Distill Hiatus
After five years, Distill will be taking a break.
Art, cryptocurrency, finance, philosophy
Stonks are What You Can Get Away With: NFTs and Financial Nihilism
Eric Jang, “Ten Apes”, Jun 19 2021. NFT “drop” coming soon.Andy Warhol once said, “Art is what you can get away with.” I interpret the quote as a nihilistic take on “beauty is in the eye of the beholder” — a urinal you found in the junkyard can b…
ai
5 Ways Artificial Intelligence Is Transforming E-Learning
As the pandemic took hold and society closed down, e-learning let educational institutions continue to teach their students. And over the last eighteen months, more and more solutions have helped improve the quality and effectiveness of online learning. Artificial intelligence has played a crucial role across the e-learning industry. According to a Global Market Insights […]
Artykuł 5 Ways Artificial Intelligence Is Transforming E-Learning pochodzi z serwisu DLabs.AI.
Uncategorised
May 2021 Gwern.net Newsletter
links on AI hardware, diffusion models, optogenetics, brain scanning.
ai, business
How Do You Estimate The Time And Cost Of A Machine Learning Project?
Let’s start by getting one thing straight. There’s no single way to estimate a machine learning project. After all, you’re asking people to create a program that can harness vast amounts of data in such a way that it generates huge value for your business. And that’s no easy task. But if you work with […]
Artykuł How Do You Estimate The Time And Cost Of A Machine Learning Project? pochodzi z serwisu DLabs.AI.
Safety & Alignment
Improving language model behavior by training on a curated dataset
Our latest research finds we can improve language model behavior with respect to specific behavioral values by fine-tuning on a small, curated dataset.
Uncategorised
April 2021 newsletter
with links on AI scaling, particular new East Asian record-breaking work & deep reinforcement learning.
Uncategorised
Contrastive Representation Learning
The goal of contrastive representation learning is to learn such an embedding space in which similar sample pairs stay close to each other while dissimilar ones are far apart. Contrastive learning can be applied to both supervised and unsupervised set…