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Amazon Science
@AmazonScience
12h
Amazon Bio Discovery developed three AI approaches to accelerate antibody drug design: MochiBind (sequence-based affinity ranking), CA-MAP (developability prediction with batch effect correction), and an agent-guided design system with 46 lab-validated hits against a novel cancer
Advancing AI for biology: Teaching models to design and characterize antibodies
From amazon.science
Amazon Science
@AmazonScience
Sep 10
Years of iterating against the same benchmarks should, by textbook logic, produce overfitting. It largely doesn't. New research explains why: strategies that generalize can be expressed in too compact a form to allow memorization, while the ones that overfit don't survive a
Why don’t machine learning research agents overfit?
From amazon.science
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Amazon Science
@AmazonScience
Sep 4
.@amazon and @DARPA brought together 150+ researchers in Seattle last week, with speakers including @awscloud CEO @mattsgarman, Fields Medalist @TaoistTerence, @EPrinceton Associate Professor @BorisHanin, and @NSAGov's Michael O'Hara to explore how AI is transforming mathematical
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Amazon Science
@AmazonScience
Sep 2
Amazon Redshift researchers were awarded Best Paper Runner-Up: Industrial Track at @VLDBconf for eliminating compilation cold starts in query execution – cutting compilation time from seconds to milliseconds with a 7x speedup on TPC-DS benchmarks. #VLDB2026
FastCompose: Eliminating compilation cold starts in query execution with composition
From amazon.science
Amazon Science
@AmazonScience
Aug 31
Verus is an open-source, automated program verifier for Rust that mechanically checks code against a formal mathematical specification for all possible inputs. Amazon used it to prove correctness of Nitro Isolation Engine primitives.
Developing provably correct Rust code with Verus
From amazon.science
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