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  1. Ars Technica · AI75

    Google DeepMind uses AI to mathematically verify key parts of the Signal protocol

    Google DeepMind researchers used AI agents to formally verify multiple key cryptographic guarantees of the Signal protocol, completing the project as a proof of concept within four weeks. This work provides independent verification for encryption used by platforms such as Signal, Google Messages, and WhatsApp, while also demonstrating the formal verification capabilities of the new AI framework AlphaProof Code.

    Same story · 2 outlets

    Why it matters: DeepMind used AI agents to formally verify the Signal protocol, and publicly released the specifications and proofs, providing a basis for evaluating the boundaries of AI-assisted verification.

  1. The Decoder71

    Google AI detects hypertension using a regular smartwatch without a cuff

    Google Research's AI detects signs of hypertension without blood pressure cuff calibration, using only the pulse and motion sensors already in smartwatches, with related research published in Nature. The neural network learns pulse and heartbeat patterns by comparing short segments from nearly 500,000 hours of sensor data to identify which segments belong to the same person, then averages multi-day data to calculate the probability of hypertension.

    Why it matters: Readers can learn about a smartwatch blood pressure detection study that requires no cuff calibration, and its comparison results with traditional measurements in tests on 196 people.

  1. Google Research72

    Google Research uses smartwatch sensors to identify signs of hypertension.

    Google Research published a multimodal AI system AI-PPG-ACC-HTN in Nature, which passively identifies hypertension status without wristband calibration, using only PPG and accelerometer data from consumer-grade smartwatches.

    Same story · 2 outlets

    Why it matters: The study passively identifies hypertension using PPG and accelerometer data from smartwatches, providing quantitative results for screening and confirmation in two stages, with 24-hour dynamic blood pressure monitoring as the gold standard.

  1. ITHome · AI75

    MIT CSAIL proposes weight space programming: GPT-6 Astra modifies Qwen3.5-0.8B's weights by about 0.016%, boosting MATH-500 score to 6 times

    MIT CSAIL researchers propose 'weight space programming', allowing GPT-6 Astra to directly read and modify the neural network weights of Qwen3.5-0.8B, adjusting only about 0.016% (131072 parameters) to increase MATH-500 score from 7.9% to 48.1%, GSM8K from 13.8% to 67.1%, and IFEval from 21.0% to 62.3%.

    Why it matters: The experiment provides a comparison of weight modification ratios with multiple benchmarks before and after, and also outlines the applicable boundaries of this method through control experiments.

  1. Epoch AI88

    Epoch AI: GLM 5.3 can break multiple Firefox versions during the patch window period.

    Epoch AI's experiment shows that the open-source weight model GLM 5.3 released by Z.ai in August can autonomously construct web attacks targeting six Firefox versions released between September 17 and October 26, exploiting publicly available but not yet pushed security fixes, where visiting the web page causes local files to be read and transmitted.

    Why it matters: Epoch AI replicates patch window attacks using open-source weight models, providing a cost level of about 1000 US dollars per version, available for evaluating the security boundaries of open models.

  1. The Decoder71

    Research finds AI helps junior patent attorneys draft faster, but does not enhance their independent review capabilities

    A study funded by Google had patent attorneys use Google Labs' unpublished AI assistant InFlow to draft patent claims, which were then scored by blind-review attorneys from independent law firms across five dimensions: executability, technical accuracy, strategic ambiguity, completeness, and clarity.

    Why it matters: This experiment measured AI-assisted drafting and AI-free review separately, revealing a divergence between immediate efficiency and long-term judgment.

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