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The most popular blog posts about ai & machine learning on Hacker News. 6,331 posts.
What is a predictive database? A database that lets you query predictions from structured tabular data with no model training step. Learn how predictive databases work, when to use them, and how they compare to traditional ML.
To advance research on AI that can understand others’ points of view and collaborate effectively, Facebook AI has developed a bot that sets a new state of the art in Hanabi, a card game in which all players work together.
This blog post is based on the work BaNEL: Exploration Posteriors for Generative Modeling Using Only Negative Rewards. Tackling Very Hard Problems The ultimate aim of machine learning research is to push machines beyond human limits in critical applications, including the next generation of th
I have been meaning for a while to establish a setup to implement neural network based algorithms on smaller microcontrollers. After reviewing existing solutions, I felt there is no solution that I…
Vector similarity search is a game-changer in the world of search. It allows us to efficiently search a huge range of media, from GIFs to articles — with incredible accuracy in sub-second timescales for billion+ size datasets.
Intel Search Results Page
This is the first of a two-part series about Bayesian bandit algorithms. Check out the second post here. Let’s talk about Bayesianism. It’s developed a reputation (not entirely justified, but not entirely unjustified either) for being too mathematically sophisticated or too computationally intensive to work at scale…
The latest information about the Unconference is now available at the Unconference wiki, which will be periodically updated with more information for attendees.
A machine learning craftsmanship blog.
· Read in · 1499 words · All posts in series · [dropcap]This[/dropcap] trick is unlike the others we’ve conjured. It will not reveal a clever manipulation of a probability or an integral or a…
📍 This article has moved. Read the current version at This is the third part in a short series of blog posts about quantum Monte Carlo (QMC). The series is derived from an introductory lecture I ga…
Language is made of discrete structures, yet neural networks operate on continuous data: vectors in high-dimensional space. A successful language-processing network must translate this symbolic information into some kind of geometric representation—but in what form? Word embeddings provide two well-known examples…
OpenAI sent Governor Greg Abbott a letter outlining its commitment to responsible AI infrastructure in Texas. The letter supports reliable, transparent growth that benefits Texans.
Model licensing & surveillance will likely be counterproductive by concentrating power in unsustainable ways
I think I've spoken at length in other places about how I am a very staunch AI hater and covered everything I hate about how the tech is pre...
Obligatory: the views and opinions expressed in this post are my own and do not represent the views and opinions of my employer. In light of all the hype going around about ChatGPT, I wanted to offer my “hot take” on what the next 2-5 years
How AI hype leads to flawed research that fuels more hype
We evaluate three leading AI models—Claude Sonnet 4.5, Gemini 2.5 Pro, and GPT-5—on their ability to solve Google reCAPTCHA v2 challenges and find significant performance differences, with success rates ranging from 28% to 60%.
A cautionary tale.
In his TED Talk, Stephen Wolfram covers the emergence of space by the application of computational rules to spacetime, gravity and quantum mechanics to AI and LLMs. Computational irreducibility and the ruliad.
Labs at Stanford and MIT built Claude-powered systems that run genome-wide studies in minutes and automate gene cluster interpretation.
