The idea that you could create human level intelligence by just feeding raw data into the right math-inspired architecture is pure fantasy.
This seems profoundly and obviously wrong to me. AIXI and similar approaches look, to me, like the obvious future of the field. The work left to be done is in soldifying the underlying math, and finding efficient approximations and speedups to make the algorithms practical for real-world problems.
Today's post, Shared AI Wins was originally published on December 6, 2008. A summary:
AIs do have enormous difficulties in communicating. That's why decreasing those difficulties is important. Collections of AIs that are able to share data, like ems, are more likely to succeed at making new developments.
Discuss the post here (rather than in the comments to the original post).
This post is part of the Rerunning the Sequences series, where we'll be going through Eliezer Yudkowsky's old posts in order so that people who are interested can (re-)read and discuss them. The previous post was Is That Your True Rejection?, and you can use the sequence_reruns tag or rss feed to follow the rest of the series.
Sequence reruns are a community-driven effort. You can participate by re-reading the sequence post, discussing it here, posting the next day's sequence reruns post, or summarizing forthcoming articles on the wiki. Go here for more details, or to have meta discussions about the Rerunning the Sequences series.