(this is a blog entry that was initially a bluesky post – you can follow me at bsky.app/profile/antonymous.bsky.social)
Total US population by Age and Characteristics in December 2024
I was reading the latest report from the @nationalacademies.org on global talents, and the need for a strategy to recruit and train talents. One sentence in the preface about the “missing millions” really caught my attention:
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I hate python.
I’ve worked with many coding languages over the years, starting from C, going into C# and Matlab, and I really loathe python when it comes to scientific computing.My contention with it is that it hampers the kind of rapid iteration needed for exploration – and I struggle teaching its basics to many of my students, who get more confused about the many library imports, the lack of proper IDE or really good REPL that would let them focus on the essential of the code.Here’s a take from LeCun, which I wholly agree with:
If only I could do without it… Alternative are few (say Julia, or rust?) and are not widely used – the curse of path-dependent progress.
A strange take on the Gadsden flag – the true meaning of the snek
Last week I hosted Leo Violini, the founder of the Centro Internacional de Física in Bogotà (Columbia), and a proponent of the the Greater Caribbean Light Source
Big science in Latin America: accelerate particles and progress – Nature (March 2024)
Here is a video of his talk on the proposal for Greater Caribbean Light Source:
And a video of his second talk on science diplomacy:I’ve read an interesting piece on Twitter from the always excellent Kareem Carr on the ladder of causation. I found it very interesting, because it allows you to go beyond the mantra “corelation is not causation“, and links statistics to the concept of falsifiability that Thomas Kuhn puts as central to sciences.
The Ladder of Causation has three levels:
1. Association. This involves the prediction of outcomes as a passive observer of a system.2. Intervention. This involves the prediction of the consequences of taking actions to alter the behavior of a system.3. Counterfactuals. This involves prediction of the consequences of taking actions to alter the behavior of a system had circumstances been different.I even read the book from which – “The Book of Why” [Full book on the Internet Archive] by Judea Pearl, a Turing prize recipient who worked on Bayesian network. The book quite illuminating, mentioning a bit too often dark figures such as Galton, Pearson and Fisher (it seems statistician get really high on their own supply.)
This certainly begs the question – “Why not?”
This last month, I received two awards related to mentorship from Berkeley Lab. They both came as a surprise, since I consider myself more a student of mentorship than someone who has something to show for.
Berkeley Lab Outstanding Mentorship AwardDirector’s award for For building the critical foundations of a complex mentoring ecosystem
I began to be interested in mentorship after I realized that mentorship plays a large role in the success of young scientist, (1) having experience myself the difference between having no mentorship and having appropriate mentorship (I’ll be forever grateful to my mentor/colleague/supervisor Ken Goldberg), (2) having had tepid internship supervision experience due to the lack of guidance, (3) realizing that academia is ill-equipped to provide the resources necessary for success.While I was running Berkeley Lab Series X, I always asked the speakers (typically Nobel prize laureates, stellar scientists and directors of prominent research institutions) how they learned to manage a group, and they answer was generally: “on the spot, via trial and error”, what struck me as awfully wrong. If people don’t get the proper resources/training, many are likely to fail, and drag their own group down the abyss. In this post, I will try to share resources I gathered along the years, and what I learned about mentorship, and provide some resources I found useful. This is more descriptive of my experience than prescriptive, but I hope you find this useful. Continue reading
Lately, there’s been quite some interest in LLM, thanks to ChatGPT
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One of the big concern du jour is plagiarism. Here’s an interesting piece by Noam Chomsky in the
Noam Chomsky: The False Promise of ChatGPT – New York Times.The human mind is a surprisingly efficient and even elegant system that operates with small amounts of information; it seeks not to infer brute correlations among data points but to create explanations.
And a more elaborate conversation:
However, it seems there is a little more at stake. A former classmate of mine who works at Microsoft talked about sparks of Artificial General Intelligence in a podcast – there are emergent properties in AI, meaning that it does not only remix text, but also seem to have an ability to create things merely from structure (short of being able to think.)
AI Frontiers: The Physics of AI with Sébastien Bubeck – AI Frontiers podcast, Microsoft Research
ChatGPT 4.0 can generate code to make a unicorn, even though it has no notion of what a unicorn is, and that code is procedural. (excerpt from Bubeck’s lecture atBerkeley on sparks of AGI)
The same friend is actually exploring what he dubs the Physics of AI: trying not to understand why AI works, but under what circumstances you can make it work.
Excerpt from Bubeck’s lecture on the Physics of AI
The key insights (nevermind the jab at physicists!) is that there are weird phase transitions at work: depending on how you pick your learning parameters, you can get wildly different results – turning the teaching of the machines into an art itself.(update March 2024: check out this fascinating analysis from Sohl Dickstein on how Neural network training makes beautiful fractals)
Computers are great, but –
IBM slide from 1979 (from MIT CSAIL)
In the end, humans will be only be there for liability. In a way this is how American society has evolved.
Personally, I think that the ability to get answers to question without the fear judgement – asking dumb or intimate questions – will have an incredible impact, perhaps more than the productivity gains that are touted by experts (sure – you can generate reports with AI, then summarize these reports with AI: perhaps the thought should have been boiled down i. the first place.)
“To ask the right question is harder than to answer it.”
–Georg Cantor
There is still some room for human thinking.
We were pleased, as Berkeley Lab Global Employee Resource Group co-chairs, to invite and co-organize with Angela Saini at Berkeley Lab on November 9th, 2022.
Author Angela Saini in conversation with Aditi Chakravarti from the Diversity and Inclusion office at Berkeley Lab (IDEA)
More details about the event:
global.lbl.gov/events/idea-speakers-series-angela-saini
It seems that US science may get a 50% boost very soon… If it happens, I am pretty sure amazing things will come out of it, given all the cool research I see happening these days.
–formerly COMPETES (House) and USICA (Senate)
–https://www.energy.gov/articles/statement-secretary-granholm-congressional-passage-chips-and-science-act–$300M for BES Science Facilities
Tucked into the $369B for climate in the Democrats' new spending bill:
-$133M for DOE lab infrastructure
-$304M for high energy physics
-$280M for fusion
-$217M for nuclear physics
-$164M for supercomputing
-$295M for basic science user facilities
-$158M for isotope R&D pic.twitter.com/erLtDK7SPi— FYI Science Policy (@FYIscipolicy) July 28, 2022
Science magazine: U.S. Senate calls for hefty research spending in 2023
There isn’t much representation of scientists in popular culture, with a only few movies standing out, such as a “A Beautiful Mind” (on John Nash) or “Good Will Hunting.” There’s been a few more in the biopic genre lately, such as the “Imitation Game” on Alan Turing or “The Theory of Everything” on Stephen Hawking, and soon a movie on Robert Oppenheimer by Chris Nolan.
But the representation of women in science and technology is even less frequent. Things seem to be changing, and during the pandemic there’s been a few biopics on women scientists, to which I want to bring attention to:
(credit: @truffleduster)
I recently read the amazing book “New Expressions in Origami Art” by Meher McArthur, that I found at the shop Paper Tree in the Japan Town of San Fransisco (it’s one of my favorite shops; they always have stunning origami on display, some for sale, from many origamists featured in the book.)
Every page of the book is a delight, where a modern twists (abstraction, wet folding, tessellation) on origami always bring something very fresh.
One Crease, by Paul Jackson
While reading the book and learning about Goran Konjevod (who seems to be a colleague from Lawrence Livermore National Laboratory), I stumbled on the work of Amanda Ghassaei, who has created the Origami Simulator and many other cool simulation tools producing mesmerizing results.
https://twitter.com/amandaghassaei/status/1352605937077522434 Continue reading