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Rich Sutton's March 2019 essay arguing that the biggest lesson from 70 years of AI research is that general methods leveraging computation ultimately prove most effective, by a large margin. Sutton walks through prominent cases — computer chess, Go, speech recognition, and computer vision — where approaches built on human knowledge were outdone by search and learning methods that scaled with computing power. He attributes the pattern to the steadily falling cost of computation and warns that relying on human knowledge tends to complicate methods in ways that limit scaling.
#AI research#essay#compute#search and learning#Rich Sutton#machine learning
A nonprofit research institute focused on basic AI research into how minds arise from computation. Its site frames minds as computational entities capable of goal-directed adaptive behavior in open, uncertain worlds, and lists open questions such as how minds learn in real time from sensorimotor experience and how synthetic and human minds can cooperate. The institute builds on The Alberta Plan for AI Research, says all results will be shared publicly with no intellectual property restrictions, and is recruiting research fellows.
#AI research#reinforcement learning#open science#The Alberta Plan#research institute#basic research
The personal site of François Chollet, software engineer and AI researcher, co-founder of Ndea and the ARC Prize. It collects his books (including Deep Learning with Python), software, papers, essays and talks, and describes his research interests: the nature of abstraction, autonomous abstraction algorithms, and democratizing AI development.
The home page of the Stanford Artificial Intelligence Laboratory, a center for AI research, teaching, theory and practice since its founding in 1963. The site lists faculty, research groups, affiliated centers, courses, events and lab news.
The Decoder report on comments from Boris Power, OpenAI's Head of Applied Research, that most of the company's research targets future model generations, and that user awareness of AI capabilities lags model performance.
An interactive case study walking through a two-day investigation that recovered the machine settings for MVUEH, an 82-letter German Army Enigma message from July 10, 1941, with source comparisons, experiments and checks readers can reproduce. Published by an individual on a ChatGPT-hosted site; its claims have not been independently reviewed.
