routes for further methodological researches.
Cutting-edge and thorough, Complex Trait Predictions: Methods and Protocols is a valuable resource for scientists and researchers who are interested in learning more about this important and developing field.
Decoding the genome confers the capability to predict characteristics of the organism (phenotype) from DNA (genotype). We describe the present status and future prospects of genomic prediction of complex traits in humans. Some highly heritable complex phenotypes such as height and other quantitative traits can already be predicted with reasonable accuracy from DNA alone. For many diseases, including important common conditions such as coronary artery disease, breast cancer, type I and II diabetes, individuals with outlier polygenic scores (e.g., top few percent) have been shown to have 5 or even 10 times higher risk than average. Several psychiatric conditions such as schizophrenia and autism also fall into this category. We discuss related topics such as the genetic architecture of complex traits, sibling validation of polygenic scores, and applications to adult health, in vitro fertilization (embryo selection), and genetic engineering.
Theory seminar at Michigan State University April 22 2022.
Title: Has Hawking's Black Hole Information Paradox Been Resolved?
Abstract: In 1976 Stephen Hawking argued that black holes cause pure states to evolve into mixed states. Put another way, quantum information that falls into a black hole does not escape in the form of radiation. Rather, it vanishes completely from our universe, thereby violating a fundamental property of quantum mechanics called unitarity. I give a pedagogical introduction to this paradox, suitable for non-experts. Then I discuss recent results concerning the quantum state of the gravitational field of a compact matter source. These results demonstrate the existence of quantum hair, violating the classical No Hair Theorems. I then discuss how this quantum hair affects Hawking radiation, allowing unitary evaporation of black holes.
Carl Zha is the host of the Silk and Steel podcast, which focuses on China, history, culture, and politics. He is a former engineer now based in Bali, Indonesia.
Scott Aaronson is the David J. Bruton Centennial Professor of Computer Science at The University of Texas at Austin, and director of its Quantum Information Center. Previously, he taught for nine years in Electrical Engineering and Computer Science at MIT. His research interests center around the capabilities and limits of quantum computers, and computational complexity theory more generally.
Sebastian Mallaby is a writer and journalist whose work covers financial markets, international relations, innovation, and technology. He is the author of "The Power Law: Venture Capital and the Making of the New Future."
Steve and Sebastian discuss venture capital, tech startups, business model and technology innovation, global adoption of the Silicon Valley model, and the future of innovation.
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