Topics /
The most popular blog posts about ai & machine learning on Hacker News. 6,326 posts.
The Google Assistant brings together all of the technology and smarts we've been building for years, from the Knowledge Graph to Natural Language Processing. To be a truly successful Assistant, it should be able to connect users across the apps and services in their lives. This makes enabling an ecosystem where…
Automating the analysis of slides of lung cancer tissue samples increases the accuracy of tumor classification and patient prognoses, according to a new study.
The Case for Bayesian Deep Learning Andrew Gordon Wilson Abstract Bayesian inference is especially compelling for deep neural networks. The key distinguishing property of a Bayesian approach is margin
I’ve been building out a small suite of command-line tools for working with ChatGPT, GPT-4 and potentially other language models in the future. The three tools I’ve built so far …
A first attempt at identifying and cataloging DeepSeek's glitched tokens
These days, nearly all the artificial intelligence-based products in our lives rely on “deep neural networks” that automatically learn to process labeled data.
Pull up your agents folks, I'll convince you why Go is the best language for them.
After maintaining a total stance of public silence for months, I recently publicly announced my unexpected divorce on Instagram. I shared a picture of the divorce cake that my friends got for me, and shared a brief essay I had drafted the day before about the news. I had to edit it down slightly from my original draft…
Today I was setting up Hermes to see how it does with web research. I chose DeepSeek V4 because I know it is cheap, but seeing it’s pricing next to Anthropic and OpenAI ‘frontier’ models is crazy. Nearly a 50x price increase based on tokens alone, let alone how much pondering any of their models might fall into (using…
Last year I created a fun little experiment where I asked a bunch of LLMs to rank 97 hackernews users using their comment history based on whether they would be good candidates for the role of “software engineer at google”. (yes yes, seems silly I know, you can read part 1 and part 2 but […]
By ICML 2026 Program Chairs Alekh Agarwal, Miroslav Dudik, Sharon Li, Martin Jaggi, Scientific Integrity Chair Nihar B. Shah, and Communications Chairs Katherine Gorman and Gautam Kamath.
The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery
Improvements to data analysis in ChatGPT Interact with tables and charts and add files directly from Google Drive and Microsoft OneDrive.
[Twitter thread, Hacker News discussion, Le Monde]
Of all the forms of tech debt, decoherence is the worst. It compounds exponentially with a system's rate of change, and AI is now producing it faster than ever, leading us deeper and deeper into the abyss...
I trusted a lot today. I trusted my phone to wake me on time. I trusted Uber to arrange a taxi for me, and the driver to get me to the airport safely. I trusted thousands of other drivers on the road not to ram my car on the way. At the airport, I trusted ticket agents and maintenance engineers and everyone else who…
We need to augment our command line tools and design APIs so they can be better used by LLM Agents. The designs are inadequate for LLMs as they are now – especially if you're constrained by the tiny context windows available with local models.
This post covers my experience training image classification models with Intel’s PyTorch extension on the Arc A770 GPU.
We explore the history of image unblurring and present a simple yet effective technique to get a high-resolution image from a pixelated video in order to recover redacted information (with no guessing involved).
With the problem of Image Classification is more or less solved by Deep learning, Text Classification is the next new developing theme in deep learning. For those who don’t know, Text classification is a common task in natural language processing, which transforms a sequence of text of indefinite length into a…
We built a neural theorem prover for Lean that learned to solve a variety of challenging high-school olympiad problems, including problems from the AMC12 and AIME competitions, as well as two problems adapted from the IMO.
Modern AI systems approach tasks like recognising objects in images and predicting the 3D structure of proteins as a diligent student would prepare for an exam. By training on many example problems, they minimise their mistakes over time until they achieve success. But this is a solitary endeavour and only one of the…
AI plays well at complex strategy games with uncertainty and incomplete information.
Lessons learned from building Codescribble with a little help (and a lot of frustration) from an AI
Claude 3 Opus outperforms all of OpenAI’s models on Aider’s code editing benchmark, making it the best available model for pair programming with AI.
Last December, tens of thousands of Claude users around the world had a conversation with our AI interviewer to share how they use AI, what they dream it could make possible, and what they fear it might do.
