10 Downing Street

Manifold Podcast #19: Ted Chiang on Free Will, Time Travel, Many Worlds, Genetic Engineering, and Hard Science Fiction

Steve and Corey speak with Ted Chiang about his recent story collection Exhalation and his inaugural essay for the New York Times series, Op-Eds from the Future. Chiang has won Nebula and Hugo awards for his widely influential science fiction writing. His short story Story of Your Life, became the film Arrival (2016). Their discussion explores the scientific and philosophical ideas in Ted's work, including whether free will is possible, and implications of AI, neuroscience, and time travel. Ted explains why his skepticism about whether the US is truly a meritocracy leads him to believe that the government-funded genetic modification he envisages in his Op-Ed would not solve the problem of inequality.

Transcript

Ted Chiang's New York Times Op-Ed From the Future

Exhalation by Ted Chiang

Stories of Your Life and Others by Ted Chiang


man·i·fold /ˈmanəˌfōld/ many and various.

In mathematics, a manifold is a topological space that locally resembles Euclidean space near each point.

Steve Hsu and Corey Washington have been friends for almost 30 years, and between them hold PhDs in Neuroscience, Philosophy, and Theoretical Physics. Join them for wide ranging and unfiltered conversations with leading writers, scientists, technologists, academics, entrepreneurs, investors, and more.

Steve Hsu is VP for Research and Professor of Theoretical Physics at Michigan State University. He is also a researcher in computational genomics and founder of several Silicon Valley startups, ranging from information security to biotech. Educated at Caltech and Berkeley, he was a Harvard Junior Fellow and held faculty positions at Yale and the University of Oregon before joining MSU.

Corey Washington is Director of Analytics in the Office of Research and Innovation at Michigan State University. He was educated at Amherst College and MIT before receiving a PhD in Philosophy from Stanford and a PhD in a Neuroscience from Columbia. He held faculty positions at the University Washington and the University of Maryland. Prior to MSU, Corey worked as a biotech consultant and is founder of a medical diagnostics startup.

London and Tallinn

I'll be speaking about AI and Health in Tallinn, after a stop in London to help the Tories prepare for the upcoming general election ;-)

Tallinn Digital Summit is where the frontrunners of digital nations drive the global conversation on digitalization.

Over the course of a day political leaders, policy innovators, thought-leaders, entrepreneurs and tech-community spotlight the most topical matters of digital transformation and tackle questions about its implications on economies, societies and governments. TDS is an annual meeting place for enhancing practical sharing of ideas and lessons to chase the opportunities of digital transformation for economy, e-governance development as well as societies. Also, to shape a more coherent approach to challenges brought by digital transformation.

Being one of the most digitally advanced countries, Estonia is an ideal location for the event. It has significant experience in building a digital society and economy, having built its digital core on secure distributed architecture. The country is also an outsized creator and exporter of startups, and possesses considerable cybersecurity expertise. Tallinn also hosts the HQ of NATO Cyber Defence Centre of Excellence and the European Agency for the Operational Management of Large-Scale IT Systems.

Manifold podcast #18: Rebecca Campbell on Identifying Serial Perpetrators, Rape Investigations, and Untested Rape Kits

Dr. Rebecca Campbell is Professor of Psychology at Michigan State University. Her research focuses on violence against women and children with an emphasis on sexual assault. Steve and Corey discuss her recent National Institute of Justice-funded project to study Detroit’s untested rape kits. Dr. Campbell describes the problem of untested kits and her work with police departments around the country to reduce the backlog. She explains how the use of the national CODIS database has led to sharply higher estimates of the proportion of rapes committed by serial perpetrators and how many rapists appear to be criminal “generalists” -- committing a wide range of offenses. She describes the dynamics of sexual assault investigations, the factors that lead police to put more effort into investigating certain cases over others, and how police questioning of women can lead them to disengage from the process. Other topics include the incentives at work in law enforcement, the slow pace at which new research in DNA testing and treatment of victims is incorporated into police training, and Dr. Campbell’s efforts to engage with law enforcement agencies to improve investigative practices.

Transcript

Additional links to research articles and media coverage


man·i·fold /ˈmanəˌfōld/ many and various.

In mathematics, a manifold is a topological space that locally resembles Euclidean space near each point.

Steve Hsu and Corey Washington have been friends for almost 30 years, and between them hold PhDs in Neuroscience, Philosophy, and Theoretical Physics. Join them for wide ranging and unfiltered conversations with leading writers, scientists, technologists, academics, entrepreneurs, investors, and more.

Steve Hsu is VP for Research and Professor of Theoretical Physics at Michigan State University. He is also a researcher in computational genomics and founder of several Silicon Valley startups, ranging from information security to biotech. Educated at Caltech and Berkeley, he was a Harvard Junior Fellow and held faculty positions at Yale and the University of Oregon before joining MSU.

Corey Washington is Director of Analytics in the Office of Research and Innovation at Michigan State University. He was educated at Amherst College and MIT before receiving a PhD in Philosophy from Stanford and a PhD in a Neuroscience from Columbia. He held faculty positions at the University Washington and the University of Maryland. Prior to MSU, Corey worked as a biotech consultant and is founder of a medical diagnostics startup.

Former Yale Law Dean on Harvard anti-Asian discrimination case: The facts are just so embarrassing to Harvard... Quotas and a climate of dishonesty

The excerpt below is from a recent interview in the Chronicle of Higher Education. Anthony Kronman was Dean of Yale Law School from 1994 to 2004 (Yale JD and PhD in Philosophy). These are elite establishment credentials. Yet the observations he makes rather matter of factly below are not to be found in the national media coverage nor in the public remarks of university administrators.

The focus of the Chronicle interview is Kronman's recent book The Assault on American Excellence, which does not, as far as I know, address Asian American university admissions. In case you are wondering, Kronman is an anti-Trump lifelong democrat.

Chronicle: What are your thoughts about the Harvard anti-Asian discrimination case?

... The facts are just so embarrassing to Harvard that with some modest adjustment in its admissions practices it might be able to absorb a judgment against it and get on with life more or less as usual. The vagueness of the category on which Harvard was relying to make sure that it kept its Asian undergraduates at the level that it wished, the so-called personality score, is such a floppy nothing of an empty basket — that’s not gonna do anymore.

There is something profoundly disturbing about Harvard using these flaccid categories to achieve something like a quota. The court papers show how the system was invented to keep the number of Jews down in the late 1920s and early 1930s. It’s all pretty bad, and part of the badness is that colleges have been both compelled and allowed to do what they’re doing under the rubric of "diversity," which conceals from view the actual operation of the whole system, and what they are in fact aiming to achieve. It’s substituting one vocabulary for another in a way that creates a climate of dishonesty. What goes on in the admissions office is increasingly mysterious, and what happens once students are admitted — that is something to which little attention is paid by educators themselves.

[ Italics mine ]

Kronman is presumably aware that other Ivy schools like Yale are little different from Harvard when it comes to undergraduate admissions.

See also

Harvard Admissions on Trial

Harvard discrimination lawsuit: data show penalization of Asian-Americans on subjective personality evaluation

Harvard Office of Institutional Research on Discrimination Against Asian-American Applicants

"When it comes to the score assigned by the Admissions Office, Asian-American applicants are assigned the lowest scores of any racial group. ... By contrast, alumni interviewers (who actually meet the applicants) rate Asian-Americans, on average, at the top with respect to personal ratings—comparable to white applicants ..."

Genomic Prediction of Complex Traits and Disease Risks (video of talk at IGI and OpenAI)

Seminar at the Innovative Genomics Institute (IGI, Berkeley and UCSF) July 17 2019. I gave a similar talk the following day at OpenAI. Jennifer Doudna, one of the co-discoverers of CRISPR-Cas9 gene editing, is the Executive Director of IGI. You might recognize her voice if you can hear the audience questions.

IGI began in 2014 through the Li Ka Shing Center for Genetic Engineering, which was created thanks to a generous donation from the Li Ka Shing Foundation. The Innovative Genomics Initiative formed as a partnership between the University of California, Berkeley and the University of California, San Francisco. Combining the fundamental research expertise and the biomedical talent at UCB and UCSF, the Innovative Genomics Initiative focused on unraveling the mechanisms underlying CRISPR-based genome editing and applying this technology to improve human health.

Slides -- slightly updated from the ones I used in the talk.

Title: Genomic Prediction of Complex Traits and Disease Risks via AI/ML and Large Genomic Datasets

Abstract: The talk is divided into two parts. The first gives an overview of the rapidly advancing area of genomic prediction of disease risks using polygenic scores. We can now identify risk outliers (e.g., with 5 or 10 times normal risk) for about 20 common disease conditions, ranging from diabetes to heart diseases to breast cancer, using inexpensive SNP genotypes (i.e., as offered by 23andMe). We can also predict some complex quantitative traits (e.g., adult height with accuracy of few cm, using ~20k SNPs). I discuss application of these results in precision medicine as well as embryo selection in IVF, and give some details about genetic architectures. The second part covers the AI/ML used to build these predictors, with an emphasis on "sparse learning" and phase transitions in high dimensional statistics.

College quality measures highly correlated to student SAT scores

Research by Brown, Chabris, and Wai shows that quality of students is strongly correlated to other quality measures of a college. (Thanks to a reader for sending the link!) See also this global analysis of university quality rankings.

Of course, causality is complex: schools with strong reputations, large endowments, etc. can attract top applicants. But how did those schools acquire those reputations and endowments in the first place?

Salon: ... Though there is often public controversy over the value of standardized tests, research shows that these tests are quite robust measures to predict academic performance, career potential, creativity and job performance.

Critics of the SAT say it tests for students’ wealth, not caliber. While it is true that wealthier parents tend to have students with higher test scores, it turns out the research robustly shows that test scores, even when you consider socioeconomic status, are predictive of later outcomes.

We first found high correlations between our test score rankings and U.S. News national university rank – 0.892 – and liberal arts college rank – 0.890 – even though U.S. News weights these scores only about 8% in their formula. ...

See also Universities Ranked By SAT Score (2013):

Schools with the strongest students (e.g., as measured by SAT) produce graduates who make outstanding contributions at per capita rates easily 10x or 100x higher than others: see Where Nobel winners get their start (Nature) and Colleges ranked by Nobel, Fields, Turing and National Academies output.

Dept. of Physicists Can Do Stuff: Brexit!

Dominic Cummings on how Vote Leave won the Brexit campaign. (Video should start at 13m30s.)

Dom hired a team of physicists and data scientists who

1. Studied the literature on elections (i.e., entered a well-established subject, studying it de novo, applying real horsepower), figured out which results/beliefs in that field were likely correct (much found was incorrect)

2. Adapted results to the job at hand (Brexit referendum) and invented new techniques for applying them

3. Built a new platform, wrote new code, executed in real time, and won a huge electoral victory against all odds.

Of course, this is the age old story of physicists invading/creating other fields: early computing, electrical engineering, molecular biology, computational biology, quantitative finance, high frequency trading, etc.

This victory will have historical reverberations that are still playing out.

13m35s: ... we had to take risks and we had to do things in a slightly new way so one of the basic things that I did was I brought in a team of physicists who essentially looked at campaigning from complete first principles and what they did was they went they simply scanned around the world and they said what studies have been done on issues of turnout and persuasion that actually have good maths behind them to support and have been replicated and we can actually have confidence in and they basically filtered all when through filtered them all out and came back to me in the team and said here is a small selection of things actually high quality or reasonable quality work which you can rely upon and here are the principles that you can see in these studies that have been replicated with randomised controlled trials and whatnot in the States

we basically created a checklist of what these things were and we built the communications team around trying to exploit each of these elements which the physicists found they also constructed models to help direct resources on the ground campaigns to wedge where to send your activists and the digital campaign how do you actually do that in a in a scientific way and essentially you had streams of data coming in from all sorts of different ways the website email on the ground canvassing a social media blah blah all of this stuff could be traditional polling all of the stuff coming in and you had the data science people sitting at the heart of the operation and essentially taking our core messages and just running experimentally a whole bunch of different things on Facebook and elsewhere and then figuring out what what things and what things don't work and we started off with relatively small amounts of money just to run this experimental process

another thing which which I'll go into a little bit of detail because it's from perhaps of interest regarding this election is we did a new kind of polling so I'm sure all of you know the polling methodology used throughout the world essentially the same system that was invented in the late 1930s and the idea of it is yo you take roughly speaking a thousand person sample and if it's random a representative then you can rely on the mathematics of the normal distribution and the famous bell curve and you that should give you a pretty accurate picture of what people think for various reasons that is becoming harder and harder to do happy to answer questions about why that is but leaving that aside what the physicists said was this is actually not the way that you would invent polling if you were going to invent polling now the way actually to do it is take massive samples of hundreds of thousands of people ideally actually millions of people but say hundreds thousands people and then use machine learning and you will actually have a system which is faster cheaper more accurate and never has another great advantage which we exploited which is that if you do these very large sample surveys you then have sub sample you can define the demographics that you interrogate yourself and what we did was we basically use the exact same categories infer demographics that Facebook uses for its digital advertising platform so we sucked in data on the precise same basis that Facebook marketing allows and then we had therefore large sub samples of the overall polling samples which you could actually rely on and then you could take that data and plug it straight back into Facebook so you could say for example we will target women between 35 and 45 who live in these particular geographical entities who don't have a degree or who do have a degree or whatever it's after cetera

and because you've got very large samples you can actually get useful information on those kind of relatively small breakdowns so we did all this and we as I said we essentially ran a whole series of experiments based on what we found at the conventional polling in the focus groups out in the digital world and then filtered what worked and then we held back almost all of our budget and then we basically dumped the entire budget or in the last ten days...

See also Dept. of Physicists Can Do Stuff: Gene Sequencing, Harold Brown, Ashton Carter.

More Dom.

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.

...

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 ... 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.

Manifold #17: Mark Moffett on the Life and Death of Human Societies

Steve and Corey talk with Mark Moffett, Photographer and Research Fellow at the Smithsonian Institute, about his new book The Human Swarm: How our Societies Arise, Thrive and Fall. They discuss Mark’s view that being able walk into a cafe filled with others and not be attacked illustrates what makes human societies distinct and so successful. Mark explains why he is far more interested in questions about when war and other events occur than with traditional issues such as the genetic origins of human behavior. The three discuss Dehumanization and its Chimp equivalent, Dechimpanizeeization, and how they lead to the division of societies, friend turning against friend, and genocide. They discuss the conditions under which foreigners are embraced and whether the US might ever enter into a post-racial society where group differences don’t matter and immigrants are more easily accepted.

Mark Moffett's Bio

Mark Moffett's Photography

The Human Swarm: How Our Societies Arise, Thrive, and Fall

Transcript

man·i·fold /ˈmanəˌfōld/ many and various.

In mathematics, a manifold is a topological space that locally resembles Euclidean space near each point.

Steve Hsu and Corey Washington have been friends for almost 30 years, and between them hold PhDs in Neuroscience, Philosophy, and Theoretical Physics. Join them for wide ranging and unfiltered conversations with leading writers, scientists, technologists, academics, entrepreneurs, investors, and more.

Steve Hsu is VP for Research and Professor of Theoretical Physics at Michigan State University. He is also a researcher in computational genomics and founder of several Silicon Valley startups, ranging from information security to biotech. Educated at Caltech and Berkeley, he was a Harvard Junior Fellow and held faculty positions at Yale and the University of Oregon before joining MSU.

Corey Washington is Director of Analytics in the Office of Research and Innovation at Michigan State University. He was educated at Amherst College and MIT before receiving a PhD in Philosophy from Stanford and a PhD in a Neuroscience from Columbia. He held faculty positions at the University Washington and the University of Maryland. Prior to MSU, Corey worked as a biotech consultant and is founder of a medical diagnostics startup.

MSU New Faculty Welcome 2019

These are excerpts from remarks I gave yesterday at a reception for new faculty.

Good afternoon and Welcome!

We are so pleased that you are here at Michigan State University. You have joined a great research university, at a very exciting time.

I’m told I only have 10 minutes in which to say something about the deep and varied research enterprise here at MSU. That’s only enough time for a high level overview, so let me start with some big picture numbers. Each year the National Science Foundation publishes its Higher Education Research and Development (or HERD) report on the total research expenditures of all US universities. MSU’s total HERD number has grown from about $500M to $700M in the last seven years. We’ve advanced faster than any other Big Ten university, and now rank 32nd in the US among all universities.

MSU is ahead of Rutgers, UT Austin, Illinois (UIUC), Purdue, Arizona, Maryland, Indiana, Iowa, ASU, Colorado (Boulder), and UVA.

Based on the HERD comparison data, MSU ranks 1st in the nation in combined Department of Energy and National Science Foundation research expenditures.

Almost all of the schools ranked above us (and many below) have major research hospitals. In those cases, the medical research component of the HERD total often exceeds the rest of campus combined. At MSU, about ~$100M of our total comes from NIH. We still have significant room to advance.

There are only a few schools without a major medical complex that rank above us -- let me mention two: UC Berkeley $771M (top public university in the US; home of Lawrence Berkeley National Lab) and MIT $952M (home of Lincoln Laboratory, a major defense research lab).

MSU, UC Berkeley, and MIT are all research powerhouses. But we are similar in another important way: all three are land-grant universities. As land-grant universities, we pride ourselves on making breakthroughs in basic research, and applying those breakthroughs to make life better for the entire world.

... MSU is home to the Facility for Rare Isotope Beams, a scientific user facility for the Office of Nuclear Physics in the Office of Science of the U.S. Department of Energy.

FRIB will be operational in 2021 and will deliver the highest intensity beams of rare isotopes available anywhere in the world. Estimates of the total investment in this project are roughly $1 billion dollars. Operated by MSU, FRIB will enable scientists to make discoveries about the properties of rare isotopes (which are unusual forms of the elements) in order to better understand the physics of nuclei, nuclear astrophysics, and the fundamental interactions of nature. It will also produce practical applications for society, including in medicine, homeland security, and industry.

... Another recent development is a new department called Computational Mathematics, Science, and Engineering or CMSE. This department was planned, authorized, and operational in only three years—quite a feat in academia. I often compare “startup time” (the fast pace at which things are accomplished in Silicon Valley) to “academic time” (i.e., nothing gets done, other than committee meetings, and a no-brainer project takes a decade to complete), but with CMSE this was a case of something on campus getting done in startup time. CMSE is one of very few such departments in the country -- it is focused on data science, machine learning, advanced computation and related applications, but is not a traditional CS department. It supports many of the new efforts on campus that require the analysis of large data sets and development of new tools and algorithms. Researchers in this department utilize datasets drawn from astrophysics, business analytics, mobile data, materials science, human and plant genomics, and many other areas. The department was conceived as fundamentally interdisciplinary -- bringing together experts in computation with subject matter experts in areas of science which are becoming increasingly reliant on data.

I can’t help mentioning a couple of big data examples related to my own research: we’ve created a compute resource with more than 500k human genomes, open to interested investigators on campus. All of the data is stored at our High Performance Computing Center or HPCC. Using this data, our collaboration demonstrated for the first time that machine learning applied to large genomic datasets could produce accurate predictors for complex human traits. We can now predict adult human height from genome alone, with accuracy roughly 1 inch. The predictor uses ~20k genetic variants distributed throughout the genome. Predictors of complex disease risk, for conditions such as heart disease, diabetes, schizophrenia, and breast cancer, have been developed and broadly replicated in out-of-sample tests. I recently participated in a meeting at No 10 Downing Street in the UK, to plan a project which will genotype 5 million individuals through their National Healthcare System. This is only the beginning for genomic Precision Medicine.

... If there is a problem -- tell us about it! -- whether it has to do with grant submissions, or startup incubation, or child care, food options on campus, your functional or dysfunctional department. We’re here to fix things, and to provide the best possible environment for your teaching, research, and creative activity.

Only one in a thousand people in our society have the privilege to engage full time in discovery -- in curiosity driven research -- for the benefit of humankind. You are part of that lucky one in a thousand, and we are here to help you succeed.

The bar has been set very high, but with the resources and new opportunities here at MSU, your potential is limitless.

My very best wishes to you all :-)

Polygenic Architecture and Risk Prediction for 14 Cancers and Schizophrenia

Two recent papers on polygenic risk prediction. As I've emphasized before, these predictors already have real clinical utility but they will get significantly better with more training data.

Assessment of Polygenic Architecture and Risk Prediction based on Common Variants Across Fourteen Cancers

Yan Zhang et al.

We analyzed summary-level data from genome-wide association studies (GWAS) of European ancestry across fourteen cancer sites to estimate the number of common susceptibility variants (polygenicity) contributing to risk, as well as the distribution of their associated effect sizes. All cancers evaluated showed polygenicity, involving at a minimum thousands of independent susceptibility variants. For some malignancies, particularly chronic lymphoid leukemia (CLL) and testicular cancer, there are a larger proportion of variants with larger effect sizes than those for other cancers. In contrast, most variants for lung and breast cancers have very small associated effect sizes. For different cancer sites, we estimate a wide range of GWAS sample sizes, required to explain 80% of GWAS heritability, varying from 60,000 cases for CLL to over 1,000,000 cases for lung cancer. The maximum relative risk achievable for subjects at the 99th risk percentile of underlying polygenic risk scores, compared to average risk, ranges from 12 for testicular to 2.5 for ovarian cancer. We show that polygenic risk scores have substantial potential for risk stratification for relatively common cancers such as breast, prostate and colon, but limited potential for other cancer sites because of modest heritability and lower disease incidence.

Some people are surprised that a mental disorder might be strongly controlled by genetics -- why? However, it has been known for some time that schizophrenia is highly heritable. I anticipate that good predictors for Autism and Alzheimer's disease will be available soon.

Penetrance and Pleiotropy of Polygenic Risk Scores for Schizophrenia in 106,160 Patients Across Four Health Care Systems

Amanda B. Zheutlin et al.

Objective:
Individuals at high risk for schizophrenia may benefit from early intervention, but few validated risk predictors are available. Genetic profiling is one approach to risk stratification that has been extensively validated in research cohorts. The authors sought to test the utility of this approach in clinical settings and to evaluate the broader health consequences of high genetic risk for schizophrenia.

Methods:
The authors used electronic health records for 106,160 patients from four health care systems to evaluate the penetrance and pleiotropy of genetic risk for schizophrenia. Polygenic risk scores (PRSs) for schizophrenia were calculated from summary statistics and tested for association with 1,359 disease categories, including schizophrenia and psychosis, in phenome-wide association studies. Effects were combined through meta-analysis across sites.

Results:
PRSs were robustly associated with schizophrenia (odds ratio per standard deviation increase in PRS, 1.55; 95% CI=1.4, 1.7), and patients in the highest risk decile of the PRS distribution had up to 4.6-fold higher odds of schizophrenia compared with those in the bottom decile (95% CI=2.9, 7.3). PRSs were also positively associated with other phenotypes, including anxiety, mood, substance use, neurological, and personality disorders, as well as suicidal behavior, memory loss, and urinary syndromes; they were inversely related to obesity.

Conclusions:
The study demonstrates that an available measure of genetic risk for schizophrenia is robustly associated with schizophrenia in health care settings and has pleiotropic effects on related psychiatric disorders as well as other medical syndromes. The results provide an initial indication of the opportunities and limitations that may arise with the future application of PRS testing in health care systems.

Bruno Maçães on The Power Game in a Connected World

Bruno Maçães in Singapore at IRAHSS Geopolitics Reimagined, 22 July 2019.

Maçães is author of Belt and Road - A Chinese World Order and former Europe Minister of Portugal. He discusses the trade war, his recent visit to a Huawei factory, and the idea of hybrid warfare or weaponized interdependence.

I met with Bruno in Beijing last month. He is among the most insightful geopolitical thinkers today.

02:35
I was shown the assembly line for the P30 smartphone [~$1k flagship using Huawei chipset] and told that this assembly line just two or three years ago was operated by 140 operators people it is now down to 17 by the end of this year we'll be down to 15 it's a very long assembly line perhaps 200 250 meters takes about 30 minutes more important than the time it takes to assemble a P30 is the time between each unit and that's now down to 29 seconds so every 29 seconds a fully produced P30 comes out at the end 17 people operate now this this assembly line but the remarkable thing is that I actually looked very carefully at what the 17 were doing and it's very obvious they're not doing anything of significance they left there more in order to keep a certain control over the process...

07:17
this is not a new Cold War and I see no indications that were moving in that direction China and the United States continue to be turned towards to each other continue to be very interested in learning from each other and I think this is an important point their way of life their ideology the way they look at the world is not predicated on a negation of the other side the Soviet Union was from the very start a revolutionary movement whose whole identity was the negation of capitalist Western Way of life and organizing society now China and the United States in a way are much less connected they are not part of the same history and their dispute is not a dispute about who is fundamentally right about questions that involved both...

08:39
they're not necessarily involved in a death and life struggle between them the world we live in is I'll sum it up this way a world where and this is I think the puzzling element of it we are neither at war nor at peace we are somewhere in the middle conflict takes below takes place below the threshold of kinetic war and other forms of direct confrontation but it is no less intense because of that...

11:21
the tactics might include the purchase of infrastructure in other states the corruption or blackmail of foreign officials important elements of this new world that is not often talked about [CALLING EPSTEIN AND GHISLAINE MAXWELL] manipulation of energy flows or energy prices all of these elements are magnified in an integrated global economy the networks that bring us together are used as tools or instruments of conflict...

More Bruno, on the Belt and Road initiative.

Epstein and the Big Lie

The biggest Epstein conspiracy mystery is not how he died. The more important mystery is how he managed to operate out in the open for 15-20 years. Rumors concerning Epstein and leading figures like Bill Clinton have been around for at least that long. I have been following his activities, at least casually, for well over a decade.

In the 1990s I was a Bill Clinton supporter. I voted for him twice and supported his efforts to move the democratic party in a centrist, pro-business direction. But my brother is a Republican. He fed me a steady stream of anti-Clinton information that I (at the time) dismissed as crazy right-wing conspiracy theories. However, with the advent of the internet in the mid 90s it became easier to obtain information that was not filtered by corrupt mainstream media outlets. I gradually realized that at least some of my brother's claims were correct. For example, Clinton's first presidential bid was almost derailed by charges of adultery by women like Gennifer Flowers. Supporters like myself dismissed these charges as a right-wing smear. However, years later, Clinton admitted under oath that he had indeed had sex with Flowers.

My first exposure to Hillary Clinton was her appearance on 60 Minutes after the SuperBowl in 1992. This was widely regarded to be the emotive performance ("stand by your man") that saved Bill Clinton's presidential candidacy. Hillary affects a fake southern accent and (I believe) lies boldly and convincingly about Flowers to an estimated 50 million Americans. Quite a display of talent.

A side-effect of my history as a Clinton supporter (and gradual enlightenment thanks to my brother!) is that I became quite interested in the tendency of the media to hide obvious truths from the general public. We Americans accept that foreign governments (e.g., the Soviets and "ChiComs") successfully brainwash their people to believe all sorts of crazy and false things. But we can't accept that the same might be true here. (The big difference is that people in the PRC and former Soviet states  -- especially intellectuals -- know propaganda when they see it, whereas most Americans do not...)

It was natural for me to become aware of Epstein once he was linked to Bill Clinton at the very birth of the Clinton Foundation. It was easy to uncover very disturbing aspects of the Epstein story -- including details of his private island, traffic in young women, connections to the rich, the powerful, and even to leading scientists, academics, (many of whom I know) and Harvard University. Almost anyone with access to the internet (let alone an actual journalist) could have discovered these things at any point in the last decade.

But just 6 months ago I could mention Epstein to highly educated "politically aware" acquaintances with absolutely no recognition on their part.

Some obvious, and still unanswered, questions:

Former Federal prosecutor and Labor Secretary R. Alexander Acosta said he was told to lay off Epstein, as he "belongs to intelligence" -- why no media followup on this? (Still don't believe in a Deep State?)

Clinton said he only flew on Epstein's plane 4 times (but 26 is also commonly reported) and never visited the island (despite many eyewitness claims to the contrary). No investigative reporting on this by mainstream media?

Epstein's partner Ghislaine Maxwell is the daughter of Robert Maxwell, a billionaire with possible Mossad connections. What were Epstein's links to Israeli intelligence and national interests? (Robert Maxwell's death is at least as mysterious as Epstein's ...)

Why did it take the FBI so long to get to Epstein's island? What have they found in Epstein's house and on his island? How much blackmail material is there and who is implicated?

Were it not for the possibility that the Epstein scandal might be damaging to Trump, would there be anything close to this level of mainstream media interest?

Why was there almost zero MSM interest in Epstein in the previous 15-20 years?

Someone was protecting Epstein (someone with influence on the DOJ, FBI, perhaps US intelligence) long before Donald Trump had political power of any kind. Why?

What other obvious scandals are hidden in plain sight? Iraq WMD? Spygate? Compromised politicians and national leaders? Blackmail by national intelligence services? Ideology-driven Social Media and Search filtering of information? Ivy League discrimination against Asian Americans? ...

Manifold Episode #16: John Schulman of OpenAI

John Schulman is a research scientist at OpenAI. He co-leads the Reinforcement Learning group and works on agent learning in virtual game worlds (e.g., Dota) as well as in robotics. John, Corey, and Steve talk about AI, AGI (Artificial General Intelligence), the Singularity (self-reinforcing advances in AI which lead to runaway behavior that is incomprehensible to humans), and the creation and goals of OpenAI. They discuss recent advances in language models (GPT-2) and whether these results raise doubts about the usefulness of linguistic research over the past 60 years. Does GPT-2 imply that neural networks trained using large amounts of human-generated text can encode "common sense" knowledge about the world? They also discuss what humans are better at than current AI systems, and near term examples of what is already feasible: for example, using AI drones to kill people.

John Schulman

OpenAI

Better Language Models and Their Implications (GPT-2)

Transcript of show


man·i·fold /ˈmanəˌfōld/ many and various.

In mathematics, a manifold is a topological space that locally resembles Euclidean space near each point.

Steve Hsu and Corey Washington have been friends for almost 30 years, and between them hold PhDs in Neuroscience, Philosophy, and Theoretical Physics. Join them for wide ranging and unfiltered conversations with leading writers, scientists, technologists, academics, entrepreneurs, investors, and more.

Steve Hsu is VP for Research and Professor of Theoretical Physics at Michigan State University. He is also a researcher in computational genomics and founder of several Silicon Valley startups, ranging from information security to biotech. Educated at Caltech and Berkeley, he was a Harvard Junior Fellow and held faculty positions at Yale and the University of Oregon before joining MSU.

Corey Washington is Director of Analytics in the Office of Research and Innovation at Michigan State University. He was educated at Amherst College and MIT before receiving a PhD in Philosophy from Stanford and a PhD in a Neuroscience from Columbia. He held faculty positions at the University Washington and the University of Maryland. Prior to MSU, Corey worked as a biotech consultant and is founder of a medical diagnostics startup.


Sporting my OpenAI t-shirt. Wish I had worn this at Number 10 Downing Street earlier this week ;-)

Different Class Altogether

BBC Radio 4 profile of Dominic Cummings. (Sorry, didn't see any embed code.)

Some interesting comments from Dom's Oxford tutor, Robin James Lane Fox: (@4m50s)

He was extremely sharp, very sure of his own abilities, but had every reason to be... not narrow minded in any way...

BBC: Who is cleverer, Boris Johnson or Dominic Cummings?

Oh Dominic, by a long way.

BBC: A long way?

Different class altogether.

Robin James Lane Fox (Wikipedia), FRSL (born 5 October 1946)[1] is an English classicist, ancient historian and gardening writer known for his works on Alexander the Great.[2] Lane Fox is an Emeritus Fellow of New College, Oxford and Reader in Ancient History, University of Oxford. Fellow and Tutor in Ancient History at New College from 1977 to 2014...

See The Differences are Enormous, Creators and Rulers, and The Gulf is Deep.

How Brexit was won, and the unreasonable effectiveness of physicists.

Jack Kirby Centennial Lecture

The kind of deep and heartfelt tribute only a lifetime fan (fanatic) can deliver. Very insightful history of the greatest American comic book artist.

See also I Love Jack Kirby.

Brainpower Matters: The French H-Bomb

Michel Carayol, father of the French H-Bomb.

The article below illuminates several mysteries concerning the French development of thermonuclear weapons. Why did it take so long? Did the French really need help from the British? Who had the crucial idea of radiation compression?

The original inventors were Ulam and Teller. In the USSR it was Sakharov. The PRC inventor was Yu Min (see Note Added at bottom).

Without men such as these, how long would it have taken to develop breakthrough technologies that defined the modern age?

See also Les Grandes Ecoles, One hundred thousand brains, and Quantum GDP.

THE REAL STORY BEHIND THE MAKING OF THE FRENCH HYDROGEN BOMB

Nonproliferation Review 15:2 353, DOI 10.1080/10736700802117361

Based on the first-person account of coauthor Pierre Billaud, a prominent French participant, this article describes for the first time in such detail the history of the development of the French hydrogen bomb in the 1960s and the organization of military nuclear research in France. ...

On November 1, 1952, the United States conducted its first thermonuclear test, ‘‘Ivy Mike,’’ seven years and three and a half months after its Trinity test. It took the Soviet Union four years (August 29, 1949 -- August 12, 1953) and the United Kingdom four years and seven months (October 3, 1952 -- May 15, 1957) to achieve thermonuclear capacity. And in the following decade, China did it, with its sixth test, in fewer than three years (October 16, 1964 -- June 17, 1967). Yet after Gerboise Bleue it took France eight and a half years to reach the same landmark, detonating its first thermonuclear device on August 24, 1968. Why such a long delay, especially since the French were pioneers in nuclear research?

1965: What We Knew About the Technical Aspects

From 1955 to 1960, as we prepared for the first French atomic test, we were also pondering thermonuclear weapons. But the prospect of hydrogen weapons seemed so far into the future that we did not work seriously on it. ... Li6D was commonly considered the best fuel for thermonuclear weapons, but we did not have any idea about how to burn it. All the problems with the thermonuclear bomb can be summarized by this question: how to discover the process that will allow the Li6D to undergo a fusion reaction?

... Compared to our American colleagues in 1948, French scientists had many advantages: we knew that hydrogen bombs existed and worked and that they used Li6D, and we understood the reactions at work. We also had powerful computers, of U.S. origin, which were not available in the late 1940s. And we knew, more or less, the dimensions and weights of the nuclear weapons deployed at NATO bases in Europe and their yields. ...

De Gaulle: It’s taking forever! ... I want the first experiment to take place before I leave! Do you hear me? It’s of capital importance. Of the five nuclear powers, are we going to be the only one which hasn’t made it to the thermonuclear level? Are we going to let the Chinese get ahead of us? If we do not succeed while I am still here, we shall never make it! My successors, from whatever side, will not dare to go against the protests of the Anglo-Saxons, the communists, the old spinsters and the Church. And we shall not open the gate. But if a first explosion happens, my successors will not dare to stop halfway into the development of these weapons.


... In January 1967, I published a voluminous report wherein I presented and developed my idea from late 1965, left idle since, explaining why the current studies were going in the wrong direction and producing a ridiculously low thermonuclear efficiency. I proposed a scheme with two consecutive steps: a cold Li6D compression increasing the density, from the normal value of 0.8 g/cm3, by a factor of at least 20, followed by a sufficient temperature increase (the ignition). In this report, I also gave orders of magnitude of the energies involved in each step... [[ One can make the (flawed) analogy of Billaud to Ulam (multi-stage insight, but no mechanism for compression), and Carayol to Teller (proposed the right mechanism for compression, although in Teller's case he may have learned of it from von Neumann and Fuchs!!!). ]] 

In early April 1967, Carayol had the idea that the x-rays emitted from the fission explosion could transport the fission energy to the thermonuclear fuel chamber to induce the necessary compression. He published a brief paper wherein he presented, and justified mathematically, his architectural idea. This was the key to the solution for an efficient thermonuclear explosive device, consistent with the current data about U.S. hydrogen weapons. Carayol had rediscovered the radiative coupling concept first introduced by Americans Stanislaw Ulam and Edward Teller in January 1951.

Michel Carayol, the Genuine Father of the French H-Bomb

Michel Carayol was born in 1934 and died in 2003. His father was an industrialist and his mother a teacher. He entered Ecole Polytechnique in 1954, graduated in 1956, and joined the Armament. In 1962, he was part of the DEFA assigned to CEA-DAM at Limeil. In 1967, Carayol was part of the advanced studies branch.

... Soon after, in April 1967, Carayol wrote a brief report describing his proposal for a cylindrico-spherical case in dense metal, containing a fission device on one side and a thermonuclear sphere on the other. The report showed that the photons radiated by the primary *still very hot* in the X-ray frequency range, swept into the chamber rapidly enough to surround completely the thermonuclear sphere before the metal case would be vaporized. Carayol had discovered independently a scheme equivalent to the concept developed by Ulam and Teller in the 50s.

But Carayol's insight was ignored! It was British assistance that alerted project leadership to the value of Carayol's ideas. It is not enough for some isolated genius to make a breakthrough -- the people in charge have to understand its value.

... During the first months of 1967, Viard had told me, ‘‘A British physicist is showing some interest in what we do.’’ At several embassy parties, a first-rate British atomic scientist, Sir William Cook, former director during the 1950s of thermonuclear research at Aldermaston, the British center for atomic military applications, had approached the military attache´ at the French Embassy in London, Andre´ Thoulouze, an Air Force colonel, and had hinted to our nuclear research program. Thoulouze had previously been in charge of an air force base and knew Rene´ David, who would later work at the DAM. For this reason, instead of contacting the French main intelligence services, Thoulouze directly contacted our information bureau at CEA, the BRIS, where David was working at the time. In analyzing the fallout from the French tests, the Americans, the British, and the Soviets knew that we had not made any real progress on the thermonuclear path. In 1966 and 1967 we had tested some combination of fission with light elements. Cook told Thoulouze that we had to look for something simpler.

Two weeks after the Valduc seminar, on September 19, and while the work resulting from the Valduc decisions had not yet concretely gotten under way, Thoulouze came from London bearing information from this qualified source. Jacques Robert immediately convened a meeting, in the DAM’s headquarters in Paris, to debrief this information. Only three other people attended the meeting: Viard, Bonnet (DAM’s deputy), and Henri Coleau (head of the BRIS). The information, very brief and of a purely technical nature, did not consist of outlines or precise calculations. Nevertheless, it allowed Bonnet to declare immediately that the Carayol design, proposed unsuccessfully as early as April 1967, could be labeled as correct.23 Had this outline not already been in existence, we would have had a difficult time understanding the information and might have suspected an attempt to mislead us. In fact, this was a reciprocal validation: Carayol’s sketch authenticated the seriousness of the source, while the latter confirmed the value of Carayol’s ideas. Without realizing it, as very few were aware of Carayol’s discovery (and surely not Cook), he had given us a big tip and unexpected assistance, as this information also freed us from the ministerial harassment to which we had been constantly subjected. From that moment, things moved briskly.

Encyclopedia Britannica:

Physicist Michel Carayol laid out what would be the fundamental idea of radiation implosion in an April 1967 paper, but neither he nor his colleagues were immediately convinced that it was the solution, and the search continued.

In late September 1967, Carayol’s ideas were validated by an unlikely source, William Cook, who had overseen the British thermonuclear program in the mid-1950s. Cook, no doubt at his government’s behest, verbally passed on the crucial information to the French embassy’s military attaché in London. Presumably, the British provided this information for political reasons. British Prime Minister Harold Wilson was lobbying for the entry of the United Kingdom into the Common Market (European Economic Community), which was being blocked by de Gaulle.

Sakharov sketch:

Note Added: Perhaps someone can translate part of this paper, which gives some details about the Chinese thermonuclear step, credit to Yu Min. Did they invent a mechanism different from Ulam-Teller? I can't tell from this paper, but I suspect the initial Chinese design used U-T. There are claims that Yu Min later developed, in the pursuit of miniaturization and improved safety, a qualitatively different design.

Yu Min was a student of Peng Huanwu (also a key figure in the bomb effort), who was a student of Max Born. Yu Min only recently passed, in early 2019!

RadioLab on embryo selection in IVF

I'm in this RadioLab podcast covering genetic selection of embryos in IVF. Apologies to SSGAC, Robert Plomin, Ian Deary, James Lee, Tom Bouchard, and countless other dedicated scientists for the impression given that progress in genomics of cognitive ability is largely my work. See last paragraph below.

This is the email I sent to RadioLab this morning:

Hi Pat and Michelle,

Congratulations on a high quality podcast. I thought you were admirably fair and balanced. I also thought the production (esp. the music) was excellent.

My main comment is that the juxtaposition between my remarks and Benjamin's is misleading: when he says 60-40 or 55% chance of rank ordering properly, that is a very different question than identifying an outlier who is, say, in among the 1% highest risk. We are not trying to rank order embryos, but to warn against unusual risk of a medical condition.

To use the SAT analogy, given two kids with scores 1250 and 1200, only some of the time does the 1250 kid end up with a higher GPA. (You can't predict rank order very well.) But if the engineering dean admits an SAT 770 kid (i.e., a negative outlier compared to the average score of, say, 1300 among engineers) in his freshman class, he knows the likelihood is high that the kid will struggle. Benjamin is talking about the first scenario, and I am talking about the second.

Finally, I realize that to hook listeners you had to make me the focus of the episode. But I want to make clear that many scientists contribute to this work, which I feel will ultimately be beneficial to our species and civilization. I am just a small part of a worldwide research endeavor.

Best wishes,
Steve

For more on recent progress in genomic prediction, see The Diffusion of Knowledge.

Manifold #15: Daniel Max of The New Yorker on Prion diseases and literary non-fiction

Daniel Max, staff writer at The New Yorker and author of Every Love Story is A Ghost Story, a biography of David Foster Wallace, speaks with Corey and Steve about his first book, The Family that Couldn’t Sleep. The discussion covers the emerging genre of literary non-fiction, Daniel’s process of writing The Family that Couldn’t Sleep, and how he approached and gained the trust of the family at the heart of the story. Corey probes Daniel about how he handled the complex scientific characters, Carl Gajdusek and Stanley Prusiner, who led research into prion disease for 40 years. Daniel recounts how Shirley Glasse (now Lindenbaum) discovered how prions were transmitted through ritual cannibalism in Papua New, a critical step in solving the mystery of what causes of the disease, but how credit was given to Gajdusek. The three discuss the painfully slow pace of research and the inspiring story of a young couple, Eric Minikel and Sonia Vallabh, who have changed careers to dedicate their lives to finding a cure.

Max’s New Yorker Page

Max’s initial 2001 article for the New York Times Magazine on the Italian Family with FFI

Max’s 2013 New Yorker story on Minikel and Vallabh

Transcript


man·i·fold /ˈmanəˌfōld/ many and various.

In mathematics, a manifold is a topological space that locally resembles Euclidean space near each point.

Steve Hsu and Corey Washington have been friends for almost 30 years, and between them hold PhDs in Neuroscience, Philosophy, and Theoretical Physics. Join them for wide ranging and unfiltered conversations with leading writers, scientists, technologists, academics, entrepreneurs, investors, and more.

Steve Hsu is VP for Research and Professor of Theoretical Physics at Michigan State University. He is also a researcher in computational genomics and founder of several Silicon Valley startups, ranging from information security to biotech. Educated at Caltech and Berkeley, he was a Harvard Junior Fellow and held faculty positions at Yale and the University of Oregon before joining MSU.

Corey Washington is Director of Analytics in the Office of Research and Innovation at Michigan State University. He was educated at Amherst College and MIT before receiving a PhD in Philosophy from Stanford and a PhD in a Neuroscience from Columbia. He held faculty positions at the University Washington and the University of Maryland. Prior to MSU, Corey worked as a biotech consultant and is founder of a medical diagnostics startup.

Dominic Cummings "de facto chief executive" for UK Prime Minister Boris Johnson

Dominic Cummings sporting an OpenAI shirt. Great messaging! Go Dom :-)

Why Dominic Cummings is Johnson’s most important appointment (Spectator)

The closest analogy to the government Boris Johnson is forming is Blair’s and Brown’s New Labour government of 1997, when they appointed super powerful political advisers – Campbell, Powell, Balls, Whelan – to boss conservative Whitehall.

That is what Johnson is doing – in spades – by making former Vote Leave campaign chief Dominic Cummings his de facto chief executive as senior advisor, because Cummings is NEVER a passive adviser. Cummings has an extraordinary sense of purpose and objectives – and pity those who get in his path.

Cummings’s mandate is to deliver Brexit in 99 days, and in his spare time he’ll endeavour to reform Whitehall, since one of his obsessions is that the civil service is unfit for modern government. Sir Humphrey will be anxious, but so too will ministers and many Tory MPs, including Brexiters, who still nurse bruises from their encounters with him when he ran Vote Leave and earlier when he was an adviser to Michael Gove.

As proof that Johnson is placing serious trust in Cummings is that so many of Cummings’s Vote Leave team are moving in to Downing Street: Lee Cain as director of communications, Rob Oxley as press secretary and Oliver Lewis as a Brexit policy adviser.

The diffusion of knowledge

Szilard and Wigner told Einstein about their recent calculations... how the fission process might create chain reactions and nuclear bombs. "Daran habe ich gar nicht gedacht," said Einstein -- I did not think about that at all!

In the past two weeks I gave talks at ISIR2019 (Minneapolis), the Institute of Biomedical Sciences (Academia Sinica, Taipei -- home of the Taiwan biobank), Innovative Genomics Institute (IGI = CRISPR central, UC Berkeley and UCSF) and at OpenAI (AGI in San Francisco).

Title: Genomic Prediction of Complex Traits and Disease Risks via AI/ML and Large Genomic Datasets

Abstract: The talk is divided into two parts. The first gives an overview of the rapidly advancing area of genomic prediction of disease risks using polygenic scores. We can now identify risk outliers (e.g., with 5 or 10 times normal risk) for about 20 common disease conditions, ranging from diabetes to heart diseases to breast cancer, using inexpensive SNP genotypes (i.e., as offered by 23andMe). We can also predict some complex quantitative traits (e.g., adult height with accuracy of few cm, using ~20k SNPs). I discuss application of these results in precision medicine as well as embryo selection in IVF, and give some details about genetic architectures. The second part covers the AI/ML used to build these predictors, with an emphasis on "sparse learning" and phase transitions in high dimensional statistics.

Slides for the first part of the talk.

I also appeared on Dilbert creator Scott Adams' show.

Beijing 2019 Notes -- addendum

I just came across this beautiful video with 4k drone footage of Guangzhou, part of the Guangdong-Hong Kong-Macau Greater Bay Area in the Pearl River delta region.

In my earlier post on Beijing I emphasized the issue of scale in China -- massive scale that is evident in the video above.

I traveled in SE Asia before the 1997 currency / economic crisis. At that time there was plenty of evidence of a bubble in those countries -- unused infrastructure and real estate built on spec, few signs of real technological or productive capability, etc. China had aspects of that 10 years ago, but now it's apparent that earlier infrastructure investment is being put to good use.

As I walked around Beijing I strained to find things around me -- buildings, solar panels, batteries, cars, high speed trains, electronics, software infrastructure, even airplanes -- that couldn't be sourced in China. Other than a few specific tech stacks that will get serious attention in coming years (e.g., CPUs) I was not able to think of many areas in which China has not caught up technologically. See Can the US derail China 2025?

PS I'm back in the US now. Will be giving a talk today at IGI in Berkeley and at OpenAI on Thursday.

Manifold Episode #14: Stuart Firestein on Why Ignorance and Failure Lead to Scientific Progress

Steve and Corey speak with Stuart Firestein (Professor of Neuroscience at Columbia University, specializing in the olfactory system) about his two books Ignorance: How It Drives Science, and Failure: Why Science Is So Successful. Stuart explains why he thinks that it is a mistake to believe that scientists make discoveries by following the “scientific method” and what he sees as the real relationship between science and art. We discuss Stuart’s recent research showing that current models of olfactory processing are wrong, while Steve delves into the puzzling infinities in calculations that led to the development of quantum electrodynamics. Stuart also makes the case that the theory of intelligent design is more intelligent than most scientists give it credit for and that it would be wise to teach it in science classes.

Stuart Firestein

Failure: Why Science Is so Successful

Ignorance: How it drives science

Transcript


man·i·fold /ˈmanəˌfōld/ many and various.

In mathematics, a manifold is a topological space that locally resembles Euclidean space near each point.

Steve Hsu and Corey Washington have been friends for almost 30 years, and between them hold PhDs in Neuroscience, Philosophy, and Theoretical Physics. Join them for wide ranging and unfiltered conversations with leading writers, scientists, technologists, academics, entrepreneurs, investors, and more.

Steve Hsu is VP for Research and Professor of Theoretical Physics at Michigan State University. He is also a researcher in computational genomics and founder of several Silicon Valley startups, ranging from information security to biotech. Educated at Caltech and Berkeley, he was a Harvard Junior Fellow and held faculty positions at Yale and the University of Oregon before joining MSU.

Corey Washington is Director of Analytics in the Office of Research and Innovation at Michigan State University. He was educated at Amherst College and MIT before receiving a PhD in Philosophy from Stanford and a PhD in a Neuroscience from Columbia. He held faculty positions at the University Washington and the University of Maryland. Prior to MSU, Corey worked as a biotech consultant and is founder of a medical diagnostics startup.

Beijing 2019 Notes

I'm at Beijing University in Zhongguancun. Some brief notes and photos below.

I had meetings with Beida professors, prominent tech entrepreneurs and VCs, policy analysts, IVF doctors and genetic scientists. I also had conversations with ordinary people -- drivers, maids, hotel and service staff.

I've been traveling to Beijing for about 15 years now and have observed significant improvements in infrastructure, general economic level, civil society, general behavior. This would of course be obvious to people living in China, which presumably explains the confidence people here have in their government and in continued advances in development. The hypothesis that this society is "brittle" or vulnerable to shocks seems unsupported.

The main thing to comprehend about China is scale. There are easily ~350M (i.e., population of US) people here living roughly first world lives: with access to education, good jobs, climate controlled apartment in major city, good public transportation, fast internet access, etc. Probably the number is twice as large depending on how one defines the category. For one thing, this means that the supply of engineers, technologists, lab scientists, project managers, entrepreneurs, etc. is very large. There are certainly poor people who lack opportunity, but the size of the population for which the education and economic system are working reasonably well is very large. Possibly a billion people out of ~1.4B.

Beijing is a microcosm of this phenomenon of scale. It's a huge city (over 20M people) with the kind of modern metro system only to be found in places like Tokyo or perhaps Seoul or Paris or London. One can ride the longer lines for 90 minutes without exiting, covering the entire extent of the city from one side to the other. Despite the public transport system, the roads are clogged with recent model cars, producing traffic conditions reminiscent of Los Angeles. I don't find the city as a whole all that livable -- it's too enormous for me -- but locals know all the many charming locations (see photos below). Beijing is reaching a level of development that reminds me of Tokyo.

Trump, the trade war, and US-China relations came up frequently in discussion. Chinese opinion tends to focus on the long term. Our driver for a day trip to the Great Wall was an older man from the countryside, who has lived only 3 years in Beijing. I was surprised to hear him expressing a very balanced opinion about the situation. He understood Trump's position remarkably well -- China has done very well trading with the US, and owes much of its technological and scientific development to the West. A recalibration is in order, and it is natural for Trump to negotiate in the interest of US workers.

China's economy is less and less export-dependent, and domestic drivers of growth seem easy to identify. For example, there is still a lot of low-hanging fruit in the form of "catch up growth" -- but now this means not just catching up with the outside developed world, but Tier 2 and Tier 3 cities catching up with Tier 1 cities like Beijing, Shanghai, Shenzhen, etc.

China watchers have noted the rapidly increasing government and private sector debt necessary to drive growth here. Perhaps this portends a future crisis. However, I didn't get any sense of impending doom for the Chinese economy. To be fair there was very little inkling of what would happen to the US economy in 2007-8.  Some of the people I met with are highly placed with special knowledge -- they are among the most likely to be aware of problems. Overall I had the impression of normalcy and quiet confidence, but perhaps this would have been different in an export/manufacturing hub like Shenzhen. [ Update: Today after posting this I did hear something about economic concerns... So situation is unclear. ]

Innovation is everywhere here. Perhaps the most obvious is the high level of convenience from the use of e-payment and delivery services. You can pay for everything using your mobile (increasingly, using just your face!), and you can have food and other items (think Amazon on steroids) delivered quickly to your apartment. Even museum admissions can be handled via QR code.

A highly placed technologist told me that in fields like AI or computer science, Chinese researchers and engineers have access to in-depth local discussions of important arXiv papers -- think StackOverflow in Mandarin. Since most researchers here can read English, they have access both to Western advances, and a Chinese language reservoir of knowledge and analysis. He anticipates that eventually the pace and depth of engineering implementation here will be unequaled.

IVF and genetic testing are huge businesses in China. Perhaps I'll comment more on this in the future. New technologies, in genomics as in other areas, tend to be received more positively here than in the US and Europe.


National Museum

Bookstore and Cafe on the grounds of the National Art Museum.

Tiananmen Square (see below for historical note)

An email sent to Julian Assange's attorney, whom I met at CogX in London:

Hi Jen,

I really enjoyed your Q&A today. Keep fighting the good fight.

Wikileaks diplomatic cables reveal no mass shootings in Tiananmen Square:

https://wikileaks.org/plusd/cables/89BEIJING18828_a.html

https://www.telegraph.co.uk/news/worldnews/wikileaks/8555142/Wikileaks-no-bloodshed-inside-Tiananmen-Square-cables-claim.html

Our media has been misrepresenting this historical event for 30 years
now. There was certainly violence, but not in the square itself.

Best wishes,
Steve

Columbia Journalism Review (1998): The Myth of Tiananmen. See comments for further discussion...

Note Added: In the comments AG points to a Quora post by a user called Janus Dongye Qimeng, an AI researcher in Cambridge UK, who seems to be a real China expert. I found these posts to be very interesting.

Infrastructure development in poor regions of China

Size of Chinese internet social network platforms

Can the US derail China 2025? (Core technology stacks in and outside China)

Huawei smartphone technology stack and impact of US entity list interdiction (software and hardware!)

Agriculture at Massive Scale

US-China AI competition


More recommenations: Bruno Maçães is one of my favorite modern geopolitical thinkers. A Straussian of sorts (PhD under Harvey Mansfield at Harvard), he was Secretary of State for European Affairs in Portugal, and has thought deeply about the future of Eurasia and of US-China relations. He spent the last year in Beijing and I was eager to meet with him while here. His recent essay Equilibrium Americanum appeared in the Berlin Policy Journal. Podcast interview -- we hope to have him on Manifold soon :-)

Manifold Podcast #13: Joe Cesario on Political Bias and Problematic Research Methods in Social Psychology

Corey and Steve continue their discussion with Joe Cesario and examine methodological biases in the design and conduct of experiments in social psychology and ideological bias in the interpretation of the findings. Joe argues that experiments in his field are designed to be simple, but that in making experimental set ups simple researchers remove critical factors that actually matter for a police officer making a decision in the real world. In consequence, he argues that the results cannot be taken to show anything about actual police behavior. Joe maintains that social psychology as a whole is biased toward the left politically and that this affects how courses are taught and research conducted. Steve points out the university faculty on the whole tend to be shifted left relative to the general population. Joe, Corey, and Steve discuss the current ideological situation on campus and how it can be alienating for students from conservative backgrounds.

Joseph Cesario's Lab
https://www.cesariolab.com/

Transcript
https://manifoldlearning.com/2019/06/27/episode-013-transcript/


man·i·fold /ˈmanəˌfōld/ many and various.

In mathematics, a manifold is a topological space that locally resembles Euclidean space near each point.

Steve Hsu and Corey Washington have been friends for almost 30 years, and between them hold PhDs in Neuroscience, Philosophy, and Theoretical Physics. Join them for wide ranging and unfiltered conversations with leading writers, scientists, technologists, academics, entrepreneurs, investors, and more.

Steve Hsu is VP for Research and Professor of Theoretical Physics at Michigan State University. He is also a researcher in computational genomics and founder of several Silicon Valley startups, ranging from information security to biotech. Educated at Caltech and Berkeley, he was a Harvard Junior Fellow and held faculty positions at Yale and the University of Oregon before joining MSU.

Corey Washington is Director of Analytics in the Office of Research and Innovation at Michigan State University. He was educated at Amherst College and MIT before receiving a PhD in Philosophy from Stanford and a PhD in a Neuroscience from Columbia. He held faculty positions at the University Washington and the University of Maryland. Prior to MSU, Corey worked as a biotech consultant and is founder of a medical diagnostics startup.