When I started to programme in 2022, a common (and correct) advice was to “get your hands dirty”. Start by making simple things happen (doesn’t matter what). The only way to “get” programming was to try to make simple things work, understand (viscerally) how the tiniest typos or logic errors can derail the project, and take things from there. This is no doubt still true to some extent. Someone who hasn’t wrangled with the terminal and/or setting up an IDE arguably doesn’t “get” programming at all....
There is no operating system for people
An operating system is how a computer works. So one might be tempted to speak of an “operating system” for a segment of the community (e.g. the legal world) or for an individual (e.g. what makes someone “tick”). But such metaphors are not just shallow, but misleading. Comparing astrology with statistics does an injustice to how poetic omens are, and also how logical, rigorous, counter-intuitive, and surprising statistics often is....
Skimming Differentiable Logic Cellular Automata with ChatGPT voice
The paper Differentiable Logic Cellular Automata popped up on my Hacker News feed tonight. It immediately attracted my attention due to my interest in the Game of Life. The paper begins with an immediately captivating demo showing how the Google logo can be generated in a Game-of-Life fashion, i.e. by the use of simple rules that one would not ordinarily expect to lead to sophisticated patterns. The claim seems to be that, given (say) an image, neural networks can somehow learn what Game-of-Life style rules are necessary to generate such an image....
Kevin Zhou’s Sam Altman
It speaks to China’s AI prowess that the first biography of Sam Altman with access to the subject is this Chinese-language text. The book is divided into three parts. Part 1 traces Altman’s journey as a Silicon Valley founder to the early years of OpenAI. What struck me the most was how closely Altman was integrated into the Silicon Valley ecosystem. Altman first made his name by founding a startup called Loopt, where he partnered with a technical co-founder to create a business to share their location with friends....
Programming, Computer Science, IT: three interconnected threads
On a conceptual level, the three are entirely separate activities. Programming is giving computers instructions to achieve a certain task, line-by-line, within a particular language. Generally, a single typo or mistake would crash the programme. Computer science (“CS”) is the more abstract, often mathematical, study of various issues arising out of computers. E.g. what is computable; how much time or memory do algorithms take; how electric circuits or distributed systems work etc....
DeepSeek Coder, no code programming, and the programmer as the product
One project within contemporary AI is to enable everyone to programme with nothing other than English prose. DeepSeek comes close to achieving this goal. This is how far I got with roughly 2 hours of DeepSeek Coder. For background, I only have a basic grasp of the broad web development landscape, and only one prior project with the technology involved (Python Flask). My first 8 prompts were as follows:...
3Blue1Brown’s Neural Networks (videos 1-4)
Data structure: a (very) long list of numbers defining a line It is possible to speculate how a neural network stores information/meaning. One can think of information as being stored on a line with a direction in a very high-dimensional co-ordinate system (i.e. “vector”). Using a 3-D graph as a visual example, perhaps an arrow in a certain direction measures how “sports-related” something is. From an origin, 1-D graph (line) is defined by 1 number, 2-D graph by 2 numbers, 3-D graph with 3 numbers....
Gregory Zuckerman the Man Who Solved the Market
In his Art of Doing Science and Engineering, Hamming warns of the difficulty of obtaining reliable data: in his experience, despite all assurances given, there were always significant errors in collection (above and beyond ordinary noise) in the datasets he encountered. One example he gave was an important accounting rules change, which (he says) affects the correct interpretation of the balance sheet for a large portion of major American companies at the time....
Notes on interactive Lean tutorials
After reading Terence Tao’s article on how proof checkers can allow non-mathematicians to contribute to cutting-edge maths, I decided to give interactive LEAN games a spin. I started with the Lean 4 version of Natural Number World and then moved to Lean intro to logic. A few notes for fellow beginners: The instructions are incomplete, likely because the materials were designed to accompany an Imperial College maths course. It is therefore useful to look at the answers within the source code, rather than struggle on....
Marcus du Sautoy Around the World in 80 Games
The text reads very fluently and makes me want to order all the books by Marcus du Sautoy. I didn’t realise that Mahjong was like Rummy and Poker in that it is a trick-taking game. After reading that, something clicked and I could finally see what it’s all about. The idea of Markov chain appeared a few times as the best way to model games, e.g. Monopoly. The core of it seems to be that the probability of something happening depends only on the current state, not on the previous states, cf visual explanation here....