The hottest Randomness Substack posts right now

An online test, the Aaronson Oracle, can predict keystrokes with surprising accuracy.
Generating true randomness is more challenging than it seems.
There are creative techniques and methods to mentally create randomness.

Thundering Herd Problem can overwhelm a server when multiple clients retry requests simultaneously.
Exponential Backoff introduces delays between retries to give servers breathing space and time to recover.
Adding randomness (Jitter) to retry intervals helps distribute retries and avoid coinciding, easing the server load.

The allegory in the post highlights the importance of accepting dissenting opinions for societal growth and decision-making
Machine learning techniques that introduce randomness can lead to more freedom and subversion within regimes
Taboos and conformity can be tools used by the illegitimate against the legitimate, but confronting these can inspire hope for Western dissidents

Metaphors are powerful tools we use to explain complex phenomena by comparing them to more familiar things. Comparisons help bridge our understanding of difficult concepts.
Interpreting art and literature involves uncovering the deeper meanings hidden below the surface. Sometimes, the pursuit of meaning where none exists can lead to misinterpretation.
Randomness was not always accepted as a concept. The shift to valuing randomization, like in randomised controlled trials, required a departure from attributing meanings to random events and a move towards empirical understanding.

Creativity involves connecting randomness and finding harmony in unexpected patterns.
Javascript game engines use player actions to create generative experiences in creative coding.
Very low frequencies in Earth's natural radio noise are used for cryptographic protocols and generative arts.

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Random numbers are important in computer science for things like cryptography, simulations, and game mechanics. They help create unpredictability and realism in these applications.
There are two main types of random number generators: True Random Number Generators (TRNGs) that use real-world entropy, and Pseudo Random Number Generators (PRNGs) that produce predictable outcomes based on a starting value.
Algorithms like Linear Congruential Generators (LCGs) and Mersenne Twister are commonly used for generating pseudo-random numbers in various applications due to their efficiency and quality.

When faced with challenges involving prime numbers, clever algorithms can help quickly eliminate composite numbers and pinpoint the secret numbers.
The difficulty of a problem depends on the randomness of number selection within a matrix and the position of prime numbers.
Designing a fair random number generation system is crucial for ensuring transparency, not only in intellectual competitions but also in traditional gambling industries.