A different take — when LLMs allow people to summarise (more or less) infinite amounts of content, attention will cease to be a bottleneck as it once was. The attention economy is an imbalance of two things: - broad-casting scale: 1 person can talk to 1 million - broad-listening

Each day it becomes clearer that the ease of generating high-quality long form text is creating supply that far exceeds demand. That makes some things more valuable: curation, verification, contextualization, and synthesis. Taste, theory of mind and discernment is all you need ;)

You spend more time on social media than you intend to, because time flows faster on these platforms, causing you to lose hours in what feels like minutes. This is no accident; it’s a result of a decades-long plot to steal your time. My new essay. gurwinder.blog/p/how-social-m…

America needs to take open models more seriously. This summer the early lead in open model adoption of the US via Llama has been overtaken by Chinese models. With The American Truly Open Models (ATOM) Project we're looking to build support and express the urgency of this issue.

A day and a half out from the launch of ATOM, one thing is very clear about open models compared to years past: it's no longer a minority position. Below is a list of notable signatories (w over 200 in total). People from every corner of the AI community have signed on. People

Major AI breakthroughs usually require a step-function change in data or compute. The present moment contains neither.

Concentration of power. This is bad.

From ⿻ Andrew Trask in 2020. Keep an eye on OpenMined... goodreads.com/author/show/15…

What futures could, and should, we create with advanced AI? Today we are announcing two possible paths – Tool AI and d/acc – with contributors like vitalik.eth Kev.Ξth is cooking GG24 🍲✨ Adam Marblestone and Anthony Aguirre