@anshulkundaje I know a guy who figured out how to generate the structures dataset without crystals. So, there will be much larger datasets in a bit of time
@SashaGusevPosts will be a lot of this. probably need a way for centralized domain expertise to reach out to the datasets and pick at them live as like a service
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Update on Erdős Problem 1196:
In joint work, we refined and adapted the proof method from GPT-5.4 Pro to give proofs of several additional problems. This includes another 60 year old conjecture by Erdős, Sárközy, and Szemerédi.
A proof is valued not just by the problem it solves, but by what new avenues it opens up. This is perhaps one of the first examples of an AI-generated proof having downstream impacts, which we are still exploring.
We are announcing the result today at the Future of Mathematics Symposium (see links below)
@bazarovturg also, we rip apart how the standard software works because we need to optimize for correctness in our services. often you dig in and find missing knobs or broken / complex code
We wrote our own hyper-efficient version of the STAR aligner.
Typically it costs around $35 in cloud compute to process 30k cells with Cell Ranger. Ours costs so little that we don't charge for it. Also ours works with nanopore.
If you prefer pseudoalignments, then you can run it in pseudoalignment mode -- obviously we don't charge for that too.
All results instantly integrated with our other tools. As soon as a run finishes you can open alignments or expression matrices in our viewers without moving anything.
Let me know if you want to try it!