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The most popular blog posts about ai & machine learning on Hacker News. 212 posts.
Engineer friends often ask me: Graph Deep Learning sounds great, but are there any big commercial success stories? Is it being deployed in practical applications? Besides the obvious ones–recommendation systems at Pinterest, Alibaba and Twitter–a slightly nuanced success story is the Transformer architecture, which…
The Game of Life is based on very simple rules, but artificial neural networks struggle to learn its rules through the classic deep learning training process.
2020 has been a heap of bad. And not small bad either. As we’ve been stuck at home, viewing the world through either real or virtual…
The past week was a momentous occasion for protein structure prediction, structural biology at large, and in due time, may prove to be so for the whole of life sciences. CASP14, the conference for …
One of my favorite ¹ concepts for multi-dimensional data visualization is the Chernoff Face . The idea here is that for a dataset with many...
Building a simple neural net in Java.
We are releasing HiPlot, a lightweight interactive visualization tool to help AI researchers discover correlations and patterns in high-dimensional data.
In our study published in Nature, we demonstrate how artificial intelligence research can drive and accelerate new scientific discoveries. We’ve built a dedicated, interdisciplinary team in hopes of using AI to push basic research forward: bringing together experts from the fields of structural biology, physics, and…
Today Lyft is excited to announce the open sourcing of Flyte, a structured programming and distributed processing platform for highly…
Posted by Thomas Müller, Software Engineer, Google Research Much of the world’s information is stored in the form of tables, which can be found o...
Posted by James Wexler, Software Engineer, Google AI Building effective machine learning (ML) systems means asking a lot of questions. It's not eno...
Chatops is a ladder
The much anticipated NVIDIA GeForce RTX3080 has been released. How good is it with TensorFlow for machine learning? How about molecular dynamics with NAMD? I've got some preliminary numbers for you!
Lambdaclass's blog about distributed systems, machine learning, compilers, operating systems, security and cryptography.
An overview of self-supervised pretext tasks in Natural Language Processing
In this article, I cover the theory behind receipt digitization and implement an end-to-end pipeline using OpenCV and Tesseract. I also review a few important papers that do Receipt Digitization using Deep Learning.
If you read a description of a static analysis in a paper, what might you find? There’ll be some cute model of a language. Maybe some inference rules describing the analysis itself, but those rules probably rely on a variety of helper functions. These days, the analysis likely involves some logical reasoning: about…
This article explains how recurrent neural networks (RNN's) work without using the neural network metaphor. It uses a visually-focused data-transformation perspective to show how RNNs encode variable-length input vectors as fixed-length embeddings. Included are PyTorch implementation notebooks that use just linear…
In August 2024, we published the next phase of our work in Science. Our research proposes a solution to one of the most difficult challenges in computational quantum chemistry: understanding how molecules transition to and from excited states when stimulated.
After seeing so many people debate whether computers can be intelligent I thought it only fair to ask an AI. As with previous posts, I picked the best responses, but everything after the bolded pro…
A few weeks ago I wrote about Kuhn’s theory of paradigm shifts and how it relates to Bayesian inference. In this post I want to back up a little bit and explain what Bayesian inference is, and eventually rediscover the idea of a paradigm shift just from understanding how Bayesian inference works.
Baidu publishes PP-YOLO and pushes the state of the art in object detection research by building on top of YOLOv3, the PaddlePaddle deep learning framework, and cutting edge computer vision research.
