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Push-ups with Python, mediapipe and OpenCV
In the Singapore Army, there is something called IPPT (Individual Physical Proficiency Test). The problem with this test is not how…
Topics /
AI & Machine Learning
The most popular blog posts about ai & machine learning on Hacker News. 6,326 posts.
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PyTorch – Internal Architecture Tour
Update 28 Feb 2019: I added a new blog post with a slide deck containing the presentation I did for PyData Montreal. Introduction Short intro to Python extension objects in C/C++ Zero-copy PyTorch Tensor to Numpy and vice-versa Tensor Storage Shared Memory DLPack: a hope for the Deep Learning frameworks Babel…
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A Cookbook for Machine Learning: Vol 1
This was a busy week, I had no time to read anything new, so I'm sharing a note that I wrote for myself, for no other reason than to understand things better. It's a kind of cookbook of various "transformations" you can apply to...
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AI Police Reports: Year in Review
In 2024, EFF wrote our initial blog about what could go wrong when police let AI write police reports. Since then, the technology has proliferated at a disturbing rate. Why? The most popular generative AI tool for writing police reports is Axon’s Draft One, and Axon also happens to be the largest...
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Mozilla's open source AI strategy
The future of intelligence is being set right now, and the path we’re on leads somewhere I don’t want to go. We’re drifting toward a worl
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Learnings from 100K lines of Rust with AI (2025)
In the past few months, I’ve been stress-testing how far AI coding agents can take us when building real, production-grade distributed systems. The result: a Rust-based multi-Paxos consensus engine that not only implements all the features of Azure’s Replicated State Library (RSL) [1] — which underpins most major…
3428
I Asked ChatGPT to Explain Some Jokes to Me
Explaining a joke is like dissecting a frog. You understand it better but the frog dies in the process.
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If you are good at code review, you will be good at using AI agents
Using AI agents correctly is a process of reviewing code. If you’re good at reviewing code, you’ll be good at using tools like Claude Code, Codex, or the…
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Why AI Infrastructure Startups Are Insanely Hard to Build
Level of difficulty: insane
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Licensing is neither feasible nor effective for addressing AI risks
Non-proliferation only benefits incumbents
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PRC elites voice AI-skepticism
Executive Summary: Rapid advancement in artificial intelligence (AI) has become a point of national pride in the People’s Republic of China (PRC), driven in part by a cohort of accelerationist advisors who view technology as a transformative solution to the country’s economic ills. Lauding it as a “new productive…
3433
Some thoughts about Anthropic's new cryptanalysis results
Yesterday Anthropic published two new cryptanalysis results, both outputs of Claude Mythos, their (still) unreleased advanced model. The first of these results attacks a signature scheme called HAW…
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Building AI products in the probabilistic era
AI turns products from deterministic functions into probabilistic systems. That requires expanding old playbooks (SLOs, funnels, siloed finance), and reasoning in terms of trajectories, Minimum Viable Intelligence thresholds, and data as company operating system.
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Voice Recognition and Text to Speech in Python
It’s tough for an aspiring Iron Man to work on creating their personal AI assistant on the weekends. Like any other time-pressured inventor without a PhD in computer science and linguistics, …
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Break-a-Scene: Extracting Multiple Concepts from a Single Image
A method for extracting multiple concepts from a single image.
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A Ray-Tracing Pioneer Explains How He Stumbled into Global Illumination
NVIDIA RTX Spark powers thin and light laptops built for everything that developers, creators and gamers do. RTX Spark laptops are now available from ASUS, Dell, HP, Lenovo, Microsoft and...
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Interpretable Machine Learning
Machine learning is part of our products, processes, and research. But computers usually don’t explain their predictions , which can cause many problems, ranging from trust issues to undetected bugs. This book is about making machine learning models and their decisions interpretable.
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Machine Learning 101: An Intro to Utilizing Decision Trees
Stay up-to-date with the latest news, practical tips & best practices from Qlik on data analytics, data integration, data literacy, and big data analytics.
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Training NanoGPT on My Journal
Wouldn't it be great to have a pet AI chat bot that knows you really well, and can give you free consulting, coaching and therapy ? What could possibly go wrong if an intelligent corporate-controlled system has unlimited access to your private data to provide you the best possible service? Well... a lot of things.
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Reinforcement learning, explained with a minimum of math and jargon
To create reliable agents, AI companies had to go beyond predicting the next token.
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Meta's Llama 3.1 can recall 42 percent of the first Harry Potter book
New research could have big implications for copyright lawsuits against generative AI.
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Tokenmaxxing is dead, long live tokenmaxxing
Alt title: The reports of tokenmaxxing’s death are greatly exaggerated.
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Detecting and countering misuse of AI: September 2026
Case studies from threat actors disrupted between December 2025 and August 2026 across seven areas of harm, from cyber operations to biological misuse.
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Emotion concepts and their function in a large language model
All modern language models sometimes act like they have emotions. What’s behind these behaviors? Our interpretability team investigates.
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The AI Unbundling
AI is starting to unbundle the final part of the idea propagation value chain: idea creation and substantiation. The impacts will be far-reaching.
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The behavior of LLMs in hiring decisions: Systemic biases in candidate selection
Hints of discrimination and lack of principled reasoning in frontier AI systems
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