flâneur

A Bird's Eye View of the ML Field [Pragmatic AI Safety #2] — AI Alignment Forum

alignmentforum.org · 11,555 words · saved by 1 readers

The internal dynamics of the ML field are not immediately obvious to the casual observer. This post will present some important high-level points that are critical to beginning to understand the field, and is meant as background for our later posts. How is progress made in ML? While the exact dynamics of progress are not always predictable, we will present three basic properties of ML research that are important to understand. A problem well-defined is a problem half solved. —John Dewey (apocryphal) The mere formulation of a problem is often more essential than its solution, which [...] requires creative imagination and marks real advances in science. —Albert Einstein I have been struck by how important measurement is... This may seem basic, but it is amazing how often it is not done and how hard it is to get right. —Bill Gates If you cannot measure it, you cannot improve it. —Lord Kelvin (paraphrase) For better or worse, benchmarks shape a field. —David Patterson, Turing award winner

x A Bird's Eye View of the ML Field [Pragmatic AI Safety #2] — AI Alignment Forum Pragmatic AI Safety Machine Learning (ML) Emergent Behavior ( Emergence ) AI Frontpage 51 A Bird's Eye View of the ML Field [Pragmatic AI Safety #2] by Dan H , TW123 9th May 2022 43 min read 8 51 This is the second post in a sequence of posts that describe our models for Pragmatic AI Safety. The internal dynamics of the ML field are not immediately obvious to the casual observer. This post will present some important high-level points that are critical to beginning to understand the field, and is meant as backgro

saved by

related reading