I participated in a French Alumni “Cafe virtuel“, organized by the French Alumni association and talking about my professional journey and my research.
Here is the recording: Continue readingSubluminal
Slower than the speed of light, but not by much
Category Archives: projects
Missing millions
(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:
Continue reading
CILAC – Synchrotrons in the Greater Caribbean and Beyond
The Latin American and Caribbean Open Science Forum (CILAC – Foro Abierto de Ciencias de Latinoamérica y el Caribe), an event organized by UNESCO had a satellite even on GCLS/LAMISTAD Symposium: Synchrotrons in the Greater Caribbean and Beyond (website) to which I participated (and help organize)
Day 1:https://www.youtube.com/live/LFEzfNRtfXQDay 2:
https://www.youtube.com/watch?v=bo_U1suKibDay 3:
https://www.youtube.com/watch?v=SP1h0OHqoIc
WordPress issues
Hello readers,
quick note: I’m experiencing issues with WordPress and I couldn’t publish new posts lately.It’s likely I’ll have to do a complete overhaul, so it may take a little while to get back on track.
I hate python
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
Greater Caribbean Light Source
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:Rise of the Machines
Recently, there’s been a lot of interesting activity in the field generative AI for science from large companies such as Google, Meta and Microsoft.
Creating new materials from scratch is difficult, since materials involve complex interactions that are difficult to simulate, or a fair amount of luck in experiments (serendipity is scientists’s most terrifying friend)
Thus most of these efforts aim to discover new material by accelerating simulations using machine learning. But recent advances (such as LLM, e.g., ChatGPT) have shown that you can use AI to make coherent sentences instead of a word soup. But the same way cooking is not just about putting ingredient together all at once but carefully preparing them, making a new material involves important intermediate steps. And new approaches can be used create new materials.
The various steps of making a new material (from Szymanski et al.)
Last month, Google in collaboration with Berkeley Lab announced that their DeepMind’s Gnome project had discovered a lot of new structures: Google DeepMind Adds Nearly 400,000 New Compounds to Berkeley Lab’s Materials Project. They managed to actually make and analyze some of those new materials ; that is quite a tour de force, and while there’s some interesting pushback on the claims, it’s still pretty cool!
In September, I invited Meta’s Open Catalyst at Berkeley Lab (here’s the event description and the recording – accessible to lab employees only)
Zachary Ulissi (Meta/OpenCatalyst) and Jin Qian (Berkley Lab) at Lawrence Berkeley National Laboratory (September 2023)
Meanwhile, Microsoft is collaborating with Pacific Northwest National Laboratory on similar topics
And it’s not limited to US tech firms: Why Is TikTok Parent ByteDance Moving Into Biology, Chemistry And Drug Discovery? – Forbes
Meanwhile, the research infrastructure has it gears moving; it seems that DeepMind’s AlphaFold is already routinely used at the lab to dream up new protein structures. I wonder where this will go!
Prediction is very difficult, especially if it’s about the future– Niels Bohr
Thinkpieces blending chips and AI in full bloom:
We need a moonshot for computing – Brady Helwig and PJ Maykish, Technology Review
The Shadow of Bell Labs
I want to resurface an interesting thread by my former colleague Ilan Gur:
Synchrotron Radiation News
The issue of Synchrotron Radiation News I had the honor to co-edit with my colleagues Lucia Alianelli from Diamond Light Source is out – hot off the press!
Table of Content – Synchrotron Radiation News 36-5 issue on New Developments in Beamline Design Tools (2024)
Synchrotron Radiation News 36-5 issue on New Developments in Beamline Design Tools (2024)
Guest Editorial – Antoine Wojdyla and Lucia Alianelli
https://doi.org/10.1080/08940886.2023.2274751
Luca Rebuffi (Advanced Photon Source, USA) andManuel Sánchez del Río (European Synchrotron Radiation Facility, France)
https://doi.org/10.1080/08940886.2023.227474440 Years of SHADOW: Serving Four Generations of Synchrotron Facilities
Manuel Sánchez del Río (European Synchrotron Radiation Facility, France) and Luca Rebuffi (Advanced Photon Source, USA)
https://doi.org/10.1080/08940886.2023.2274745Status of the Synchrotron Radiation Calculation Code SPECTRA: New Functions and Latest Developments
Takashi Tanaka (Spring-8, Japan)
https://doi.org/10.1080/08940886.2023.2274757Applications of “Synchrotron Radiation Workshop” Code (SRW)
Oleg Chubar and colleagues (National Synchrotron Radiation Facility, USA)
https://doi.org/10.1080/08940886.2023.2274739New Features of xrt: Bent Crystals, Coherent Modes, Waves with OAM
K. Klementiev and R. Chernikov (MavIV, Sweden)
https://doi.org/10.1080/08940886.2023.2274735Developments in X-Ray Optics Modelling at Diamond Light Source
John P. Sutter and colleagues (Diamond Light Source, UK)
https://doi.org/10.1080/08940886.2023.2274754Beamline Optics and Modeling School (BLOMS) 2023
Kenneth Goldberg (Advanced Light Source, USA)
https://doi.org/10.1080/08940886.2023.2274746
On Mentorship
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
Lamaseries
It’s been a few months since the ChatGPT craze started, and we’re finally seeing some interesting courses and guidelines, particularly for coding, where I found the whole thing quite impressive.
Ad hoc use of LLaMa
Here’s a few that can be of interest, potentially growing over time (this is mostly a notes to self.)
- chat.openai.com
- ChatGPT Prompt Engineering for Developers (Andrew Ng)
- Berkeley Lab Guidance on using Generative AI tools
- HuggingFrace’s Wizard coder
- Meta’s Code Llama, through Perplexity: labs.perplexity.ai or HuggingFace
Plus – things are getting really crazy: Large language models encode clinical knowledge (Nature, Google Research.)