Cross-disciplinary road-mapping and analysis of science and technology topics
Just a fun tidbit. In response to my Dwarkesh podcast appearance, which heavily focused on Steve Byrnes theories of how human social instincts are shaped by the brain, some people asked about beavers. Patrick Mineault asked I m thinking of Justin Beaver (a favorite example of Tony Zador): what would I read off in the pattern of the Continue reading Sketching beaver theories with and based on AI
https://evebio.org dropped a first bit of pharm-ome mapping data today, with 1397 compounds against 19 nuclear receptor targets. This is just a tracer bullet and taste of what is to come. https://data.evebio.org/ I made a little Colab notebook for making a heatmap of the compound versus target activation matrix for agonist mode (you can easily Continue reading First look at first micro-drop of EvE…
The excellent Casey Handmer says you should be working on hardware. I mostly agree. Especially in biology, for example, we’re often limited by the unknown physical configuration of the system. That’s not something that can be solved by reasoning (software) alone. Often you have to deal directly with the physical world, to do what’s important. Continue reading Reusable rockets were partly a “bits”…
The use of AI for predicting how molecules behave has made significant but still narrow progress compared to what is possible — applying AI to directly simulating molecules atom by atom could yield much broader wins Machine learning is making big splashes in biology, chemistry and materials recently, but arguably the big leaps are yet Continue reading Molecular simulations – from niche to…
There are a number of ways we could make the hardest part of biomedicine, namely, safe translation from animal models to humans, more reliable through tooling and public goods oriented projects One of the big problems in drug discovery is the low “predictive validity” of disease models, like mice. Most mouse results don’t translate to Continue reading “The best model organism for humans is humans”
Neuroscience is mostly funded from a health perspective, but its implications are much wider If we can advance neuroscience through new technological modalities that address the brain’s huge dynamic range of scales, the implications are big, and not just for brain diseases. It is worth considering long-term, big picture implications, even if they are highly Continue reading Some big picture…
Generative AI is moving fast, with scaling laws visibly playing out. What will the next few years of deep learning bring us, in terms of real world impact outside of tech/software? I’ve been hearing some bold predictions for disruption. I think about this a lot, since my job is to help the world do beneficial, Continue reading General automation, and science
convergentresearch.org e11.bio cultivarium.org https://www.nature.com/articles/d41586-022-00018-5 https://www.macroscience.org/p/metascience-101-ep4-arpas-fros-and https://www.forbes.com/sites/alexknapp/2023/03/17/why-billionaires-ken-griffin-and-eric-schmidt-are-spending-50-million-on-a-new-kind-of-scientific-research/?sh=7bd83bbb2847…
Epistemic status: initial stab from a non-expert Thanks to Shannon Nangle and Max Schubert for helpful discussions. Summary: There are a variety of potential scenarios where a self-sustaining, biologically isolated Refuge would be needed towards existential risk reduction. Currently, there is very little work going on towards technical common denominators required for all such approaches, Continue…
Note: prepared as a response to this RFI. Response to prompt (b) on Biotemplated Registration capabilities: b1. What are the physical mechanisms underlying your registration approach(es)? Include surface chemistry requirements in your discussion. The proposed approach would achieve sequence-specific addressable chips that can direct unique-sequence DNA origami to specific spots on chip with an…