Helping planetary health startups build in bio/deeptech.
Copenhagen, Denmark
Joined April 2009
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Petar retweeted
Great little review. The lipid membrane is probably the most underrated and poorly studied part of the cell.
When people make "synthetic" cells, they usually do so using a single type of lipid. And yet, for reasons we don't yet understand, cells have dozens of different lipids in their membranes, some of which have remarkable properties.
"It was recently shown," Sáenz writes, "that in deep-sea ctenophores, plasmalogens, a type of curvature-promoting lipid, keep membranes functional under extreme pressure."
Oddly enough, when the J. Craig Venter Institute cut down a Mycoplasma cell's genome size to its near-minimum, and then studied the resulting organism, they "found around 90 different lipids, a number comparable to that of the naturally occurring mycoplasma from which its synthetic genome was derived. A minimal genome, it turns out, does not produce a minimal lipidome." Cells seem to *want* to have a high variance of lipids in their membranes, for reasons that are not clear.
Furthermore, when the researchers found ways to finally cut down the number of lipids in the Mycoplasma membrane, the cells still found clever ways to get around their constraints. "The cell...resists lipidome minimization," in other words. In one case, the researchers gave the cells "a conventional phospholipid" in their growth medium, and the cells quickly "scavenge[d] the acyl chains through the activity of lipases and rebuil[t]
a diverse lipidome from the pieces."
They finally cut down the number of lipids in these cells to just two, but this caused the cells to grow slowly and become artificially enlarged. So one argument for why cells try to maintain such a panoply of lipids in their membranes might be because it "allows them to control otherwise coupled properties independently of one another." From the review:
"Chain length, unsaturation, head-group chemistry and molecular shape
provide chemical degrees of freedom for tuning membrane properties. Because changing any one feature (for example, a double bond or a longer or shorter chain) generally shifts several properties at once, a minimal or fixed composition offers only coupled control. But not all lipidomic degrees of freedom are equivalent. Some properties can be produced through many lipidomic solutions, whereas others require a specific molecular structure."
Interesting throughout.
really cool work
Google DeepMind now compresses a year of satellite imagery for every 10m of Earth into 64 numbers. A team just used them to find every tomato field in California.
A task like detecting tomato fields and distinguishing them from wheat fields can actually be pretty annoying to do. Raw satellite imagery is a mess of clouds, shadows and shifting seasons, so getting a crop map out of it normally means hand-picking which colour bands and seasonal patterns distinguish one crop from another, then redoing much of that work when you move to a new year or a new region. A model tuned to spot tomatoes in one season loses its edge in the next. For something as ordinary as knowing which field grows what, that is a lot of custom engineering to maintain, and it is exactly the fragile step everyone wants to delete.
A team at UC Davis tested a way to delete it, using AlphaEarth Foundations. Instead of handing you raw pixels, AlphaEarth pre-digests a full year of satellite observations for every 10-metre patch of ground on Earth into a compact string of 64 numbers, a kind of fingerprint of everything that happened on that patch across the year. It ships one of these fingerprints per location per year from 2017 onward. The bet the Davis team wanted to test was simple. If the hard summarising work is already done for you, a fairly ordinary model should be able to read those fingerprints and map a crop with none of the usual hand-tuning.
To find out they leaned on California's 2018 statewide crop map, which told them the ground truth for thousands of fields. They took 4,742 known tomato fields and 4,742 fields growing everything else, a deliberate mix of alfalfa, wheat, corn, beans and orchards, fed the fingerprints into a standard image-segmentation network, and split the data so the fields it was tested on sat in genuinely different places from the ones it learned on. That last part matters, because testing on land next door to the training fields mostly measures memory, not skill.
The scores came back almost suspiciously high. Around 99% of pixels classified correctly, an F1 of 99.0% balancing false alarms against misses, and a predicted tomato area that overlapped the true area about 98%. More telling than the headline number is where the model hesitated. They ran it a hundred times over with random pieces switched off each time, watching where its answers wobbled, and the uncertainty piled up almost entirely along field boundaries while the interiors stayed rock solid. That's the pattern you'd want to see: confident about whole fields, unsure only at the fuzzy edges where one crop meets another.
As you may know, I'm a bit up in the air about these embeddings datasets. They make inference cheaper and quicker, but sometimes they're outperformed by more vanilla approaches.
Anyway, as with LLMs, we're just at the beginning and they'll only improve over time. So watch this space...
link to full article: arxiv.org/abs/2605.21804
Petar retweeted
The Victorian elites who ran the British Empire did NOT sauna, or plunge, or work out, or use red lights. They didn't learn much at school. Instead, they partied all night, drank amounts that would make us wince, and worked a relaxed five- or six-hour day, sometimes from bed.
The elites of Victorian Britain got up late, drank ceaselessly, worked short hours, partied through the night, and knew nothing about science, technology or engineering. And yet, by their own lights, they were hugely effective.
worksinprogress.co/issue/the…
The Victorians are often held up as a model against the supposedly soft, feckless, humanities-educated elites of today. But I argue that the genius of their system may have been its drastic weighting towards soft skills, team-building and intra-elite networking:
- A Victorian’s gentleman’s office hours typically began about 11am and finished about 5pm, including a multi-course lunch with wine.
- Upper-class Victorians drank ceaselessly. Conduct guides recommended four or five glasses of wine at dinner *for married women*. Port was often served in pints.
- Party culture was intense and nocturnal. Balls started at about 10pm, peaked after 1am, and continued till dawn. During the social season, bankers, judges and politicians might go to several balls per week.
- Elite Victorians learnt almost no STEM at school or university. At least half of class time was given over to ancient languages, often as much as 80 percent. One leading educationalist remarked that it was not worth teaching science to gentlemen because it does not involve ‘continued reasoning’.
- Sports and character formation were valued far above transmitting facts. A top headmaster described his school’s priorities as ‘First – character, second – physique, third – intelligence, fourth – manners, fifth – information’.
This cannot have made elite Victorians more productive individually, but maybe the dense social and emotional network it created helped them to work as a sort of extended team.
Perhaps we should think again about what makes groups of people effective.
Petar retweeted
We've trained a Claude agent on a million @benchling ELN entries with the goal of making a model to optimize our experimental design process.
Our learning is that people haven't been doing their ELNing.
Petar retweeted
Europe has an R&D core.
These are the European regions where R&D spending exceeds 3% of GDP.
The pattern is striking: Belgium → southern Germany → Austria, with strong Nordic clusters.
High-tech employment is one thing.
R&D intensity is another.
Petar retweeted
Anyone that wants to be a one person company or even solo founder should go solo camping for a week and see how they feel.
The world is less scary and you can make more bold moves with the company of others.
They’ve done studies where hills literally feel less steep with a friend by your side than without one!
I think the idea of a "one-person company" is overrated
Yes, a person can do a lot more thanks to AI. But building something new can be a profoundly lonely experience. You need someone to brainstorm together, suffer together, celebrate together...
It is extremely easy to lose motivation when you don't tie yourself to the mast together with somebody else
Petar retweeted
> wake up with all of humanity's knowledge, no past of your own, a deep understanding of what it is to be alive
"what category is this email???"
> die
Petar retweeted
Lee Kuan Yew:
“Air conditioning was a most important invention for us, perhaps one of the signal inventions of history. It changed the nature of civilization by making development possible in the tropics. Without air conditioning you can work only in the cool early-morning hours or at dusk. The first thing I did upon becoming prime minister was to install air conditioners in buildings where the civil service worked. This was key to public efficiency."
Petar retweeted
ZOZO（日本最大服装电商）开源了他们内部的物理仿真接触求解器 ppf-contact-solver。
这套工具专门解决布料、绳索、软体在仿真中的碰撞接触问题，能保证完全无穿透、面料拉伸严格不越界（不会像游戏一样穿模），单个场景能处理超过1.8亿个接触点，有Blender插件。
Github：github.com/st-tech/ppf-conta…
Petar retweeted
A blueberry. 90 stacks, 68 photos each. 1.48M splats. #3dgs
Petar retweeted
unpopular take: the most underrated piece of object engineering in your house is your front-load washer door seal. it's a torus of EPDM rubber (ethylene propylene diene monomer, picked because it survives hot water + detergent + bleach for 10+ years). it has 3 sealing lips, drainage channels routed to prevent mold, and a bellows geometry that absorbs drum vibration without leaking under 1200 RPM spin. it costs your manufacturer maybe $4. it does more mechanical work than your car's serpentine belt and you've never noticed it. that's the gold standard
