Thursday, October 15, 2026

CS & research

The research items ranged across biology, timekeeping and cryptanalysis. The common thread is automation, with AI-designed enzymes and arguments over how well AI will do cryptanalysis.

What happened

• Scientists rewarmed pig kidneys cooled to -150 °C and stored for months, and the organs function again. It is a first, and the researchers hope to replicate it in humans. MIT Technology Review ↗

• Researchers used AI protein design tools to create enzymes that cleave bonds that are stable for centuries. Ars Technica ↗

• Time standards bodies will vote on a proposal that lets UTC drift from Earth's rotation, which would avoid future leap second adjustments. The Register ↗

• Schneier says he is more optimistic than Matthew Green that AI will outperform humans at cryptanalysis. He cites cryptographers' tendency to over-engineer. Schneier on Security ↗

• A survey taxonomy covers combining post-quantum cryptography with quantum key distribution, including constructions, proofs, standards and deployments. arXiv cs.CR (Cryptography & Security) ↗

Articles the model saw · 9

• Pig kidneys that were “frozen” for a year have been brought back to life4

  Scientists rewarmed pig kidneys cooled to -150 °C and stored for months, showing they function again, a first that they hope to replicate in humans.

  MIT Technology Review4 h agobiotechcryopreservationresearch

  Feed excerpt

  Pig kidneys that were cooled to -150 °C and stored in a freezer for months have been successfully rewarmed and shown to work again for the first time, say scientists. They hope to replicate the findings with human organs. The kidneys—which are similar in size to human ones—were left in a glass-like state, in one…

• Researchers use AI to design proteins that cut up other proteins3

  Researchers used AI protein design tools to create enzymes that cleave bonds stable for centuries.

  Ars Technica20 h agoprotein-designaibiology

  Feed excerpt

  AI design tools make proteins that break bonds that are stable for hundreds of years.

• Leap seconds face judgment day as time lords prepare to vote3

  Time standards bodies will vote on a proposal letting UTC drift from Earth's rotation, avoiding future leap second adjustments.

  The Register21 h agotimeutcleap-second

  Feed excerpt

  Proposal would let UTC drift an hour from Earth's rotation, sparing computer systems awkward adjustments for centuries

• The Future of AI Cryptanalysis3

  Schneier argues he is more optimistic than Matthew Green about AI systems outperforming humans at cryptanalysis, citing cryptographers' over-engineering.

  Schneier on Security23 h agocryptographyaicryptanalysis

  Feed excerpt

  Matthew Green has been writing a rather pessimistic series of posts about the potential for AI systems to vastly outperform humans in cryptanalysis of both symmetric and public-key ciphers. I am more optimistic than he is. That is, I have stronger faith in the over-engineering cryptographers tend to do. I am trying to write this up in more detail.

• ArenaAllocators don't play nicely with ArrayLists2

  A Lobsters discussion covers how arena allocators interact poorly with ArrayList-style growable containers in systems programming.

  Lobsters4 h agomemoryprogrammingallocators

  Feed excerpt

  Comments

• An Emulator Writer's HOWTO for Static Binary Translation2

  A technical guide explains how emulator authors can approach static binary translation for executing code ahead of time.

  Lobsters8 h agoemulationcompilershowto

  Feed excerpt

  Comments

• Combining Post-Quantum Cryptography and Quantum Key Distribution: Taxonomy, Constructions, Proofs, Standards, Deployments and Open Problems2

  A survey taxonomy of combining post-quantum cryptography with quantum key distribution, covering constructions, proofs, standards, and deployments.

  arXiv cs.CR (Cryptography & Security)9 h agopost-quantumqkdsurvey

  Feed excerpt

  arXiv:2610.19039v1 Announce Type: new Abstract: Post-quantum cryptography (PQC) and quantum key distribution (QKD) address the quantum threat from opposite directions: PQC replaces vulnerable public-key algorithms with schemes believed to resist quantum cryptanalysis, while QKD derives keys whose secrecy rests on physical assumptions rather than computational ones. Because each approach has a distinct failure mode, a growing body of work combines them so that a session key remains secure if either component holds. We first establish the deployed baseline, hybrid classical-plus-PQC key exchange, against which QKD-augmented designs must be judged. We then propose a taxonomy of hybrid PQC-QKD designs along eight dimensions (integration layer, combiner construction, authentication scope and source, QKD topology, trusted entities, key-delivery interface, classical component, and evidence type), and use it to compare published protocols, including Muckle and its successors, MACsec and TLS integrations, and IKEv2 mechanisms standardised in RFCs 8784, 9370, and 9867. We examine key-combiner constructions in light of the KEM-combiner literature and of NIST, ETSI, and ITU-T guidance, and map…

• AutoPoly-HE: Autonomous Design of Polynomial Activations for Privacy-Preserving Encrypted Inference2

  AutoPoly-HE automatically designs dataset-specific polynomial activation functions to enable homomorphic encryption-based private neural network inference.

  arXiv cs.CR (Cryptography & Security)9 h agohomomorphic-encryptionprivacyresearch

  Feed excerpt

  arXiv:2610.19325v1 Announce Type: new Abstract: Privacy-preserving machine learning has become critical for deploying artificial intelligence in sensitive domains such as healthcare, finance, and infrastructure monitoring. Homomorphic encryption (HE) enables secure inference on encrypted data. Despite its advantages, HE is not compatible with nonlinear activation functions found in machine learning models. Existing methods mitigate this problem by manually designing polynomial approximations for these activation functions. However, these functions do not account for the differences in dataset characteristics or model architecture. Furthermore, these functions are also limited to the accuracies of convolutional neural network (CNN) models. In this work, we propose an autonomous framework that selects polynomial activation functions tailored to each dataset and model. Using this framework, we analyze the interdependence between polynomial activation design and model architecture by evaluating several CNN ResNet and Vision Transformer models across multiple datasets. Experimental results demonstrate that the proposed framework generalizes across multiple architectures, including ResNe…

• A Graph-Based Analysis of Comparability, Scale, and Attribution in Private Transformer Inference2

  Systematizes 62 private Transformer inference systems into an empirical graph to analyze comparability and evaluation consistency.

  arXiv cs.CR (Cryptography & Security)9 h agoprivacytransformerssurvey

  Feed excerpt

  arXiv:2610.19607v1 Announce Type: new Abstract: Rising privacy concerns around large language models have accelerated research in private Transformer inference (PTI). Synthesizing the empirical claims in this line of research, however, is hindered by multi-dimensional cryptographic progress and inconsistent evaluation contracts. In this work, we systematize the field by constructing an empirical graph of 62 PTI systems, mapping system attributes to node features and evaluation compatibility to edges. A three-tiered analysis of this graph illuminates the state of private inference. Node-level attribution shows that cryptographic progress drives performance gains across most systems, yet always co-occurs with other factors (model fidelity, hardware, cost accounting). Edge-level auditing shows that only 1 of 1891 candidate system pairs is directly comparable under shared assumptions. Finally, graph-level analysis shows that the scaling frontier of private inference has plateaued at 13B parameters and projects the cost of deploying current PTI techniques on production-scale Transformers. Overall, this graph-based framework equips the community to evaluate PTI claims transparently and c…