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Grok {Shan, Shui}*: Advent of understanding the generative art
I spent 24 days digging into the code of {Shan, Shui}* Chinese painting generator and lived to tell the story.
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The latest blog posts to take off on Hacker News. 80 posts.
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Trade-Offs in Automatic Differentiation: TensorFlow, PyTorch, Jax, and Julia
To understand the differences between automatic differentiation libraries, let’s talk about the engineering trade-offs that were made. I would personally say that none of these libraries are “better” than another, they simply all make engineering trade-offs based on the domains and use cases they were aiming to…
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Inverting PhotoDNA
Ribosome inverts Microsoft PhotoDNA hashes using machine learning.
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The Hyperbolic Geometry of DMT Experiences (2016)
[Content Warning: Trying to understand the contents of this essay may be mind-warping. Proceed with caution. Featured image credit: Paul Nylander] Friends, right here and now, one quantum away, the…
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The future of artificial intelligence is self-organizing and self-assembling
This is the first post in a series I plan to write on the work from our group and others that combines ideas from deep learning with ideas from self-organization and collective systems. In this first post, we’ll look at some of the developed approaches and the domains they have…
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How a Kalman filter works, in pictures
I have to tell you about the Kalman filter, because what it does is pretty damn amazing.
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Learning with Not Enough Data: Semi-Supervised Learning
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Lessons from a year of AI research
Made in Notion, the connected workspace where AI agents and teams organize docs, projects and knowledge together.
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Neural-control family: what deep learning and control enables in the real world
With the unprecedented advances of modern machine learning comes the tantalizing possibility of smart data-driven autonomous systems across a broad range of real-world settings. However, is machine learning (especially deep learning) really ready to be deployed in safety-critical systems?
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Is my cat Turing-complete?
This article is an adaptation of a Lightning Talk I gave at CppCon2021. Link here : https://www.youtube.com/watch?v=RtqTGSOdmBo
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Ancient secrets of computer vision
This class is a general introduction to computer vision. It covers standard techniques in image processing like filtering, edge detection, stereo, flow, etc. (old-school vision), as well as newer, machine-learning based computer vision. It was originally offered in the spring of 2018 at the University of Washington .
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Zillow just gave us a look at machine learning's future
It's put up or shut up time for Data Science teams. When the business depends on our work for revenue growth, success is expected. Failure is fatal.
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Self-parking Car in 500 Lines of Code
Training the car to do self-parking using a genetic algorithm
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Data scientists shouldn’t need to know Kubernetes
[Hacker News discussion, Twitter thread]
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The First Rule of Machine Learning: Start Without Machine Learning
Why this is the first rule, some baseline heuristics, and when to move on to machine learning.
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Robots Must Be Ephemeralized
There is a subfield of robotics research called “sim-to-real” (sim2real) whereby one attempts to solve a robotic task in simulation, and the...
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Turing Oversold?
It is not the fault of Turing, though.
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AI movie posters
Guess the movie based on an AI’s visual interpretation of the plot.
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Tesla Project Dojo Overview
A couple of days back, Ganesh Venkataramanan, leader of the Tesla Dojo project, announced the Dojo machine learning training system. It’s an unusually network rich, power dense, and memory light design. I’ve summarized the architecture of the system below but I found three aspects of the system particularly…
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Machine learning’s crumbling foundations
Technological debt is insidious, a kind of socio-infrastructural subprime crisis that's unfolding around us in slow motion. Our digital infrastructure is built atop layers and layers and layers of code that's insecure due to a combination of bad practices and bad frameworks.
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Marc Andreessen on Investing and Tech
Transcript of interview on how tech changes the world
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Intro to Deep Learning
I just sat down this morning and organized all deep learning related videos I recorded in 2021. I am sure this will be a useful reference for my future…
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Simulating worlds on the GPU: Four billion years in four minutes
This post delves into the implementation of my procedural earth simulation, written entirely in GLSL fragment shaders. It simulates the complete history of an earth-like planet in a few minutes, with the simulation updating at 60 frames per second.
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Useful algorithms that are not optimized by Jax, PyTorch, or TensorFlow
In some previous blog posts we described in details how one can generalize automatic differentiation to give automatically stability enhancements and all sorts of other niceties by incorporating graph transformations into code generation. However, one of the things which we didn’t go into too much is the limitation of…
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GitHub Copilot: First Impressions
A glimpse of the upcoming paradigm shift in how we do development