Published on: 2025-06-18 17:03:00
The remarkable story of Bill Benter and how he amassed a staggering $1B fortune betting on horses in Hong Kong has been extensively documented in the article, The Gambler Who Cracked the Horse-Racing Code. In 1994, Benter published an academic paper titled Computer Based Horse Race Handicapping and Wagering Systems: A Report. In it, he documents the implementation of a successful horse race betting model, which by virtue of it being published, likely meant that the model was outdated and superce
Keywords: estimate model probability public races
Find related items on AmazonPublished on: 2025-06-20 04:03:00
The remarkable story of Bill Benter and how he amassed a staggering $1B fortune betting on horses in Hong Kong has been extensively documented in the article, The Gambler Who Cracked the Horse-Racing Code. In 1994, Benter published an academic paper titled Computer Based Horse Race Handicapping and Wagering Systems: A Report. In it, he documents the implementation of a successful horse race betting model, which by virtue of it being published, likely meant that the model was outdated and superce
Keywords: estimate model probability public races
Find related items on AmazonPublished on: 2025-06-20 14:03:00
The remarkable story of Bill Benter and how he amassed a staggering $1B fortune betting on horses in Hong Kong has been extensively documented in the article, The Gambler Who Cracked the Horse-Racing Code. In 1994, Benter published an academic paper titled Computer Based Horse Race Handicapping and Wagering Systems: A Report. In it, he documents the implementation of a successful horse race betting model, which by virtue of it being published, likely meant that the model was outdated and superce
Keywords: estimate model probability public races
Find related items on AmazonPublished on: 2025-07-25 20:11:33
Sherman Kent was rattled. It was March 1951 and Kent, a CIA analyst, had found himself in a troubling conversation about some recent intelligence. A few days earlier, Kent's team had released a report titled ‘Probability of an Invasion of Yugoslavia in 1951’, which concluded that Soviet aggression against Yugoslavia ‘should be considered a serious possibility’. Kent thought the phrase was clear. But when he ran into the chairman of the Policy Planning Staff, he realised his message hadn’t lande
Keywords: estimate intelligence kent like probability
Find related items on AmazonPublished on: 2025-07-27 05:26:28
Dummy's Guide to Modern LLM Sampling Intro Knowledge Large Language Models (LLMs) work by taking a piece of text (e.g. user prompt) and calculating the next word. In more technical terms, tokens. LLMs have a vocabulary, or a dictionary, of valid tokens, and will reference those in training and inference (the process of generating text). More on that below. You need to understand why we use tokens (sub-words) instead of words or letters first. But first, a short glossary of some technical terms
Keywords: logits probability threshold token tokens
Find related items on AmazonPublished on: 2025-08-07 17:43:50
The picture of electrons "orbiting" the nucleus like planets around the sun remains an enduring one, not only in popular images of the atom but also in the minds of many of us who know better. The proposal, first made in 1913, that the centrifugal force of the revolving electron just exactly balances the attractive force of the nucleus (in analogy with the centrifugal force of the moon in its orbit exactly counteracting the pull of the Earth's gravity) is a nice picture, but is simply untenable.
Keywords: atom electron energy nucleus probability
Find related items on AmazonPublished on: 2025-08-25 18:01:46
This article was ported from my old Wordpress blog here, If you see any issues with the rendering or layout, please send me an email I have a little secret: I don’t like the terminology, notation, and style of writing in statistics. I find it unnecessarily complicated. This shows up when trying to read about Markov Chain Monte Carlo methods. Take, for example, the abstract to the Markov Chain Monte Carlo article in the Encyclopedia of Biostatistics. Markov chain Monte Carlo (MCMC) is a techniq
Keywords: distribution markov probability random walk
Find related items on AmazonPublished on: 2025-08-29 22:48:48
April 12, 2025 at 06:54 Tags Math , Machine Learning Cross-entropy is widely used in modern ML to compute the loss for classification tasks. This post is a brief overview of the math behind it and a related concept called Kullback-Leibler (KL) divergence. Information content of a single random event We'll start with a single event (E) that has probability p. The information content (or "degree of surprise") of this event occurring is defined as: \[I(E) = \log_2 \left (\frac{1}{p} \right )\] Th
Keywords: cross entropy kl log_2 probability
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