Eva Alderman

sparklepony @superbioai

[Eva Alderman @AldermanEva]

@Noahpinion The problem is we don’t even know what data to collect / do not have the tools to collect it. Wet lab innovation will be necessary to even get the data. After that, *maybe* bitter lesson applies.

[Eva Alderman @AldermanEva]

@hassantsyed No vesting cliffs + secondaries

[Eva Alderman @AldermanEva]

@itsumeshk LMAO

[Crémieux @cremieuxrecueil]

Amazing.

These researchers found that there's a spike in Bitcoin activity around the time foreign aid money goes out.

Somewhere between 2 and 6 cents of every dollar of World Bank foreign aid disbursements got siphoned off into crypto wallets:

[Eva Alderman @AldermanEva]

@nlarusstone Gives power to omit/selectively include synthetic structures from future training datasets

[Eva Alderman @AldermanEva]

@anothercohen Did the kids ever get picked up though 😂

[David Bellamy @DavidRBellamy]

Could an LLM propose a viral genome to synthesize? Sure. Could it be synthesize-able? Sure. Could it be infectious? Sure, it could just be a replica or a slight modification of a viral genome we already know.

This really isn't the bottleneck to creating dangerous viruses. The bottleneck is in the physical process of synthesizing a virus and the equipment/goods needed to do so.

[Eva Alderman @AldermanEva]

@beffjezos lmfao

[Akshat Khandelwal @akshatk7]

Two years at DoorDash. I do not say this lightly.

We are extremely close to the burrito arriving before you decide you want it.

We are not asking for a ban. We are asking for a pause.

[Eva Alderman @AldermanEva]

@jlsteenwyk Godspeed @jlsteenwyk - they are lucky to have you!

[Eva Alderman @AldermanEva]

@aaronw3r @RuxandraTeslo Makes sense! What’s your favorite (public) method?

[Eva Alderman @AldermanEva]

@ArtirKel @RetroBio_ @z_chiang Project name? 😉

[Eva Alderman @AldermanEva]

@aaronw3r @RuxandraTeslo Don’t think she’s saying AI tools like NetMHC didn’t play a role, just that ChatGPT didn’t hypothesize, plan, and execute design independently — as was implied

[Ankit Gupta @agupta]

This one is tricky. A 6 year old received a base editor that unfortunately caused an immune reaction and she passed away. It was a similar procedure to other ones that worked but it didn’t in this case. Undoubtedly a tragedy. Unacceptably, the trial authors never reported it publicly.

A lot of people are piling on about this, claiming China’s trial environment is unsafe or not trustworthy.

I think we need to careful about what part of this we are critiquing. Every death is a tragedy, but waiting for every single thing to be perfect and having too narrow a window of failure also means many people die waiting for a cure. I don’t claim to have perfect ethics here, but “China allowed for an unsafe trial” seems like the wrong take.

What’s definitely true is it’s very bad this wasn’t reported. That needs to change.

But if we want to bring more cures to people, and especially if we want to those to happen at a lower cost, we have to be very careful to not use instances like this to set excessively high standards for what we put in people. Excessive caution is also deadly.

[JUNDE WU @JundeMorsenWu]

I’m an AI PhD at Oxford wanted to move to the US for years, but it never worked out. Maybe I can share why.

To me, it feels like the US is making it harder and harder for Chinese talent to come or stay.

First, Trump signed PP10043, which meant I couldn’t go to the US for any graduate school. That’s why I had to turn down my Stanford offer and come to Oxford.

Later, I qualified for an EB-1A (the extraordinary ability green card). But because I was born in China, I’m stuck in a country-specific backlog that could take another 4–5 years.

Meanwhile, on the other side, I’m getting 3–4 emails from China almost every week. They offer high salaries, free housing, generous research funding, and even offered an astonishing amount of money just for me to come back and have a conversation.

I’ve always loved the American spirit. I truly believe my abilities could have a bigger impact there. But honestly, the whole process has been incredibly frustrating.

All of this makes me wonder whether I should just give up.

Why am I spending so much energy trying to go to a country that doesn’t seem to want me, when another country is doing everything it can to bring me back?

[Eva Alderman @AldermanEva]

@catehall Tretinoin and topical GHK-Cu are very real

[Maziyar PANAHI @MaziyarPanahi]

🚨 Over 1 billion rows of psychiatric genetics data. Now on Hugging Face.

ADHD. Depression. Schizophrenia. Bipolar. PTSD. OCD. Autism. Anxiety. Tourette. Eating disorders.

12 disorder groups. 52 publications. Every GWAS summary statistic from the Psychiatric Genomics Consortium.

Before: wget, gunzip, 20 minutes debugging separators, repeat 50 times.
Now: one line of Python.

[Anthropic @AnthropicAI]

New Anthropic research: Emotion concepts and their function in a large language model.

All LLMs sometimes act like they have emotions. But why? We found internal representations of emotion concepts that can drive Claude’s behavior, sometimes in surprising ways.

[Eva Alderman @AldermanEva]

@dr_alphalyrae It was the best of times, it was the worst of times.

[Niko McCarty. @NikoMcCarty]

I think this is one of the most important articles we've published at @AsimovPress. If you read carefully, there are at least 3-4 ideas in here that *should* be large, well-funded research programs.

The article begins by arguing that existing AI models are good at predicting things *within* an existing framework, but are not good at building new frameworks (and, thus, cannot do paradigm-shifting science). As AI models become more widespread in science, they therefore risk "hypernormal science," meaning we will have less actual breakthroughs and more incremental discoveries.

The author (Alvin Djajadikerta) supports this argument with several examples, one of which comes from germ theory:

"In the mid-nineteenth century, doctors thought that illness was caused by noxious air, and kept meticulous records accordingly. The physician William Farr mapped cholera deaths across London and found they correlated strongly with low elevation, which he thought was because noxious vapors accumulated in low-lying areas. He was actually picking up a real signal: low-lying districts were closer to the contaminated Thames River. But because his data was organized around air quality, he could not find the true cause..."

"An AI trained on Farr’s records could have found even subtler correlations, and would have been genuinely useful for predicting which neighborhoods would be hit hardest in the next outbreak. But it would not be able to derive the concept of a waterborne microorganism, as this was not a variable anyone had yet recorded."

After giving other examples of this, Alvin begins mapping out ideas to solve this problem and create AIs that are "visionary" rather than "merely predictive." My favorite idea, of his, is to use AI agents as a model organism for metascience.

The gist is that many paradigm shifts seem to happen under particular conditions. "Bell Labs, Xerox PARC, and the early Laboratory of Molecular Biology at Cambridge all produced extraordinary concentrations of paradigm-shifting work," Alvin writes, "mostly because they were small groups with enough institutional protection to pursue ideas that looked unproductive by conventional measures."

Alvin continues:

"We have never been able to run controlled experiments on scientific institutions; it is impossible to create labs that differ in only one respect and compare the results. But we could run AI agents in parallel populations under different research conditions, and analyze the results...In this sense, AI scientists may give metascience its first model organism."

"For instance, one could test how group structure shapes discovery: do small, isolated teams produce more conceptual reorganization than large, well-connected ones? Do flat hierarchies outperform rigid ones? One could run AI agent populations that vary these factors independently and measure the results — something that is impractical to do with real institutions..."

This essay is excellent throughout and I hope you'll read it.