Angelica Parente

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Angelica Parente

Angelica Parente

@draparente

Building the adjacent possible. Prev: @SHV @Nurix_Tx @StanfordMedX @Stanford @SSBiophysics @vijaypande & Bryant labs. Tweets my own🔬🧬🧫🧠💻

LA 🔄SF 🔄PDX Katılım Ekim 2018
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Angelica Parente
Angelica Parente@draparente·
@tobi I like this idea a lot, I'm using qwen 3.6 35B and sometimes it's a bit over-confident. How often have you seen it ask GPT5.5 for ideas?
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tobi lutke
tobi lutke@tobi·
I’ve had very good results running autoresearch with local qwen 3.6 26b model as long as I had a simple vibed pi “advisor” extension that allowed it to periodically ask GPT 5.5 for ideas. I think this direction has a lot of merit.
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Angelica Parente
Angelica Parente@draparente·
@curiouswavefn Love richard rhodes, didn't know he wrote a book on how to write - have been looking for something like this.
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Angelica Parente
Angelica Parente@draparente·
You have to do a literature search rather than a kosmos run. You can view the result in the web UI, if you click on a reference it will pop up. You can click on references & see the quality labels Edison's assigned. It's been a while since I've used Edison because I ran out of credits, but that feature was one of the things I liked the most about it.
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Fyodor Urnov
Fyodor Urnov@UrnovFyodor·
I prompted the “deep literature” mode of Edison Scientific to write a comprehensive review on the biology of a gene that I know well. Twenty five min later it sent a 17 page PDF. It was, as best as I can tell, flawless. Folks, we are not in Kansas anymore. Don’t at me - try it.
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Angelica Parente
Angelica Parente@draparente·
Guys, this is why companies spend a lot of resources doing rigorous internal testing for protein quality. You cannot trust the claims from vendors, you'll hear plenty of horror stories from people who have been in the industry long enough. Now apply this thinking to grey market peptides.
Sholto David@addictedtoigno1

Surprised to discover that Thermo Fisher appears to show a fake western blot for the validation of one of their p53 antibodies. I've added a diagram to show the very similar bands. This does not appear to be one of the "published figures", but their own internal data.

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Khalia Primer, PhD 🩺🧬
@draparente I literally don't even look at the vendor's figures when buying antibodies/ELISAs/etc because they cannot be trusted. We rely entirely on word of mouth recommendations and in-lab optimisation/validation
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Angelica Parente
Angelica Parente@draparente·
Why is Claude obsessed with using the term “load bearing” now?
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Vega Shah
Vega Shah@dr_alphalyrae·
but seriously has anyone in the bay area figured out how to make net new, non-transactional friendships as an adult?
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Ron Alfa
Ron Alfa@Ronalfa·
@dr_alphalyrae I think the real answer is people will show up to things but feel too busy to organize. So hosting can be a good unlock. I’ve also connected with folks cycling and I guess people with young kids often gather.
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adaption
adaption@adaption_ai·
Introducing AutoScientist. Most model training fails outside of frontier labs. AutoScientist automates the full research loop so it doesn't have to.
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Angelica Parente
Angelica Parente@draparente·
Once you learn about Goodhart’s law you see it everywhere.
Startup Archive@StartupArchive_

Shopify CEO Tobi Lutke explains Goodhart’s law and why he doesn’t like KPIs or OKRs “Goodhart’s law is real. The moment a metric becomes a goal, it’s no longer a useful metric… No metric by itself is a complete heuristic for a complex business. There’s a million different tensions in a company, and you can’t keep all of them in harmony by optimizing for one thing.” For this reason, Shopify doesn’t use KPIs or OKRs. But as Tobi explains, this doesn’t mean they don’t value data and metrics. “We are extremely data informed. We have invested enormous amounts of money and time into systems that give us basically everything at our fingertips… But what Shopify attempts to do is just not over-fit for what’s quantifiable.” People love optimizing for highly-quantifiable things because there’s immediate gratification that comes from seeing a number go up. But Tobi thinks that the most important aspects of a product are rarely quantifiable: “The overlap of the most valuable things you can do with a product and the things that happen to be fully quantifiable are like maybe 20%. Which leaves 80% of a value space unaddressable by the people who only look at quantifiable things.” He continues: “Shopify is comfortable with unquantifiable things like taste, quality, passion, love, hate… The sort of deep satisfaction that a craftsperson feels when they’ve done a job well is actually a better proxy if you allow it to be.” They then have robust analytics systems that tell the company if something’s wrong or a new rollout breaks something. “We think about it as a cockpit for a pilot. The decisions are still made by pilots, and we think this leads to better results… I think there needs to be more acceptance in business of unquantifiable things… And then metrics take a support function.” Source: @lennysan (Feb 2025)

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Angelica Parente
Angelica Parente@draparente·
Decisions are everything in biotech, and this is a great experiment to run. That said, BMS’ decision making around Opdivo is one of the most-written-about case studies on drug development. It is certainly in the training corpus for both models. We need better evals for strategic decision making (something I’ve been thinking about), but hard to do retrospectively without having a training cutoff before an outcome is read out.
Rowland Manthorpe@rowlsmanthorpe

In 2012, two pharma companies faced a defining decision. One chose badly, the other well. If AI can make better decisions than humans, then given the same information it should make the correct choice But it didn't Ingenious experiment by @liangc_science via @adamjkucharski liangchang.substack.com/p/can-ai-make-…

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Angelica Parente retweetledi
Andrew White 🐦‍⬛
Andrew White 🐦‍⬛@andrewwhite01·
hallucinated references will land you a 1-year ban from arxiv now. wow
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Angelica Parente
Angelica Parente@draparente·
@tessafyi What’s even funnier is Kaihang Wang showed me this paper last week and I thought of you. He is hilarious. Highly suggest you meet him.
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Tessa Alexanian
Tessa Alexanian@tessafyi·
me: sure, synthesis screening can't catch tiny fragments, but assembly is annoying labwork, it's not practical to go below a certain size new preprint: 12kb assembly from oligo pools, 2 one-pot steps, accurate enough that synthesis error rates matter me: welp
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