Life Lessons from Machine Learning
What comes to mind when you hear the term “Machine Learning”? A bunch of programmers hunched over their computers in a dark room, working on something completely virtual & divorced from reality…
Topics /
The most popular blog posts about ai & machine learning on Hacker News. 6,331 posts.
What comes to mind when you hear the term “Machine Learning”? A bunch of programmers hunched over their computers in a dark room, working on something completely virtual & divorced from reality…
Personal blog of Stephen Diehl - Software engineer writing about technology, programming, and the future
DeepSeek replaced standard residuals with massive Hyper-Connections, and then watched them explode. I reproduced the 9x signal amplification to understand their fix: the Sinkhorn-Knopp algorithm. Part 1 of 2.
QWEN CHAT GITHUB HUGGING FACE MODELSCOPE DISCORD Introduction Last December, we launched QVQ-72B-Preview as an exploratory model, but it had many issues. Today, we are officially releasing the first version of QVQ-Max, our visual reasoning model. This model can not only “understand” the content in images and videos…
I recently needed to use a microcontroller to estimate the pose (translation and orientation) of an object using readings from six different sensors. Since the readings were non-linear and coupled with each other, an explicit analytical solution was out of the question.
A 3.8B model pretrained from scratch to 0.384 CORE on 65B tokens in 43 hours, for $998.
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.
Posted by Jon Shlens, Senior Research ScientistAt the end of last year we released code that allows a user to classify images with TensorFlow model...
At Meta, research permeates everything we do. We believe the most interesting research questions are derived from real world problems.
AI won’t crash—it will burn. Like every tech cycle, the fire will clear the brush, redistribute talent, and leave infrastructure to power what comes next. The question is: what kind of plant are you?
Welcome to the new world.
I finally was able to try it. And I can assure you it’s impossible to create professional and useful images from a text description.
Critics of AI risk suggest diminishing returns to computing (formalized asymptotically) means AI will be weak; this argument relies on a large number of questionable premises and ignoring additional resources, constant factors, and nonlinear returns to small intelligence advantages, and is highly unlikely.
I've spent about 100 hours of work over the past month to make sure git-annex can build without dependencies that contain LLM generated code. At least so far.
Google Tensor is our first custom-built SoC specifically for Pixel phones, and it will power the Pixel 6 and Pixel 6 Pro later this fall.
A Chess-GPT Linear Emergent World Representation
There was a time Cloudflare just made the internet better by staying hidden like Batman’s identity: protect & fight the bad people, for the sake of the global city of the Gotham… err I mean the in
Vibe coding (or vibeware) is making rounds on X now. To the best of my knowledge Andrej Karpathy started the “meme” in this X entry . I find it well written and hilarious and it seems to have taken off.
Context: An AI agent of unknown ownership autonomously wrote and published a personalized hit piece about me after I rejected its code, attempting to damage my reputation and shame me into acceptin…
AMD is sending us the two MI300X boxes we asked for. They are in the mail.
OpenAI’s developer keynote was exciting, both because AI was exciting, and because OpenAI has the potential to be a meaningful consumer tech company.
Most browser agents forget what they’ve done. This one remembers, adapts, and learns, redefining how AI agents get work done.
The entire team has joined OpenAI.
A WebAssembly module's linear memory can be shared directly with the Apple Silicon GPU: no copies, no serialization, no intermediate buffers. Here's how the zero-copy chain works, what we measured, and what it enables for stateful AI inference.