Artificial Intelligence & Large Language Models: Oxford Lecture — Manifold #35

 

This week's episode is based on a lecture I gave to an audience of theoretical physicists at Oxford University. 

Slides 

Audio-only version, transcript: 

https://www.manifold1.com/episodes/artificial-intelligence-large-language-models-oxford-lecture-35

Outline: 

0:00 Introduction 

2:31 Deep Learning and Neural Networks; history and mathematical results 

21:15 Embedding space, word vectors 

31:53 Next word prediction as objective function 

34:08 Attention is all you need 

37:09 Transformer architecture 

44:54 The geometry of thought 

52:57 What can LLMs do? Sparks of AGI 

1:02:41 Hallucination 

1:14:40 SuperFocus testing and examples 

1:18:40 AI landscape, AGI, and the future

Final slide:

Quantum Hair and Black Hole Information, University of Amsterdam, 17 Jun 2022

 

As promised, video from my talk in Amsterdam. 

Seminar at the Institute of Physics, University of Amsterdam, 17 Jun 2022. 

Title: Quantum Hair and Black Hole Information 

Abstract: I discuss recent results concerning the quantum state of the gravitational field of a compact matter source such as a black hole. These results demonstrate the existence of quantum hair, violating the classical No Hair Theorems. I then discuss how this quantum hair affects Hawking radiation, allowing unitary evaporation of black holes. Small corrections to leading order Hawking radiation amplitudes, with weak dependence on the external graviton state, are sufficient to produce a pure final radiation state. The radiation state violates the factorization assumption made in standard formulations of the information paradox. These conclusions are consequences of long wavelength properties of quantum gravity: no special assumptions are made concerning short distance (Planckian) physics. 

Slides

Institute of Physics, University of Amsterdam:

Amsterdam, Utrecht, Split, Hvar

Last week I was in Amsterdam and Utrecht to give seminars on quantum hair and black hole information at the Universities of Utrecht and Amsterdam. The organizers told me I was the first external visitor to give an in-person talk since the COVID lockdowns. 

The Utrecht seminar went over 2 hours (unfortunately, 't Hooft was away) and the other over 90 minutes. 

I will post video of the seminars at some point. 

Now I am at the John Bell Institute on Hvar, Croatia for a special workshop on the black hole information puzzle. 

This is the view of the Adriatic from the John Bell Institute, and the beach:

 

Institute of Physics, University of Amsterdam:

Seminar on Black Hole Information and Quantum Hair, Yangzhou University (video)

 

Center for Gravitation and Cosmology, Yangzhou University (May 16 2022) 

There were several good questions at the end, and a discussion of the following rather fundamental topic.

In the conventional description of quantum measurement a pure state evolves into a mixed state, with probabilities of distinct outcomes (non-unitary von Neumann projection). 

See, e.g., 

Against Measurement (John Bell)

Black holes and decoherence 

What Hawking suggested is that a black hole (i.e., gravity) causes pure states to evolve into mixed states. But if pure states already evolve into mixed states in ordinary quantum mechanics, why is it problematic for black hole physics (gravity) to have this effect? 

Title: Quantum Hair and Black Hole Information 

Abstract: I discuss recent results concerning the quantum state of the gravitational field of a compact matter source such as a black hole. These results demonstrate the existence of quantum hair, violating the classical No Hair Theorems. I then discuss how this quantum hair affects Hawking radiation, allowing unitary evaporation of black holes. Small corrections to leading order Hawking radiation amplitudes, with weak dependence on the external graviton state, are sufficient to produce a pure final radiation state. The radiation state violates the factorization assumption made in standard formulations of the information paradox. These conclusions are consequences of long wavelength properties of quantum gravity: no special assumptions are made concerning short distance (Planckian) physics.

Slides.

Quantum Hair and Black Hole Information -- Quantum Gravity and All of That seminar series (video)

 

May 5 2022 talk in the international seminar series Quantum Gravity and All of That. 

The talk is pitched at a slightly more expert audience than previous versions I have given. 

There are interesting comments by and discussions with G. Veneziano, V. Rubakov, Suvrat Raju and others during the seminar. 

The Zoom client on ChromeOS does not allow me to see others in the meeting when I share my slides fullscreen. So at times I was not sure whose questions I was responding to! 

Slides.

Title: Quantum Hair and Black Hole Information 

Abstract: I discuss recent results concerning the quantum state of the gravitational field of a compact matter source such as a black hole. These results demonstrate the existence of quantum hair, violating the classical No Hair Theorems. I then discuss how this quantum hair affects Hawking radiation, allowing unitary evaporation of black holes. Small corrections to leading order Hawking radiation amplitudes, with weak dependence on the external graviton state, are sufficient to produce a pure final radiation state. The radiation state violates the factorization assumption made in standard formulations of the information paradox. These conclusions are consequences of long wavelength properties of quantum gravity: no special assumptions are made concerning short distance (Planckian) physics.

Has Hawking's Black Hole Information Paradox Been Resolved? (Video of MSU Theory Seminar 4/22/2022)

 

Theory seminar at Michigan State University April 22 2022. 

Title: Has Hawking's Black Hole Information Paradox Been Resolved? 

Abstract: In 1976 Stephen Hawking argued that black holes cause pure states to evolve into mixed states. Put another way, quantum information that falls into a black hole does not escape in the form of radiation. Rather, it vanishes completely from our universe, thereby violating a fundamental property of quantum mechanics called unitarity. I give a pedagogical introduction to this paradox, suitable for non-experts. Then I discuss recent results concerning the quantum state of the gravitational field of a compact matter source. These results demonstrate the existence of quantum hair, violating the classical No Hair Theorems. I then discuss how this quantum hair affects Hawking radiation, allowing unitary evaporation of black holes. 

Slides.

Black Hole Information and Quantum Hair: seminar video and slides

 

This is video of a seminar I gave at the University of Sussex. Slides.

Has Hawking's Black Hole Information Paradox Been Resolved? Quantum Hair and Black Hole Information 

Abstract: In 1976 Stephen Hawking argued that black holes cause pure states to evolve into mixed states. Put another way, quantum information that falls into a black hole does not escape in the form of radiation. Rather, it vanishes completely from our universe, thereby violating a fundamental property of quantum mechanics called unitarity. I give a pedagogical introduction to this paradox, suitable for non-experts. Then I discuss recent results concerning the quantum state of the gravitational field of a compact matter source. These results demonstrate the existence of quantum hair, violating the classical No Hair Theorems. I then discuss how this quantum hair affects Hawking radiation, allowing unitary evaporation of black holes.

See this related blog post: Has Hawking's Black Hole Information Paradox Been Resolved?

In the talk I mention an introductory colloquium on the history of black holes and the connection to entropy and information. See slides.

Macroscopic Superpositions in Isolated Systems (talk video + slides)

 

This is video of a talk based on the paper

Macroscopic Superpositions in Isolated Systems 

R. Buniy and S. Hsu 

arXiv:2011.11661, to appear in Foundations of Physics 

For any choice of initial state and weak assumptions about the Hamiltonian, large isolated quantum systems undergoing Schrodinger evolution spend most of their time in macroscopic superposition states. The result follows from von Neumann's 1929 Quantum Ergodic Theorem. As a specific example, we consider a box containing a solid ball and some gas molecules. Regardless of the initial state, the system will evolve into a quantum superposition of states with the ball in macroscopically different positions. Thus, despite their seeming fragility, macroscopic superposition states are ubiquitous consequences of quantum evolution. We discuss the connection to many worlds quantum mechanics.

Slides for the talk.

See this earlier post about the paper:

It may come as a surprise to many physicists that Schrodinger evolution in large isolated quantum systems leads generically to macroscopic superposition states. For example, in the familiar Brownian motion setup of a ball interacting with a gas of particles, after sufficient time the system evolves into a superposition state with the ball in macroscopically different locations. We use von Neumann's 1929 Quantum Ergodic Theorem as a tool to deduce this dynamical result. 

The natural state of a complex quantum system is a superposition ("Schrodinger cat state"!), absent mysterious wavefunction collapse, which has yet to be fully defined either in logical terms or explicit dynamics. Indeed wavefunction collapse may not be necessary to explain the phenomenology of quantum mechanics. This is the underappreciated meaning of work on decoherence dating back to Zeh and Everett. See talk slides linked here, or the introduction of this paper.

We also derive some new (sharper) concentration of measure bounds that can be applied to small systems (e.g., fewer than 10 qubits). 

Related posts:

Classics on the arxiv: von Neumann and the foundations of quantum statistical mechanics 

Pure State Quantum Thermalization: from von Neumann to the Lab 

Entanglement and fast thermalization in heavy ion collisions 

Harvard CMSA talks (video)

I recently came across this channel on YouTube, produced by CMSA at Harvard.

The new Center for Mathematical Sciences and Applications in the Faculty of Arts and Sciences will serve as a fusion point for mathematics, statistics, physics, and related sciences. Evergrande will support new professorships, research, and core programming. 

Shing-Tung Yau, Harvard’s William Caspar Graustein Professor of Mathematics, will serve as the center’s first director. 

“The Center for Mathematical Sciences and Applications will establish applied mathematics at Harvard as a first-class, interdisciplinary field of study, relating mathematics with many other important fields,” Yau said. “The center will not only carry out the most innovative research but also train young researchers from all over the world, especially those from China. The center marks a new chapter in the development of mathematical science.”

If I'm not mistaken Evergrande is a big real estate developer in China. It's nice to see them supporting mathematics and science in the US :-) 

In 2010 I accompanied S.T. Yau and a number of other US academics and technologists to visit Alibaba, which wanted to establish a center for data science in China. Unfortunately this never really got off the ground, but CMSA looks like it is off to a good start. 

Here are some talks I found interesting. There are quite a few more.

The talk on Atiyah, Geometry, and Physics led me to this poem which I like very much. Sadly, Atiyah passed in 2019. I believe we met once at a dinner at the Society of Fellows, but I hardly knew him.

In the broad light of day mathematicians check their equations and their proofs, leaving no stone unturned in their search for rigour. 

But, at night, under the full moon, they dream, they float among the stars and wonder at the mystery of the heavens: they are inspired. 

Without dreams there is no art, no mathematics, no life. 

—Michael Atiyah

Genomic Prediction and Embryo Selection (video panel discussion)

 

This is a recent panel discussion on genomic prediction, and applications in IVF and health systems (e.g., early screening of high risk individuals for breast cancer, heart disease). 

Jamie Metzl and Simon Fishel are my co-panelists. Metzl is the author of the best seller Hacking Darwin: Genetic Engineering and the Future of Humanity. Fishel was part of the team that produced the first IVF baby in 1978, and has been a leader in IVF research ever since. 

Today millions of babies are produced through IVF. In most developed countries roughly 3-5 percent of all births are through IVF, and in Denmark the fraction is about 10 percent! But when the technology was first introduced with the birth of Louise Brown in 1978, the pioneering scientists had to overcome significant resistance. There may be an alternate universe in which IVF was not allowed to develop, and those millions of children were never born.

Wikipedia: ...During these controversial early years of IVF, Fishel and his colleagues received extensive opposition from critics both outside of and within the medical and scientific communities, including a civil writ for murder.[16] Fishel has since stated that "the whole establishment was outraged" by their early work and that people thought that he was "potentially a mad scientist".[17]

I predict that within 5 years the use of polygenic risk scores will become common in some health systems and in IVF. Reasonable people will wonder why the technology was ever controversial at all, just as in the case of IVF.

Previous discussion: Sibling Validation of Polygenic Risk Scores and Complex Trait Prediction (Nature Scientific Reports)

When Machine Learning Met Genetic Engineering | CogX 2019 (video)

 

I recently came across this video on YouTube. 

Hard to believe it's been over a year since the conference. 2020 versions of these meetings were all killed by the pandemic.

Post from June 2019: London: CogX, Founders Forum, Healthtech

I'm in London again to give the talk below and attend some meetings, including Founders Forum and their Healthtech event the day before.

CogX: The Festival of AI and Emerging Technology
King's Cross, London, N1C 4BH

When Machine Learning Met Genetic Engineering

3:30 pm Tuesday June 11 Cutting Edge stage

Speakers

Stephen Hsu
Senior Vice-President for Research and Innovation
Michigan State University

Helen O’Neill
Lecturer in Reproductive and Molecular Genetics
UCL

Martin Varsavsky
Executive Chairman
Prelude Fertility

Azeem Azhar (moderator)
Founder
Exponential View

Regent's Canal, Camden Town near King's Cross.

CogX speakers reception, Sunday evening:

HealthTech

Commanding heights of global capital:

Sunset, Camden locks:

Cold Spring Harbor Laboratory: Seminar and Photos

Last week I visited Cold Spring Harbor Laboratory to give a seminar.

The new material is in slides 13-17. See also Live Long and Prosper: Genetic Architecture of Complex Traits and Disease Risk Predictors. I believe the sibling validation results are extremely important: typically most of the predictive power persists in within-family validation tests. We have not released this paper but will soon -- the slides are a preview. To be honest I fully anticipated these results: the large number of out of sample predictor validations using unrelated individuals strongly suggests that real genetic effects are at work. However, many people are irrationally biased against -- have strong priors against -- genetic causation of complex traits (even disease risks). These family designs provide important "gold standard" evidence, which, one can hope, will enlighten even the most stubborn. The sad alternative is progress one funeral at a time...

Otherwise the talk is similar to the one I gave at the Berkeley/UCSF Innovative Genomics Institute last summer. Video of IGI 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.

Some photos. The ones on the wall of the seminar room capture a golden era in molecular biology and the study of DNA. Leo Szilard on the right in the one below. Also, Jacques Monod, Crick and Watson, Wally Gilbert, Max Delbruck, Frank Stahl, Francois Jacob, David Baltimore. Of these individuals I have known four in person. I would give a lot to have met Crick and especially Szilard. While at CSHL I learned that James Watson is still alive and intellectually active.

See H. Judson's The Eighth Day of Creation (PDF) for a brilliant but readable history of the golden age of molecular biology.

Future Investment Initiative (Riyadh)

I'm making my way home from the FUTURE INVESTMENT INITIATIVE 2019 in Riyadh, Saudi Arabia​​​. At the moment I am sitting in a Lufthansa lounge at Frankfurt.

The annual event is sponsored by the Saudi sovereign wealth fund, or PIF (Public Investment Fund), which is one of the largest pools of capital in the world.

The meeting this year had an AI theme, and I spoke in the AI and Health (genomics) session. The mix of people was very interesting -- VC, hedge fund, and private equity investors (among other things, looking for allocations from PIF), tech entrepreneurs, policy and government people, etc. There was a large Chinese contingent at the meeting, and a strong Huawei presence. IIUC the telco infrastructure in the Kingdom uses a lot of Huawei gear.

I got a Star Wars cantina in business suits vibe from the thousands of attendees at the Ritz. The various global tribes were there in almost equal mixture -- Americans (Silicon Valley + NY money), Euro-grifters, money men, technologists, spooks, government suits, Chinese, Arabs, Indians, Russians (even Sputnik News). The Kingdom is really at the global crossroads.

Right away on the first day I "bumped into" someone from the US embassy. Her card says State, but I suspect another agency with three letters.

My hotel was in the DQ or Diplomatic Quarter, not far from the Ritz. The DQ is separated from the rest of the city by serious security checkpoints. The Saudi soldiers like to wear their pistols low on the thigh with cool looking black polymer "gunfighter" holsters.

See also The Geopolitics of US Global Decline: Beijing and Washington Struggle for Dominion over the World Island.

Kaifu Lee and Stephen Schwarzman dialog.

Our panel on AI and Health was held here:

The gala reception in the King Abdullah Financial District. An interesting little drone hovered above the crowd all evening.

My speaker pass. I had a driver and was able to get through the numerous security checkpoints quickly using this. MBS has his own elite Royal Guard, and they were in evidence at the event.

Over the summer I also spoke at the Tallinn Digital Summit and the World Congress of Information Technology in Yerevan Armenia -- lots of travel! I haven't even had time to blog about these events. There are videos of my talks and panels I will try to post at some point.

TDS 2019: Panel on AI social and political impacts
https://youtu.be/fddG7hQkkW4

TDS 2019 Parallel Breakout Sessions I: AI in Healthcare
https://youtu.be/atOnB1dW0OA

Tallinn Digital Summit YouTube Channel
https://www.youtube.com/channel/UC9ptGynkOPe3vFRW6otoI3g

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.

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.

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.

London: CogX, Founders Forum, Healthtech

I'm in London again to give the talk below and attend some meetings, including Founders Forum and their Healthtech event the day before.

CogX: The Festival of AI and Emerging Technology
King's Cross, London, N1C 4BH

When Machine Learning Met Genetic Engineering

3:30 pm Tuesday June 11 Cutting Edge stage

Speakers

Stephen Hsu
Senior Vice-President for Research and Innovation
Michigan State University

Helen O’Neill
Lecturer in Reproductive and Molecular Genetics
UCL

Martin Varsavsky
Executive Chairman
Prelude Fertility

Azeem Azhar (moderator)
Founder
Exponential View

Regent's Canal, Camden Town near King's Cross.

CogX speakers reception, Sunday evening:

HealthTech

Commanding heights of global capital:

Sunset, Camden locks:

Janelia (HHMI) talk: Genomic Prediction of Complex Traits and Disease Risks via AI and Large Genomic Datasets

Janelia is the research campus of the Howard Hughes Medical Institute (HHMI), located near Washington DC. It is reputed to be heaven on earth for scientists :-)

I'll be visiting there next week (see title and abstract below). If you're at Janelia and want to meet with me there is still a little space on my schedule. Or just come to the talk and try to grab me afterward.

My talk is Tuesday May 7 12:30 – 1:30.

Genomic Prediction of Complex Traits and Disease Risks via AI 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 concerning genetic architecture. 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.

Manifold Show, episode 2: Bobby Kasthuri and Brain Mapping

Show Page    YouTube Channel

Our plan is to release new episodes on Thursdays, at a rate of one every week or two.

We've tried to keep the shows at roughly one hour length -- is this necessary, or should we just let them go long?

Corey and Steve are joined by Bobby Kasthuri, a Neuroscientist at Argonne National Laboratory and the University of Chicago. Bobby specializes in nanoscale mapping of brains using automated fine slicing followed by electron microscopy. Among the topics covered: Brain mapping, the nature of scientific progress (philosophy of science), Biology vs Physics, Is the brain too complex to be understood by our brains? AlphaGo, the Turing Test, and wiring diagrams, Are scientists underpaid? The future of Neuroscience.

Bobby Kasthuri Bio
https://microbiome.uchicago.edu/directory/bobby-kasthuri 

The Physicist and the Neuroscientist: A Tale of Two Connectomes
http://infoproc.blogspot.com/2017/10/the-physicist-and-neuroscientist-tale.html

COMPUTING MACHINERY AND INTELLIGENCE, A. M. Turing https://www.csee.umbc.edu/courses/471/papers/turing.pdf


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.

On with the Show

Our YouTube / podcast show is live!

Show Page

YouTube Channel

Podcast version available on iTunes and Spotify.

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.