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Science fiction hasn’t prepared us to imagine machine learning
It resembles the Library of Babel more than HAL.
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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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Why machine learning struggles with causality
Machine learning systems thrive on finding and exploiting statistical regularities. This is why they can't do causal reasoning.
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Data scientists shouldn’t need to know Kubernetes
[Hacker News discussion, Twitter thread]
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Fun and dystopia with AI-based code generation using GPT-J-6B
At the least, AI-generated code is much more readable than the average human’s.
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Baking with machine learning (2020)
Like many people, I’ve been entertaining myself at home by baking a ton. I’ve gotten pretty good at following recipes, but I decided I wanted to take things one step further and understand the science behind what differentiates a cake from a bread or a cookie. I also like machine learning so I thought: what if I could…
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Gaussian Processes from Scratch (2019)
This post explores some concepts behind Gaussian processes, such as stochastic processes and the kernel function. We will build up deeper understanding of Gaussian process regression by implementing them from scratch using Python and NumPy.
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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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Decoding the Peloton
From Voltages to "Cadence, Output, and Resistance" TL;DR - I’ve decoded (most of) the protocol that the Peloton bike uses to communicate with its head unit tablet and built a device,...
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Wav2vec Overview: Semi and Unsupervised Speech Recognition
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Gradient Descent Models Are Kernel Machines
This paper shows that models which result from gradient descent training (e.g., deep neural nets) can be expressed as a weighted sum of simi...
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Why I'm Lukewarm on Graph Neural Networks
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Review: The Book of Why
The Book of Why: The New Science of Cause and Effect is a collaborative effort aimed at a general audience by Judea Pearl , a professor of computer science at UCLA, and Dana Mackenzie , a science writer. As a medical student with a laughably poor formal education in statistics, I believe I qualify as a card-carrying…
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Learning with Not Enough Data: Semi-Supervised Learning
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GPT-J-6B: 6B JAX-Based Transformer
Summary: We have released GPT-J-6B, 6B JAX-based (Mesh) Transformer LM (Github).GPT-J-6B performs nearly on par with 6.7B GPT-3 (or Curie) on various zero-shot down-streaming tasks.You can try out …
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Speech to Birdsong Conversion
A blog about signals, programming, music, and other stuff.
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FastText is the best text classification library for a quick baseline
Text classification is a very frequent use case for machine learning (ML) and natural language processing (NLP). It’s used for things like spam detection in emails, sentiment analysis for social media posts, or intent detection in chat bots. In this series I am going to compare several libraries that can be used to…
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Is Google’s AI research about to implode?
What does Timnit Gebru’s firing and the recent papers coming out of Google tell us about the state of research at the world’s biggest AI…
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Marc Andreessen on Investing and Tech
Transcript of interview on how tech changes the world
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Ray: A Distributed Framework for Emerging AI Applications
Ray: A Distributed Framework for Emerging AI Applications Moritz, Nishihara, Wang et. al.
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Inverting PhotoDNA
Ribosome inverts Microsoft PhotoDNA hashes using machine learning.
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Reasonable Effectiveness of the Multiplicative Weights Update Algorithm (2017)
papad Hard to believe Sanjeev Arora and his coauthors consider it “a basic tool [that should be] taught to all algorithms students together with divide-and-conquer, dynamic programming, and random sampling.” Christos Papadimitriou calls it “so hard to believe that it has been discovered five times and forgotten.” It…
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Mastering Real-Time Strategy Games with Deep RL: Mere Mortal Edition
The capabilities of game-playing AIs have grown rapidly over the last few years. This trend has culminated in the defeat of top human players in the complex real-time strategy (RTS) games of DoTA 2…
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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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GitHub Copilot: First Impressions
A glimpse of the upcoming paradigm shift in how we do development
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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…