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Anselm Levskaya

@levskaya.bsky.social
1.6K followers 262 following 7 posts

Doing spooky things with linear algebra.

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Anselm Levskaya @levskaya.bsky.social · 07/06/2025
Oh gods - let us know in DMs or otherwise how we’re the source of suffering.
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Anselm Levskaya @levskaya.bsky.social · 07/06/2025
What unholy artifact is asking you to do that?
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Thomas Ptacek @sockpuppet.org · 04/06/2025
My "early-career" developer feelings are complicated and alienating to SFBA-type career ladder people.
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Stephen Curry @scurry.bsky.social · 23/05/2025
If your test for ground-breaking discoveries can’t detect the discovery of RNAi, or of CRISPR-Cas9, or the cryoEM resolution revolution or Alphafold2, maybe it’s not a very good test. www.nature.com/articles/d41...
Graph claiming to show a decline in groundbreaking discoveries flatlines for the life sciences around zero from about 1996 onwards.
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Ethan Mollick @emollick.bsky.social · 20/05/2025
At some point, the fact that over a billion people use this technology and that they self-report high utility has to mean something. There is lots to criticize about AI and plenty of real issues caused by AI, but the narrative that this is all a fake thing that will disappear doesn't help anyone.
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Charlie Marsh @crmarsh.com · 13/05/2025
Today, we’re announcing the preview release of ty, an extremely fast type checker and language server for Python, written in Rust. In early testing, it's 10x, 50x, even 100x faster than existing type checkers. (We've seen >600x speed-ups over Mypy in some real-world projects.)
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Ryan Moulton @moultano.bsky.social · 12/05/2025
This isn't true. I'm the person who ran the experiments this is BSing about. When search results are worse, people attempt fewer tasks. When they're better they attempt more.
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Sam @samd.bsky.social · 23/04/2025
LET’S FUCKING GOOOO THE MOST AMBITIOUS HOUSING BILL IN THE HISTORY OF THE STATE OF CALIFORNIA HAS ADVANCED OUT OF COMMITTEE
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Zach Hensel @zachhensel.bsky.social · 12/04/2025
@zey.bsky.social I’m not on the site with Nazis anymore — wtf are you saying about me over there? You know there’s new data on the origins question, right?
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Zach Hensel @zachhensel.bsky.social · 11/04/2025
The case for "lab leak" book "VIRAL" by Alina Chan and Matt Ridley leaned heavily on two facts in 2021: 1. The Wuhan Institute of Virology had sampled the virus most identical to SARS-CoV-2 2. SARS-CoV-2 lineage B, but not lineage A, was found in Huanan market By 2022, neither was true, so...
Excerpts from 1st and 2nd editions of VIRAL by Alina Chan and Matt Ridley. A sentence is highlighted that was removed once it was no longer true. Their conclusions did not change.Excerpts from 1st and 2nd editions of VIRAL by Alina Chan and Matt Ridley. A phrase is highlighted that was removed once it was no longer true. Their conclusions did not change.
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Jieyu Zheng @jieyusz.bsky.social · 12/04/2025
My first outing of "The Unbearable Slowness of Being" at the Caltech Chen Neuroscience Workshop today! What does living at 10 bits/s mean for humans, flies, mice, and crows? More here: jieyusz.github.io/talks/2025_c... Thanks to Profs. @cfcamerer.bsky.social & Carlos for the invite!
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Diego del Alamo @delalamo.xyz · 03/03/2025
There it is again: using PLMs to predict antigen-epitope interactions from sequence alone yields a prediction accuracy of 0.65, in line with a proposed upper limit from a previous study QTed below (from doi.org/10.1101/2025.02.12.637989; I deleted an older version of this post due to typos/errors)
From the paper abstract, "we find that antibody-specific PLMs such as AntiBERTy and general PLMs such as ProtTrans and ESM-2 for antigens provide improved epitope prediction performance with an AUCROC of 0.65, precision of 0.28, and recall of 0.46"
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Thomas Wolf @thomwolf.bsky.social · 19/02/2025
After 6+ months in the making and over a year of GPU compute, we're excited to release the "Ultra-Scale Playbook": hf.co/spaces/nanot... A book to learn all about 5D parallelism, ZeRO, CUDA kernels, how/why overlap compute & coms with theory, motivation, interactive plots and 4000+ experiments!
hf.co
The Ultra-Scale Playbook - a Hugging Face Space by nanotron
The ultimate guide to training LLM on large GPU Clusters
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Fred Scharmen @sevensixfive.bsky.social · 26/01/2025
Ceding techno optimism to the right is a generational scale mistake
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Angie Rasmussen @angierasmussen.bsky.social · 17/02/2025
AI is revolutionary but it also elicits some of the dumbest LinkedIn takes of all time. I’d like this lawyer whose primary expertise is scaremongering for EA money to explain how using “future kinds of models” starts pandemics. Outline the model to pandemic pipeline for me.
“Future kinds of models, both frontier models—and also models trained on biological data—could potentially bring about biological harms with a global impact, like a new pandemic.”
Anita Cicero, Deputy Director, Johns Hopkins Center for Health Security
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Jeff Dean @jeffdean.bsky.social · 09/02/2025
Well said, @carlbergstrom.com. I also feel the dismantling of our scientific institutions & funding agencies for basic science is an attack on all scientists, wherever they might be (government or corporate lab, academic institution, ...). Our collective identities are about advancing knowledge.
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Jeff Dean @jeffdean.bsky.social · 09/02/2025
Another example of what cutting science funding is doing to our leading university research programs in the U.S.: dismantling things like the Soybean Innovation Lab at UIUC, which have made US crop yields dramatically higher.
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Roy Frostig @froystig.bsky.social · 04/02/2025
Our online book on systems principles of LLM scaling is live at jax-ml.github.io/scaling-book/ We hope that it helps you make the most of your computing resources. Enjoy!
jax-ml.github.io
How To Scale Your Model
Training LLMs often feels like alchemy, but understanding and optimizing the performance of your models doesn't have to. This book aims to demystify the science of scaling language models on TPUs: how...
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Michael Eisen @mbeisen.bsky.social · 04/02/2025
Y'all are just noticing that scientific societies are obsequious cowards on everything except preserving their publishing cash cows?
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jacobaustin123.bsky.social @jacobaustin123.bsky.social · 04/02/2025
Making LLMs run efficiently can feel scary, but scaling isn’t magic, it’s math! We wanted to demystify the “systems view” of LLMs and wrote a little textbook called “How To Scale Your Model” which we’re releasing today. 1/n
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Anne Applebaum @anneapplebaum.wsocial.eu · 07/01/2025
"When conspiracy theories and nonsense cures are widely accepted, the evidence-based concepts of guilt and criminality vanish quickly too." www.theatlantic.com/magazine/arc...
theatlantic.com
The New Rasputins
Anti-science mysticism is enabling autocracy around the globe.
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Derek Lowe @dereklowe.bsky.social · 06/01/2025
Re-upping this reply thread from last night. Drugs don't come from nowhere, folks. And we're not ripping off the NIH, either.
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Nathaniel Johnston @njohnston.ca · 20/12/2024
There's been a bunch of claims (mostly on X) that ChatGPT did great on this year's Putnam math competition. Let's do a thread to talk about it! 🧵 #MathSky
A screenshot of a Tweet claiming that OpenAI o1 scored in the top 1%-2% of participants in the Putnam math competition.
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Jieyu Zheng @jieyusz.bsky.social · 17/12/2024
Attached is a piece of art by me for "The Unbearable Slowness of Being: Why do we live at 10 bits/s?" Hope this will inspire you to think about the brain from a new perspective!
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Anselm Levskaya @levskaya.bsky.social · 19/12/2024
You really need long (compared to cells) metal antennae for decent radio, and biology never got that good at reducing and templating crystalline metals/alloys.
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Sara Hooker @sarahooker.bsky.social · 04/12/2024
AI amplifying biorisk has been a major focus in AI policy & governance work. Is the spotlight merited? Our recent cross-institutional work asks: Does the available evidence match the current level of attention? 📜 arxiv.org/abs/2412.01946
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Ash Jogalekar @ashjogalekar.bsky.social · 15/12/2024
In early phase drug discovery, biology and assays are make-or-break. I can remember very few programs I worked on which were hampered by the inability to make molecules, but plenty that were hampered by the inability to capture disease biology complexity on a chip or in an enzyme readout.
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🎃 scarecrowcialism 👻 @swolecialism.bsky.social · 12/12/2024
All western US water issues are entirely caused by the cultivation of cash crops in places that they shouldn't be grown. Everything, literally everything else, is a rounding error
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Shae Mclaughlin @shaemcl.bsky.social · 12/12/2024
Here is the model it was trained on! Preprint went up on bioRxiv last week: www.biorxiv.org/content/10.1...
biorxiv.org
Nucleotide GPT: Sequence-Based Deep Learning Prediction of Nuclear Subcompartment-Associated Genome Architecture
The spatial organization of the genome within the nucleus is partially determined by its interactions with distinct nuclear subcompartments, such as the nuclear lamina and nuclear speckles, which play...
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Shae Mclaughlin @shaemcl.bsky.social · 12/12/2024
I trained a sparse autoencoder on the middle layer residual stream of my genome language model and found human-interpretable latent features that consistently detect specific DNA motifs! 🧵1/8
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Dan Roy @roydanroy.bsky.social · 23/11/2024
Reviewing is dead. I just read some ICLR reviews. Absolutely junk. No insight. Written by humans, but could have been written by a chatbot or teenager who had read a few dozen reviews. Why do we think this is useful? Only 5% (if that!) of the community has worthwhile opinions.
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Anselm Levskaya @levskaya.bsky.social · 20/11/2024
BOS, BOE have been amazing, hadn’t realized you did SFMTA as well. Thank you so much for this service over the years!
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Ben Recht @beenwrekt.bsky.social · 25/10/2024
Following up on Kyle Cranmer's excellent and measured response to my inflammatory Higgs missive. www.argmin.net/p/toward-a-t...
argmin.net
Toward a Transformative Hermeneutics of Standard Model Physics
A dialogue with Kyle Cranmer
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Ben Recht @beenwrekt.bsky.social · 22/10/2024
The Higgs Discovery did not take place. www.argmin.net/p/the-higgs-...
argmin.net
The Higgs Discovery Did Not Take Place
Some noncontroversial blogging during midterm break
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Julia Evans @b0rk.jvns.ca · 22/10/2024
to celebrate selling out the first print run of How Integers and Floats work, we're giving away 500 PDF copies! use code BUYONEGIVEONE at checkout to get a copy for free As usual this works with the honour system, use the code if $12 USD is a lot of money for you! wizardzines.com/zines/intege...
How Integers and Floats Work, by Julia Evans - Cartoon of a smiling person in a purple diving suit looking at friendly fish and numbers underwater.
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Meredith Whittaker @meredithmeredith.bsky.social · 22/10/2024
New Paper! w/@HeidyKhlaaf + @sarahbmyers. We put the narrative on AI risks & nat'l security under a microscope, finding that the focus on hypothetical AI bioweapons is warping policy and ignoring the real & serious harms of current AI use in surveillance, targeting, etc. 1/
Mind the Gap: Foundation Models and the Covert Proliferation of Military Intelligence, Surveillance, and Targeting
Heidy Khlaaf, Sarah Myers West, Meredith Whittaker
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Discussions regarding the dual use of foundation models and the risks they pose have overwhelmingly focused on a narrow set of use cases and national security directives-in particular, how AI may enable the efficient construction of a class of systems referred to as CBRN: chemical, biological, radiological and nuclear weapons. The overwhelming focus on these hypothetical and narrow themes has occluded a much-needed conversation regarding present uses of AI for military systems, specifically ISTAR: intelligence, surveillance, target acquisition, and reconnaissance. These are the uses most grounded in actual deployments of AI that pose life-or-death stakes for civilians, where misuses and failures pose geopolitical consequences and military escalations. This is particularly underscored by novel proliferation risks specific to the widespread availability of commercial models and the lack of effective approaches that reliably prevent them from contributing to ISTAR capabilities.
In this paper, we outline the significant national security concerns emanating from current and envisioned uses of commercial foundation models outside of CBRN contexts, and critique the narrowing of the policy debate that has resulted from a CBRN focus (e.g. compute thresholds, model weight release). We demonstrate that the inability to prevent personally identifiable information from contributing to ISTAR capabilities within commercial foundation models may lead to the use and proliferation of military AI technologies by adversaries. We also show how the usage of foundation models within military settings inherently expands the attack vectors of military systems and the defense infrastructures they interface with. We conclude that in order to secure military systems and limit the proliferation of AI
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David Pfau @davidpfau.com · 21/10/2024
I'm starting a research nonprofit dedicated to understanding and addressing the potential wellbeing and moral patienthood of the people living on the other side of mirrors, lakes and other reflective surfaces. eleosai.org
eleosai.org
Eleos AI
Eleos AI Research is a nonprofit organization dedicated to understanding and addressing the potential wellbeing and moral patienthood of AI systems.
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David Pfau @davidpfau.com · 23/10/2024
My phone just autocorrected "singularitarians" to "singular Italians" and I think this is a massive improvement.
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Anselm Levskaya @levskaya.bsky.social · 23/09/2024
Yeah but common people can’t use any of that stuff. GenAI is accessible to the public.
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Anselm Levskaya @levskaya.bsky.social · 15/09/2024
(aside: it's great to see ML people beginning to show up here.)
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Anselm Levskaya @levskaya.bsky.social · 13/09/2024
The boosters of AI safety bills like SB1047 claim that open models will enable the production of biological weapons. These claims are delusional. As a synthetic biologist and LLM engineer, I felt compelled to write why for anyone who might care: dreamofmachin.es/machine_prop...
dreamofmachin.es
The backers of California’s SB1047 routinely cite AI-enabled bioweapons as a threat justifying the radical regulatory regime that places a locus of liability on general computational models, rather than on particular dangerous applications or criminal acts.
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