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Most cited
Posts that commenters keep linking to, ranked by how many different people have cited them in Hacker News comments. 1,015 posts.
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Project Vend: Phase Two
How Claude turned around its failing vending machine business
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Facebook to open-source AI hardware design
Visit the post for more.
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Understanding Convolutional Neural Networks
An interactive visualization system designed to help non-experts learn about Convolutional Neural Networks (CNNs).
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Windsurf SWE-1: Our First Frontier Models
Introducing our first Frontier Models!
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The Components of Agent Memory
For Claude to learn from experience, it has to decide what’s worth remembering before it knows what’s next. Here’s how “dreaming” helps it organize memory and correct mistakes.
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Brain Uses Quantum Effects, New Study Finds [video]
Science News, Physics, Science, Philosophy, Philosophy of Science
938
A comparison to Waymo’s auto liability insurance claims at 25M miles
Understanding the safety impact of Automated Driving Systems (ADS) is crucial for their widespread adoption, yet robust real-world evaluation remains a critical area of development. By leveraging insurance industry third-party auto liability claims, we analyze the Waymo ADS performance across 25.3 million fully…
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Towards a conversational agent that can chat about anything
Posted by Daniel Adiwardana, Senior Research Engineer, and Thang Luong, Senior Research Scientist, Google Research, Brain Team Modern conversatio...
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Training a Neural Net to Generate CSS
A log of experiments done on the site design, intended to render pages more readable, focusing on the challenge of testing a static site, page width, fonts, plugins, and effects of advertising.
941
Revenge of the Chickenized Reverse-Centaurs
In AI circles, a “centaur” describes a certain kind of machine/human collaboration, in which “decision-support” systems (which the field loves to call “AI”s) are paired with human beings for results that draw upon the strengths of each, such as when a human chess master and a chess-playing computer program collaborate…
942
Agents that imagine and plan
Imagining the consequences of your actions before you take them is a powerful tool of human cognition. When placing a glass on the edge of a table, for example, we will likely pause to consider how stable it is and whether it might fall. On the basis of that imagined consequence we might readjust the glass to prevent…
943
Neural Networks Are Essentially Polynomial Regression (2018)
You may be interested in my new arXiv paper, joint work with Xi Cheng, an undergraduate at UC Davis (now heading to Cornell for grad school); Bohdan Khomtchouk, a post doc in biology at Stanford; a…
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Spinning Up in Deep RL
Stay up to speed on the rapid advancement of AI technology and the benefits it offers to humanity.
945
The AI Industry Is Lying to You
Hi! If you like this piece and want to support my independent reporting and analysis, why not subscribe to my premium newsletter? It’s $70 a year, or $7 a month, and in return you get a weekly newsletter that’s usually anywhere from 5000 to 18,000 words, including
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Fixing Gemma Bugs
Unsloth fixing Google's open-source language model Gemma.
947
How much Anthropic and Cursor spend on Amazon Web Services
So, I originally planned for this to be on my premium newsletter, but decided it was better to publish on my free one so that you could all enjoy it. If you liked it, please consider subscribing to support my work. Here’s $10 off the first year of annual.
948
GPT-4 Turbo with Vision is a step backwards for coding
OpenAI’s GPT-4 Turbo with Vision model scores worse on aider’s code editing benchmarks than all the previous GPT-4 models. In particular, it seems much more prone to “lazy coding” than the existing GPT-4 Turbo “preview” models.
949
Open-sourcing circuit tracing tools
Our open-source tools generate attribution graphs showing how language models reach decisions.
950
Fooling around with encrypted reasoning blobs
Update August 11, 2026: A group of researchers from all over Europe were inspired by this post, and actually turned it into a real working attack! Check out their writeup and paper here. This is a …
951
Letting neural networks be weird
Machine learning algorithms are not like other computer programs. In the usual sort of programming, a human programmer tells the computer exactly what to do. In machine learning, the human programmer merely gives the algorithm the problem to be solved, and through trial-and-error the algorithm has to figure out how to…
952
Machine Learning Cheat Sheet (for scikit-learn)
As you hopefully have heard, we at scikit-learn are doing a user survey (which is still open by the way). One of the requests there was t...
953
Reformer, the Efficient Transformer
Posted by Nikita Kitaev, Student Researcher, UC Berkeley and Łukasz Kaiser, Research Scientist, Google Research Understanding sequential data — s...
954
Training GPT-2 to Play Chess
Almost 25 years after Kasparov vs. Deep Blue, another seminal man vs. machine matchup: Neither competitor has much to be proud of here. White has a poor opening. Black screws up and loses his queen…
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Emergent abilities of large language models
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Improving mathematical reasoning with process supervision
We’ve trained a model to achieve a new state-of-the-art in mathematical problem solving by rewarding each correct step of reasoning (“process supervision”) instead of simply rewarding the correct final answer (“outcome supervision”). In addition to boosting performance relative to outcome supervision, process…
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AI solves Advent of Code 2022
I will try to solve all of the advent of code with as little human input as possible
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