Pavle Jeremić

@SynBioMars

Building the post scarcity future

San Francisco, CA

aetherbio.com

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Pavle Jeremić
@SynBioMars
Jul 22, 2025
Some learnings from the last 12 months. At Aether our mission has always been to build a future of abundance for the human race. We plan on doing this by using our AI to design totally new classes of proteins that can assemble complex products in modular factories (more on this
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Pavle Jeremić
@SynBioMars
Aug 6
Biological systems are much more like machines than text, they data that describes them needs to have a lot higher dimensionality
Anshul Kundaje
@anshulkundaje
Aug 5
This is a very poor one line summary of the article by @DaphneKoller IMO. The point is not just data volume. The right kind of data scaled in the right axis with the right experimental designs for well defined tasks + using the models to discover biology (not eval maxxing)
Pavle Jeremić
@SynBioMars
Apr 15
This is incredible
Yuri Shakhov 🇷🇺
@Koroshitelol
Apr 14
This time, I am publishing in full the album authored by TsKBEM in 1969, dedicated to the mock-up article N1-L3 №1M1, built for the comprehensive development of the rocket-space system. 1/16
Pavle Jeremić
@SynBioMars
Apr 9
Co-design is the future! Any effort to design de-novo functions must include both the protein design and the actual molecular function/target in model, awesome work here further validating that strategy
Jarrid Rector-Brooks
@jarridrb
Apr 8
What if AI could invent enzymes that nature hasn’t seen? 👩‍🔬🧑‍🔬 Introducing 🪩 DISCO: Diffusion for Sequence-structure CO-design 14 rounds of directed evolution and over a year of wet lab work. That's what it took to engineer an enzyme for selective C(sp³)–H insertion, one of the
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Pavle Jeremić
@SynBioMars
Apr 6
Protein function models are the future! Requires massive multi-functional datasets to generalize not just to “natural” functions but also to push well beyond what nature evolved.
Prof. Nikolai Slavov
@slavov_n
Apr 6
Progress in AI modeling of proteins leaves major gaps affecting most proteins and especially functional analysis. The opportunities to transcend them beacon: AI models can now predict static protein structures with high accuracy. This achievement is rightly celebrated. It is