Computer simulations are invaluable tools for scientific discovery. However, accurate simulations are often slow to execute, which limits their applicability to extensive parameter exploration, large-scale data analysis, and uncertainty quantification. A promising route to accelerate simulations by building fast emulators with machine learning requires large training datasets, which can be prohibitively expensive to obtain with slow simulations. Here we present a method based on neural architecture search to build accurate emulators even with a limited number of training data. The method successfully accelerates simulations by up to 2 billion times in 10 scientific cases including astrophysics, climate science, biogeochemistry, high energy density physics, fusion energy, and seismology, using the same super-architecture, algorithm, and hyperparameters. Our approach also inherently provides emulator
uncertainty estimation, adding further confidence in their use. We anticipate this work will accelerate research involving expensive simulations, allow more
extensive parameters exploration, and enable new, previously unfeasible computational discovery.

A small DIY air purifier using off-the-shelf components for under $100.

Asciimatics is a package to help people create full-screen text UIs (from interactive forms to ASCII animations) on any platform.

This is a collection of common templates and documents I have been using over the years. I am tired of trying to google them every time I need them, so I just gathered them all here.

Topics are: Pitch, Vision, Strategy, Product Requirements, Technical Design, Product Opportunity Assessment, Product Vision, Run Book.

Clearview AI devised a groundbreaking facial recognition app. You take a picture of a person, upload it and get to see public photos of that person, along with links to where those photos appeared. The system — whose backbone is a database of more than three billion images that Clearview claims to have scraped from Facebook, YouTube, Venmo and millions of other websites — goes far beyond anything ever constructed by the United States government or Silicon Valley giants.

A gravity simulation using the runge kutter integration method.

Analyses of single-cell recordings from mouse ventral tegmental area are consistent with a model of reinforcement learning in which the brain represents possible future rewards not as a single mean of stochastic outcomes, as in the canonical model, but instead as a probability distribution.

Tetris game made using pygame and python.

Journal entry from 20 August 1999, introducing his new blog about The Lord of the Rings.