Information Processing

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.

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Our plan is to record a new one every 1-2 weeks. We're in the process of scheduling now, so if you have contacted me to be on the show, or have suggested a guest, please bear with us as we get going.

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

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

Steve and Corey 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.

I feel terrible about this news. I had no idea Dave Jackson was living only a few miles away from me the past few years.

... J.D. Jackson, particle physicist and author of the graduate text Classical Electrodynamics, passed away on May 20, 2016 at the Burcham Hills retirement home in East Lansing. He had resided there for the last several years. His memorial service will be held in Berkeley, CA later this summer, ...

The picture below (taken by Josh Burton in 2013) shows three former Berkeley professors: J.D. Jackson, Geoff Chew, and Steven Weinberg.


When I entered graduate school at Berkeley I asked to place out of the required course in advanced electrodynamics, which was taught by Jackson using his famous book. I had lecture notes from the course I had taken at Caltech from Mark Wise, which also used the book. Jackson borrowed the notes for a few days, looked through them carefully, and returned to me a short list detailing topics in which my education had been deficient. I was to study those topics, but was excused from the course.

Although I never had Jackson as a teacher, one of the great experiences of graduate school was attending regular theory seminars and hearing the ideas and incisive commentary of brilliant professors like him.

See also Where men are men, and giants walk the earth.

This Quartz article describes Jonathan Wai's research on the rate at which different universities produce alumni who make great contributions to science, technology, medicine, and mathematics. I think the most striking result is the range of outcomes: the top school outperforms good state flagships (R1 universities) by as much as a thousand times. In my opinion the main causative factor is simply filtering by cognitive ability and other personality traits like drive. Psychometrics works!

Quartz: Few individuals will be remembered in history for discovering a new law of nature, revolutionizing a new technology or captivating the world with their ideas. But perhaps these contributions say more about the impact of a university or college than test scores and future earnings. Which universities are most likely to produce individuals with lasting effect on our world?

The US News college rankings emphasize subjective reputation, student retention, selectivity, graduation rate, faculty and financial resources and alumni giving. Recently, other rankings have proliferated, including some based on objective long-term metrics such as individual earning potential. Yet, we know of no evaluations of colleges based on lasting contributions to society. Of course, such contributions are difficult to judge. In the analysis below, we focus primarily on STEM (science, technology, engineering and medicine/mathematics) contributions, which are arguably the least subjective to evaluate, and increasingly more valued in today’s workforce.

We examined six groups of exceptional achievers divided into two tiers, looking only at winners who attended college in the US. Our goal is to create a ranking among US colleges, but of course one could broaden the analysis if desired. The first level included all winners of the Nobel Prize (physics, chemistry, medicine, economics, literature, and peace), Fields Medal (mathematics) and the Turing Award (computer science). The second level included individuals elected to the National Academy of Sciences (NAS), National Academy of Engineering (NAE) or Institute of Medicine (IOM). The National Academies are representative of the top few thousand individuals in all of STEM.

We then traced each of these individuals back to their undergraduate days, creating two lists to examine whether the same or different schools rose to the top. We wanted to compare results across these two lists to see if findings in the first tier of achievement replicated in the second tier of achievement and to increase sample size to avoid the problem of statistical flukes.

Simply counting up the number of awards likely favors larger schools and alumni populations. We corrected for this by computing a per capita rate of production, dividing the number of winners from a given university by an estimate of the relative size of the alumni population. Specifically, we used the total number of graduates over the period 1966-2013 (an alternative method of estimating base population over 100 to 150 years led to very similar lists). This allowed us to objectively compare newer and smaller schools with older and larger schools.

In order to reduce statistical noise, we eliminated schools with only one or two winners of the Nobel, Fields or Turing prize. This resulted in only 25 schools remaining, which are shown below ...

The vast majority of schools have never produced a winner. #114 Ohio State and #115 Penn State, which have highly ranked research programs in many disciplines, have each produced one winner. Despite being top tier research universities, their per capita rate of production is over 400 times lower than that of the highest ranked school, Caltech. Of course, our ranking doesn’t capture all the ways individuals can impact the world. However, achievements in the Nobel categories, plus math and computer science, are of great importance and have helped shaped the modern world.

As a replication check with a larger sample, we move to the second category of achievement: National Academy of Science, Engineering, or Medicine membership. The National Academies originated in an Act of Congress, signed by President Abraham Lincoln in 1863. Lifetime membership is conferred through a rigorous election process and is considered one of the highest honors a researcher can receive.

The results are strikingly similar across the two lists. If we had included schools with two winners in the Nobel/Fields/Turing list, Haverford, Oberlin, Rice, and Johns Hopkins would have been in the top 25 on both. For comparison, very good research universities such as #394 Arizona State, #396 Florida State and #411 University of Georgia are outperformed by the top school (Caltech) by 600 to 900 times. To give a sense of the full range: the per capita rate of production of top school to bottom school was about 449 to one for the Nobel/Fields/Turing list and 1788 to one for the National Academies list. These lists include only schools that produced at least one winner—the majority of colleges have produced zero.

What causes these drastically different odds ratios across a wide variety of leading schools? The top schools on our lists tend to be private, with significant financial resources. However, the top public university, UC Berkeley, is ranked highly on both lists: #13 on the Nobel/Fields/Turing and #31 on the National Academies. Perhaps surprisingly, many elite liberal arts colleges, even those not focused on STEM education, such as Swarthmore and Amherst, rose to the top. One could argue that the playing field here is fairly even: accomplished students at Ohio State, Penn State, Arizona State, Florida State and University of Georgia, which lag the leaders by factors of hundreds or almost a thousand, are likely to end up at the same highly ranked graduate programs as individuals who attended top schools on our list. It seems reasonable to conclude that large differences in concentration or density of highly able students are at least partly responsible for these differences in outcome.

Sports fans are unlikely to be surprised by our results. Among all college athletes only a few will win professional or world championships. Some collegiate programs undoubtedly produce champions at a rate far in excess of others. It would be uncontroversial to attribute this differential rate of production both to differences in ability of recruited athletes as well as the impact of coaching and preparation during college. Just as Harvard has a far higher percentage of students scoring 1600 on the SAT than most schools and provides advanced courses suited to those individuals, Alabama may have more freshman defensive ends who can run the forty yard dash in under 4.6 seconds, and the coaches who can prepare them for the NFL.

One intriguing result is the strong correlation (r ~ 0.5) between our ranking (over all universities) and the average SAT score of each student population, which suggests that cognitive ability, as measured by standardized tests, likely has something to do with great contributions later in life. By selecting heavily on measurable characteristics such as cognitive ability, an institution obtains a student body with a much higher likelihood of achievement. The identification of ability here is probably not primarily due to “holistic review” by admissions committees: Caltech is famously numbers-driven in its selection (it has the highest SAT/ACT scores), and outperforms the other top schools by a sizeable margin. While admission to one of the colleges on the lists above is no guarantee of important achievements later in life, the probability is much higher for these select matriculants.

We cannot say whether outstanding achievement should be attributed to the personal traits of the individual which unlocked the door to admission, the education and experiences obtained at the school, or benefits from alumni networks and reputation. These are questions worthy of continued investigation. Our findings identify schools that excel at producing impact, and our method introduces a new way of thinking about and evaluating what makes a college or university great. Perhaps college rankings should be less subjective and more focused on objective real world achievements of graduates.

For analogous results in college football, see here, here and here. Four and Five star recruits almost always end up at the powerhouse programs, and they are 100x to 1000x more likely to make it as pros than lightly recruited athletes who are nevertheless offered college scholarships.

[ See updated version. ]

A few years ago I posted a list of number of Nobel prizes aggregated by undergraduate institution of the winner. A social science researcher who reads this blog got interested in the topic and has compiled much more complete information, which he is preparing to publish.

He reports that the school with the most Nobel + Fields + Turing prizes, normalized to size of (undergraduate) alumni population, is Caltech, which leads both Harvard and MIT (the next highest ranked schools) by a factor of 3 or 4. Caltech beats Michigan by a factor of ~50, and Ohio State (typical of good public flagships) by a factor of ~500!

To obtain a higher statistics measurement of exceptional achievement, he aggregated living members of the National Academy of Science, National Academy of Engineering, and Institute of Medicine, and normalized to size of alumni population over the last 100 years or so. Caltech again comes out first, beating both Harvard and MIT by a factor of about 1.5. Caltech beats Yale and Princeton by a factor of ~4, and Stanford by a factor of ~5. Swarthmore and Amherst are the leading liberal arts colleges. (See list below.) Caltech beats very good public universities by factors ~100 and more typical public universities by factors ~1000.

Berkeley is the best public university in both the Nobel+ and National Academies rankings. Berkeley is roughly tied with Stanford in Nobels+ per alum, but behind in academicians per capita.

As you might expect, correlation of rank order in these lists with average SAT score is pretty high. Likelihood ratios of ~500 or 1000 for high end achievement suggest that 1. psychometric scores used in college admissions have significant validity and 2. high end achievement is correlated to unusually high ability: two schools with very different mean SAT have very different population fractions above some threshold, such as +3 SD. For example at Caltech perhaps half the students are above +3 SD in ability, whereas at an average university only 1 in ~500 are at that level, leading to ratios as large as 100 or 1000!

Colleges ranked by per capita production of National Academy (Science, Engineering, Medicine) members:

California Institute of Technology
Massachusetts Institute of Technology
Harvard University
Swarthmore College
Yale University
Princeton University
Amherst College
Stanford University
Oberlin College
Columbia University
Haverford College
Cooper Union
Dartmouth College

See also Annals of Psychometry: IQs of eminent scientists, and Vernon Smith at Caltech.


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Correction! The original post quoted results using an estimate of alumni population derived from recent US News data. However, some schools have changed over time in enrollment, so more precise estimates are required. The lists below use graduation numbers reported to IPEDS from 1966-2013 and probably yield more accurate rankings than what was reported above. The main difference on the Nobel+ list is that the University of Chicago jumps to #3 and MIT falls several notches. On the NAS/NAE/IOM list MIT is #2 and Harvard #3.


Undergraduate Institution | Nobel+ | Bachelor's degrees awarded (1966-2013) | Prize per capita ratio

California Institute of Technology 11 9348 0.001176722

Harvard University 34 81553 0.000416907

University of Chicago 15 37171 0.000403540

Swarthmore College 5 15825 0.000315956

Columbia University 20 68982 0.000289931

Massachusetts Institute of Technology 14 52891 0.000264695

Yale University 13 60107 0.000216281

Amherst College 4 18716 0.000213721

[ For comparison: Penn State and Ohio State ~ 0.0000028 and 0.0000026 ; many schools have zero Nobel+ winners. ]



Undergraduate Institution | NAS+NAE+IOM | Bachelor's degrees awarded (1966-2013) | ratio

California Institute of Technology 78 9348 0.0083440308

Massachusetts Institute of Technology 255 52891 0.0048212361

Harvard University 326 81553 0.0039974005

Swarthmore College 49 15825 0.0030963665

Princeton University 109 50633 0.0021527462

Amherst College 35 18716 0.0018700577

Yale University 112 60107 0.0018633437

University of Chicago 56 37171 0.0015065508

Stanford University 117 79683 0.0014683182

[ For comparison, Arizona State and Florida State  ~ 0.000013 ; University of Georgia ~ 0.000008 ]

For more on Frederick Wiseman's new 4 hour documentary see here , here , here.

NYTimes: ... Mr. Wiseman has made his share of grim documentaries in which people are processed and oppressed by bureaucracy. “At Berkeley” is not one. Its cautiously upbeat attitude is expressed in a director’s note: “I think it is just as important for a filmmaker to show people of intelligence, character, tolerance and good will, hard at work, as it is to make movies about the failures, insensitivities and cruelties of others.” Amen.

For historical comparison, see below.

Trivia question: What do Chancellor Birgeneau (the leader of UC Berkeley in Wiseman's film) and Mario Savio, the leader of the Free Speech Movement, have in common?

Biotechnology meeting with Malaysian Prime Minister.



New Mission Bay campus of UCSF.






Espresso in Berkeley.





View from Treasure Island.

Holistic evaluation of applicants = noise? (Or worse?)

Why no evidence-based admissions?

Is there any serious study of whether subjective criteria used to judge applicants actually predict success? In psychometrics this is referred to as test validity. In the article below, it is not even clear that the evaluation method satisfies the weaker criteria of consistency or stability: applicants passed through the system another time might generate significantly different scores. "Expert" evaluation often reduces the power of prediction relative to simple algorithms.

See Data mining the university and Nonlinear psychometric thresholds for physics and mathematics for plenty of evidence of validity, consistency and stability of traditional measures of intellectual ability.

NYTimes: A highly qualified student, with a 3.95 unweighted grade point average and 2300 on the SAT, was not among the top-ranked engineering applicants to the University of California, Berkeley. He had perfect 800s on his subject tests in math and chemistry, a score of 5 on five Advanced Placement exams, musical talent and, in one of two personal statements, had written a loving tribute to his parents, who had emigrated from India.

Why was he not top-ranked by the “world’s premier public university,” as Berkeley calls itself? Perhaps others had perfect grades and scores? They did indeed. Were they ranked higher? Not necessarily. What kind of student was ranked higher? Every case is different.

The reason our budding engineer was a 2 on a 1-to-5 scale (1 being highest) has to do with Berkeley’s holistic, or comprehensive, review, an admissions policy adopted by most selective colleges and universities. In holistic review, institutions look beyond grades and scores to determine academic potential, drive and leadership abilities. Apparently, our Indian-American student needed more extracurricular activities and engineering awards to be ranked a 1.

Now consider a second engineering applicant, a Mexican-American student with a moving, well-written essay but a 3.4 G.P.A. and SATs below 1800. His school offered no A.P. He competed in track when not at his after-school job, working the fields with his parents. His score? 2.5.

Both students were among “typical” applicants used as norms to train application readers like myself. And their different credentials yet remarkably close rankings illustrate the challenges, the ambiguities and the agenda of admissions at a major public research university in a post-affirmative-action world.

[ Despite Prop. 209, the nearly equal scores of these "typical" training cases suggests outcomes very similar to those produced by explicit affirmative action. ]

... I could see the fundamental unevenness in this process both in the norming Webinars and when alone in a dark room at home with my Berkeley-issued netbook, reading assigned applications away from enormously curious family members. First and foremost, the process is confusingly subjective, despite all the objective criteria I was trained to examine.

In norming sessions, I remember how lead readers would raise a candidate’s ranking because he or she “helped build the class.”

... After the next training session, when I asked about an Asian student who I thought was a 2 but had only received a 3, the officer noted: “Oh, you’ll get a lot of them.” She said the same when I asked why a low-income student with top grades and scores, and who had served in the Israeli army, was a 3. ...

Unfortunately I had to miss this event, but one of our cohort of Berkeley students (Josh Burton) was able to attend. The photos below were taken by Josh. Had LHC discovered superpartners, Bruno Zumino and Julius Wess would have had a decent claim to a Nobel prize for their early work on supersymmetry.

It is strange to see my teachers grow old; to find myself older than some of the younger ones were when I was a student.

I remember Bruno as a consummate gentleman. He was kind to students and an excellent lecturer. The main idiosyncrasy was a small metal chalk holder that kept his hands clean but made the chalk squeak sharply as Bruno wrote his beautiful long equations on the board. In one of his special topics courses I turned in a term paper on string compactification (the Hosotani mechanism) which was returned with some nice comments and an A+. I think he hadn't been familiar with some of the results and attributed their cleverness incorrectly to me. Despite learning differential forms from both Kip Thorne and Bruno I've never used them much and continue to rely on explicit indices ;-)


Signing the guest book for all of us.


Ed Witten with Stanley Mandelstam.


J.D. Jackson, Geoff Chew and Steven Weinberg.

Another historical letter sent by a reader. My understanding is that Feynman was not appointed at Berkeley because of Birge's anti-semitism: "One Jew (Oppenheimer) is enough," he is reported to have said.

CONFIDENTIAL

November 4, 1943

Professor R. T. Birge
Chairman, Department of Physics
University of California
Berkeley, California

Dear Professor Birge:

In these war times it is not always easy to think constructively about the peace that is to follow, even in such relatively small things as the welfare of our department. I would like to make one suggestion to you which concerns that, and about which I have myself a very sure and strong conviction.

As you know, we have quite a number of physicists here, and I have run into a few who are young and whose qualities I had not known before. Of these there is one who is in every way so outstanding and so clearly recognized as such, that I think it appropriate to call his name to your attention, with the urgent request that you consider him for a position in the department at the earliest time that that is possible. You may remember the name because he once applied for a fellowship in Berkeley: it is Richard Feynman. He is by all odds the most brilliant young physicist here, and everyone knows this. He is a man of thoroughly engaging character and personality, extremely clear, extremely normal in all respects, and an excellent teacher with a warm feeling for physics in all its aspects. He has the best possible relations both with the theoretical people of whom he is one, and with the experimental people with whom he works in very close harmony.

The reason for telling you about him now is that his excellence is so well known, both at Princeton where he worked before he came here, and to a not inconsiderable number of "big shots" on this project, that he has already been offered a position for the post war period, and will most certainly be offered others. I feel that he would be a great strength for our department, tending to tie together its teaching, its research and its experimental and theoretical aspects. I may give you two quotations from men with whom he has worked. Bethe has said that he would rather lose any two other men than Feyman from this present job, and Wigner said, "He is a second Dirac, only this time human."

Of course, there are several people here whose recommendation you might want; in the first instance Professors Brode and McMillan. I hope you will not mind my calling this matter to your attention, but I feel that if we can follow the suggestion I have made, all of us will be very happy and proud about it in the future. I cannot too strongly emphasize Feynman's remarkable personal qualities which have been generally recognized by officers, scientists and laity in this community.

With every good wish,

Robert Oppenheimer

From the autobiography Alvarez: Adventures of a Physicist. See also Alvarez quotes, and related posts.

Chapter 4: I learned about the discovery of nuclear fission in the Berkeley campus barbershop one morning in late January 1939, while my hair was being cut. Buried on an inside page of the Chronicle was a story from Washington reporting Bohr's announcement that German chemists had split the uranium atom by bombarding it with neutrons. I stopped the barber in mid-snip and ran all the way to the Rad Lab to spread the word. The first person I saw was my graduate student Phil Abelson. I knew the news would shock him. "I have something terribly important to tell you," I said. "I think you should lie down on the table." Phil sensed my seriousness and complied. I told him what I had read. He was stunned; he realized immediately, as I had before, that he was within days of making the same discovery himself. 

... I tracked down Oppenheimer working with his entourage in his bullpen in LeConte Hall. He instantly pronounced the reaction impossible and proceeded to prove mathematically to everyone in the room that someone must have made a mistake. The next day Ken Green and I demonstrated the reaction. I invited Robert over to see [it] ... In less than 15 minutes he not only agreed that the reaction was authentic but also speculated that in the process extra neutrons would boil off that could be used to split more uranium atoms and thereby generate power or make bombs. It was amazing to see how rapidly his mind worked, and he came to the right conclusions. His response demonstrated the scientific ethic at its best. When we proved that his previous position was untenable, he accepted the evidence with good grace, and without looking back he immediately turned to examining where the new knowledge might lead.

This short passage illustrates many aspects of science: the role of luck, the convergence of different avenues of investigation, the overconfidence of theorists and the supremacy of experiments in discerning reality, the startling reach of a powerful mind.

I was a bit busy last week, with a visitor, posting a paper, etc. so I didn't get to comment on the Nobel prizes.

The dark energy prize is richly deserved (see slides from a colloquium on dark energy I've given a few times; includes above figure). These guys have discovered where most of the energy in the universe is, and may have determined the ultimate fate of the universe on cosmological scales. I note Saul Perlmutter was awarded 1/2 the prize and the other two guys each received 1/4. This may seem like petty credit splitting, but in this case it is appropriate as Perlmutter's group at LBNL have been working on supernova astronomy for a long time trying to get it to work. (Since when I was a grad student!) Perlmutter attributes the original idea to Luis Alvarez, perhaps the greatest experimentalist of the 20th century.

In finding that the universe is on a path to runaway expansion, you had to find type Ia supernovae, which can act as distance markers. How did you get involved with supernova searching?

I was at the University of California at Berkeley for graduate school. One of the heroes here at Berkeley is Luis Alvarez. The tradition that he started is looking for interesting science no matter where it is and then finding tools to do those things. For example, he invented one of the first steady cams.

One of his protégés was my professor, Richard Muller. There was a project to do a superautomated supernova search that Luis Alvarez had suggested to Rich. They had just done one of the first adaptive-optics experiments.

...

To what do you most attribute your scientific success?

I think the biggest thing is, first of all, being willing to learn things, being willing to pick up a new area, but also just being able to work with other people. Most of these jobs are too big for any one person. You end up trying to find a team of people who are as excited as you are and want to push the technique forward. I'm always struck by the fact that the image of the scientist is as a lone person wearing a lab jacket in the lab by themselves for hours, whereas my sense is that maybe the single most important thing for a scientist, aside from being able to think of good questions, is figuring out good people to work with and enjoying the process of inventing ideas together with other people.

You can add one more Nobel prize to the Berkeley lab collection:




I don't have too much to say about the quasicrystal prize, except that there are several curious aspects (this is mostly second hand stuff I picked up from colleagues): 1. the chemists gave a prize for a physics discovery, and seem to have botched the job: 2. they left out the theorist who was instrumental in convincing people that Shechtman's result was for real (Steinhardt had worked out the theory of quasicrystals out already, and even coined the name!) and 3. Shechtman's group at NIST (where he made the discovery) didn't believe the result and his boss kicked him out!

I'm back in Berkeley again after my visit to Caltech. Later this week I'll return to my sabbatical in Taiwan.

As I mentioned in this earlier post, I've lately been working on the unconventional idea that the theta parameter in QED might be directly measurable (specifically, in experiments involving superpositions of photonic states; slides). If I'm correct, there is an additional fundamental parameter of the standard model, and of QED, that has yet to be measured. On this trip I've discussed this idea with theorists at Oregon, Berkeley and Caltech, and also with experimentalists in quantum optics at Oregon, Stanford and Caltech.

During my week at Caltech I sought out my former professors Mark Wise (McCone Professor of Theoretical Physics), John Preskill (Feynman Professor of Theoretical Physics) and David Politzer (Tolman Professor of Theoretical Physics) to get their feedback on the idea. Mark and John both arrived on campus in 1983, my freshman year. They and David were the bright young professors on the fourth floor of Lauritsen, successors to the giants, Feynman and Gell-Mann. As you might expect, it's psychologically quite difficult to be the advocate of an idea that goes against conventional wisdom. An iconoclastic "maverick spirit" is probably as necessary for innovation as is raw intelligence. I was counting on their brainpower to help me find the problems with my work -- what is opaque to me might be obvious to them :-)

It's entirely possible that I'll discover, after many months of effort, that the work is incorrect. Dave Politzer told me, either this idea will be seen in retrospect to be obvious, and people will wonder why they didn't have the imagination to think of it, or there's something wrong that will be revealed under further examination. I guess time will tell.


Action photo: theoretician at work in a Berkeley cafe.



Another beautiful sunset.

Tomorrow I'm headed down to Caltech. Here are a few more Berkeley photos.

An LBNL building I particularly like. The big glass wall has a great view of the Bay.




This is the hottest restaurant in Berkeley (NYTimes review: "Gather has the feel of a Michael Pollan book come to life"). A foodie friend insisted we go there and enjoy the vegan “charcuterie” plate :-) Menu.





I got home in time to watch Antonio Silva administer the beatdown on Fedor. Zhoozhitsu! Zhoozhitsu! Very tough to deal with a bigger, stronger guy with good jits. Fedor kept winging punches looking for the knockout, but once Silva got top position his ground technique was too much for the Russian. I doubt the fight game is very popular at Gather.

I spent almost 12 hours today shooting for an episode of the Science Channel's Through the Wormhole. The producer told me our efforts would result in a 6 minute segment that will air towards the end of the summer. See earlier post for some discussion of the actual science in the episode.

In the episode I drive the VW bug below through a tunnel (the Caldecott tunnel; don't ask how many takes we did!), to simulate what it would be like to go through a wormhole :-)

I had dinner on the north side. Bongo Burger, Top Dog, LaVal's, and some of the Asian restaurants seem to have survived 20+ years of competition :-)





When I was a student here they sometimes ran an ad (soliciting alumni support) in the Daily Californian showing that Berkeley had more Nobel Laureates than the entire USSR. I suppose the lab (now Lawrence Berkeley National Lab) might also, depending on how you count.



The Center for Theoretical Physics on campus. Early atomic bomb calculations were done on this floor of LeConte Hall by Oppenheimer, Teller and Bethe.

Now I am in Berkeley, which is as wonderful as ever :-) Each time I come back here I tell myself I should have done everything possible to stay in the bay area after finishing my PhD! (See Living like kings.)

LBNL finally built its own guest house for visitors, which is right inside the lab near the cafeteria. The rooms have marvelous views of the bay.

Physics library, LeConte Hall, Berkeley, 1987. Studying string theory and Calabi-Yau tomfoolery, not far from the Campanile in the picture above. We'll never have it better than that.

Me: Mike, I can't believe we're in here working on such a beautiful afternoon. Look at that sunshine!

Mike C. (the pride of Jadwin Hall):

Hsu, we're doing exactly what we want to be doing.

We're livin' like kings, man! Livin' like kings (big grin).

1986 -- pounding pitchers with some Sigma Chi's at Kip's. Berkeley frats rented extra rooms in the summer, and some of the coed boarders were with us.

"Gettin' pretty heated!"

"Heated?"

"Drunk, buzzed."

"Yeah, we're heated."

"So are they ..." Nods across the table. "Which one do you like?"

"The small one would be more fun, but the big one wants it."

"You know, they can hear us."

To find a 90 minute podcast of this gathering, which is remarkable for the quality of the speeches given in honor of philosopher John Searle, search under "searle 50 berkeley" at iTunes U (or follow this link).

John Searle’s 50 Years at Berkeley—A Celebration

A celebration of John Searle’s 50 years of distinguished service to the UC Berkeley campus, with reflections by Tom Nagel, Barry Stroud, Robert Cole, Alex Pines, Peter Hanks, and Maya Kronfeld.

While I disagree strongly with Searle's most famous philosophical construct -- the so called Chinese room argument against strong AI (see also here) -- I've always found his writing and argumentation to be exceptionally clear, at least for a philosopher ;-)

See also Paul Graham against philosophy.