randomness

博客讲述了作者在 GitHub Nomic 游戏中试图利用 merge commit 时间戳进行 timing attack 却被 GPG 签名阻止，最终朋友 Chelsea Voss 通过本地生成并推送无签名 merge commit 赢得游戏的故事。

一篇讲述『The Aaronson Oracle』的长文，回溯 1950 年代 Bell Labs 中 David Hagelbarger 的 SEER 与 Claude Shannon 的机器如何通过预测对手模式在匹配硬币等游戏中获胜，并延伸到现代可预测性实验。

Show HN: an interactive web experiment that tests how random users' choices really are, hosted at lab.specr.net's rigged-draw page.

Mathematician Yilin Wang's work on Loewner energy quantifies how far curves deviate from randomness, aiding Citadel in distinguishing true market signals from noise with $500,000 rewards for precise computation.

This article discusses Xorshift generators, a type of fast pseudorandom number generator used in computational applications.

An exploration of why two statistically identical sequences—pure noise and the digits of π—differ in compressibility, distinguishing between statistical redundancy and process-based compression.

QSignAI is a production-deployed open-source platform that combines quantum randomness from a Toeplitz two-source extractor with an AI bot on Telegram to generate unique identity signatures, demonstrating a bidirectional relationship between artificial intelligence and quantum science.

This paper analyzes the variance of FID scores across different training and sampling seeds, revealing significant reproducibility issues in image generation evaluation. It proposes a new evaluation protocol with error bars and per-cell optimal guidance tuning.

A technical blog post exploring randomness, Linux entropy, and building a tool called morerandom that uses WASM plugins to feed the system entropy pool.

Researchers at ETH Zurich have demonstrated a method for generating 'perfect randomness' using entangled superconducting qubits, a breakthrough with implications for cryptography and secure communications.

An article exploring the philosophical and practical meaning of randomness, using lava lamps as a metaphor for entropy generation in computing.

Debunks common myths about /dev/urandom and /dev/random, explaining that /dev/urandom is the preferred source of cryptographic randomness on Unix-like systems.

This paper investigates whether probabilistic calibration in language models can be improved through fine-tuning, comparing soft-target and hard-target methods across 12 models. The results show that calibration is a trainable capability, though gains sometimes reduce downstream arithmetic reasoning capabilities.

The paper introduces Diamond Attention, a method for multi-agent reinforcement learning that uses structured randomness to break symmetry and enable role differentiation among homogeneous agents, achieving perfect coordination in symmetric tasks like the XOR game.