871
Topics /
AI & Machine Learning
The most popular blog posts about ai & machine learning on Hacker News. 3,091 posts.
872
Understanding large language models: A cross-section of the relevant literature
A Cross-Section of the Most Relevant Literature To Get Up to Speed
873
The deep learning boom caught almost everyone by surprise
"You’ve taken this idea way too far," a mentor told Prof. Fei-Fei Li.
874
Are the costs of AI agents also rising exponentially? (2025)
There is an extremely important question about the near-future of AI that almost no-one is asking. We’ve all seen the graphs from METR showing that the length of tasks AI agents can perform has been growing exponentially over the last 7 years. While GPT-2 could only do software engineering tasks t
875
Growing from 0 to 4M users on our fashion app with vertical machine learning
My name is Gabi (my bio), and I’m the CEO and co-founder of Chicisimo. We launched three years ago, our goal was to offer automated outfit…
876
877
How I changed teaching after AI managed to do all my homework assignments
AI forced me to abandon evidence-based best pedagogy practices, focus on oral and written exams, and redo most assignments. Here is what we did in 17-645...
878
Stable Diffusion Is the Most Important AI Art Model Ever
A state-of-the-art AI model available for everyone through a safety-centric open-source license is unheard of.
879
With AI you need to think bigger
I have noticed something in the past 12 months, something a little profound. I have noticed that I am no longer scared that a project will be too big or too complex for me, or that a project will use a technology or programming language I don’t know.
880
881
A Gentle Introduction to Bayes’ Theorem for Machine Learning
Bayes Theorem provides a principled way for calculating a conditional probability. It is a deceptively simple calculation, although it can be used to easily calculate the conditional probability of events where intuition often fails. Although it is a powerful tool in the field of probability, Bayes Theorem is also…
882
883
884
The availability of text generators will force positive changes to education
Teachers adapted to the calculator. They can certainly adapt to language models.
885
GPT-5: Overdue, overhyped and underwhelming. And that's not the worst of it
A new release botched … and a breaking research new paper that spells trouble
886
A non-technical explanation of deep learning
This document will explain what neural networks are and how they work, which will help you understand how AI and machine learning work. In the scenario below you'll play the part of the neural network.
887
AI Data Laundering
Tech companies working with AI are outsourcing data collection and training to academic/nonprofit research groups, shielding them from potential accountability and legal liability.
888
Pushing ChatGPT's Structured Data Support to Its Limits
“Function calling” with ChatGPT is ChatGPT’s best feature since ChatGPT.
889
890
Online art communities begin banning AI-generated images
Online art communities have started banning AI-generated art, while others are facing public pressure from their own members to take a stand.
891
892
If you don't run your own LLM proxy, how do you know whats going on?
I think the title captures the idea fully but I'll dig into it because this ain't Twitter. You're working an idea, a piece of code, or a multibillion a year SaaS app which is probably saving the world. Maybe you're automating the cloning process of grabbing
893
The bitter lesson is coming for tokenization
Highlights the desire to replace tokenization with a general method that better leverages compute and data. We'll see tokenization's fragility and review the Byte Latent Transformer arch.
894
Calculating the cost of a Google DeepMind paper
Recently, GDM released a great paper titled, Scaling Exponents Across Parameterizations and Optimizers, in which they conduct over 10,000 LLM training runs to obtain optimal hyperparameters under different regimes. After reading it (it was great), I wanted to test my understanding of the paper by tallying up all…
895
I fed 24 years of my blog posts to a Markov model
Yesterday I shared a little program called Mark V. Shaney Junior at github.com/susam/mvs . It is a minimal implementation of a Markov text generator inspired by the legendary Mark V. Shaney program from the 1980s. Mark V. Shaney was a synthetic Usenet user that posted messages to various newsgroups using text…
896
897
NVIDIA frenemy relation with OpenAI and Oracle
I’ve spent the last 48 hours completely falling down the rabbit hole of NVIDIA’s Q3 Fiscal 2026 earnings report . If you just skim the headlines, everything looks perfect: Revenue is up 62% to $57 billion, and Jensen Huang is talking about a "virtuous cycle of AI."
898
The Deep Research problem
OpenAI’s Deep Research is built for me, and I can’t use it. It’s another amazing demo, until it breaks. But it breaks in really interesting ways.
899
Probabilistic Programming and Bayesian Methods for Hackers (2013)
Bayesian Methods for Hackers : An intro to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view.
900
I accidentally turned LLM memory into program analysis
Why I stopped trying to give LLM agents a better memory and instead built Lemmalog, a Datalog engine that maintains an agent's knowledge as analysis state, with provenance, retractions and incremental evaluation, plus what happened when I benchmarked it on LongMemEval and LoCoMo.