Category Archives: ressources

Self-reference

Self-reference is cornerstone in Hofstadter’s Godel-Escher-Bach, a must read book for anyone interested in logic (and we shall rely logic in these days to stay sane.)

Here’s a bunch of examples of self-reference that I found interesting, curated just for you!

Barber’s paradox:

The barber is the “one who shaves all those, and those only, who do not shave themselves.” The question is, does the barber shave himself?

Self-referential figure (via xkcd):

Tupper’s formula that prints itself on a screen (via Brett Richardson) Continue reading

Quick’n’dirty

Over the years I’ve collected quotes from people who are.

I always like quotes, because they are atoms of knowledge, quick and dirty ways to understand the world we only have one life to explore. To some extent, they axioms of life in that they are true and never require an explanation (otherwise they wouldn’t be quotations.)

Here’s a bunch of quotes that I found particularly interesting, starting with my absolute favorite quote comes from the great Paul Valery:

The folly of mistaking a paradox for a discovery, a metaphor for a proof, a torrent of verbiage for a spring of capital truths, and oneself for an oracle, is inborn in us. – Paul Valery

On research — trial and error

Basic research is like shooting an arrow into the air and, where it lands, painting a target.
-Homer Burton Adkins

A thinker sees his own actions as experiments and questions–as attempts to find out something. Success and failure are for him answers above all.
– Friedrich Nietzsche
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Learning Deep

In the past four years, there’s been a lot of progress in the field of machine learning, and here’s a story seen from the outskirts.

Eight years ago, for a mock start-up project, we tried to do some basic headtracking. At that time, my professor Stéphane Mallat told us that the most efficient way to do this was the Viola-Jones algorithm, which was still based on hard-coded features (integral images and Haar features) and a hard classifier (adaboost.)

(I was thrilled when a few years later Amazon Firephone was embedding similar features; unfortunately, this was a complete bomb — better technologies now exist and will make a splash pretty soon.)

By then, the most advanced book on machine learning was “Information Theory, Inference, and Learning” by David McKay, a terrific book to read, and also “Pattern Recognition and Machine Learning” by Chris Bishop (which I never read past chapter 3, lack of time.)

Oh boy, how things have changed!

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Julia Language

A few years ago, I got interested in the then-nascent Julia language (julialang.org), a new open source language based on Matlab syntax with C-like performances, thanks to its just-in-time compiler.

Large Synoptic Survey Telescope (LSST, Chile) data being processed with Julia on super computers with 225x speedup

Large Synoptic Survey Telescope (LSST, Chile) data being processed with Julia on super computers with 200x speedup (from https://arxiv.org/pdf/1611.03404.pdf)

It now seems that the language is gaining traction, with many available packages, lots of REPL integration (it works with Atom+Hydrogen, and I suspect Jupyter gets its first initial from Julia and Python) and delivering on performances.

Julia is now used on supercomputers, such as Berkeley Lab’s NERSC, taught at MIT (by no less than Steven G Johnson, the guy who brought us FFTW and MEEP!), and I’ve noticed that some of the researchers from Harvard’s RoLi Lab I’ve invited to SPIE DCS 2018 are sharing their Julia code from their paper “Pan-neuronal calcium imaging with cellular resolution in freely swimming zebrafish“. Pretty cool!

Julia used for code-sharing in a Nature publication. I wish I could see that every day!

Julia used for code-sharing in a Nature publication. I wish I could see that every day!

I got a chance to attend parts of Julia Con 2017 in Berkeley. I was amazed by how dynamic was the the community, in part supported by Moore’s foundation (Carly Strasser, now head of Coko Foundation), and happy to see Chris Holdgraf (my former editor at the Science Review) thriving at the Berkeley Institute for Data Science (BIDS).

Julia picking up speed at Intel (picture taken dusing JuliaCon 2017)

Julia picking up speed at Intel (picture taken dusing JuliaCon 2017)

I started sharing some code for basic image processing (JLo) on Github. Tell me what you think!

(by the way, I finally shared my meep scripts on github, and it’s here!)

ALS-U

Some may have been wondering what I have been up to lately!
At the beginning of the year, I started working on the ALS-U project, which is the  upgrade of the Advanced Light Source, the main synchrotron at Lawrence Berkeley National Laboratory. The goal is to improve the facility with a Diffraction-Limited Storage Ring (DLSR), in order to increase the brilliance of the beam, so as allow scientists from all over the world to perform the most precise experiments, allowing bright and full coherent beams with diameters as small as 10 nanometer, or twice the width of a strand of DNA. (here’s a report on all the niceties you can do with such a tool: ALS-U: Solving Scientific Challenges with Coherent Soft X-Rays)

ALS-U logo Continue reading

Qubit

I’ve run my first quantum computation!

Since I was working on the latest iteration of classical computer manufacturing techniques (EUV lithography), everyone asked me what were my thought on the future of Moore’s law, and what did I think about quantum computing. To the first question, I could mumble things about transistor size and the fact that we’re getting awfully close to the atomic size; to the latter question… I just had to go figure out myself!

Back in April, I’ve invited Irfan Siddiqi (qnl.berkeley.edu), founding director of the brand new Center for Quantum Coherent Science, and his postdocs at Berkeley lab to give a talk to postdocs, and last the lab announced the first 45-qubits quantum simulations on the NERSC… things are going VERY fast! (read the Quantum manifesto)

Kevin O'Brien on multiplexing qubit readouts

Kevin O’Brien on multiplexing qubit readouts

This is thanks to Rigetti, a full-stack quantum computer startup based in Berkeley (Wired, IEEE Spectrum).

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Open Access

My article for the Berkeley Science Review on Open Access is out, and it is available here (for free, of course!): Science to the people.

“Astronomers and physicists have been sharing pre-prints since before the web existed,” says Alberto Pepe, founder of the authoring and pre-printing platform Authorea. “Pre-prints are an effective (and fully legal) way to make open access a reality in all scholarly fields.” Within hours, articles are available online, and scientists can interact with the author, leaving comments and feedback. Importantly, submission, storage, and access are all free. The pre-printing model ensures that an author’s work is visible and properly indexed by a number of tools, such as Google Scholar.

Special thanks to Rachael Samberg from thee UC Library and Alberto Pepe from Authorea.

Things seems to change quickly in that field, thanks to institutional efforts:

Here’s a list of resources that I’ve compiled from the talk by Laurence Bianchini from MyScienceWork when I invited at LBL, and a piece written by Nils Zimmerman on Open Access at LBNL: Open Access publishing at Berkeley Lab.

Farewell to BPEP!

Yesterday, I’ve organized my last event with the Berkeley Postdoc Entrepreneurial Program (bpep.berkeley.edu), an association dedicated to helping young researchers turning their science into companies that can benefit the economy directly. I served for about two years as the liaison for Berkeley Lab, and helped organize over a dozen events, directly responsible for four of them (on government funding, intellectual property, the art of pitch, and lastly a job fair.)

BPEP team with UC Berkeley vice-chancellor for reasearch, Paul Alivisatos

BPEP team with UC Berkeley vice-chancellor for research, Paul Alivisatos

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Berkeley Lab Postdoc Association

Dear reader,

I haven’t been very communicative lately, for I was kept busy by a very cool new venture : the birth of the Berkeley Lab Postdoc Association. The new association is meant to bring together over a thousand postdocs at Berkeley Lab, and provide them with support, career advice and bring feedback to the lab management about issues encountered by postdocs.logo_blpaNow that the association is alive and well (see the blog), I can tell a little about its story.

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Wanted : science tools for the digital age

The internet may still be less than 10,000-days old, it still fails to deliver for scientists.

By empowering institutions to efficiently track down the number of publications, pushing even further the drive to publish many half-baked ideas and follow the hype instead of long-term research. It is true that it had never been as simple to get access to a paper and makes life easier on many aspects– collaboration often just requires sending an email, but new hurdles have appeared, and these should be removed.05e2e400dd1165870b3787a527e4e753Here is a bunch of ideas on how to use the new digital tools we have at hand to make research easier and thus more efficient, and a limited overview of what we have now. Continue reading